Nonlinearity in parallel compliance can be exploited to improve the performance of locomotion systems in terms of(1)energy efficiency,(2)control robustness,and(3)gait optimality;that is,attaining energy efficiency acr...Nonlinearity in parallel compliance can be exploited to improve the performance of locomotion systems in terms of(1)energy efficiency,(2)control robustness,and(3)gait optimality;that is,attaining energy efficiency across a set of motions.Thus far,the literature has investigated and validated only the first two benefits.In this study,we present a new mathematical framework for designing nonlinear compliances in cyclic tasks encompassing all three benefits.We present an optimization-based formulation for each benefit to obtain the desired compliance profile.Furthermore,we analytically prove that,compared to linear compliance,using nonlinear compliance leads to(1)lower energy consumption,(2)better closed-loop performance,specifically in terms of tracking error,and(3)a higher diversity of natural frequencies.To compare the performance of linear and nonlinear compliance,we apply the proposed methods to a diverse set of robotic systems performing cyclic tasks,including a 2-DOF manipulator,a 3-DOF bipedal walker,and a hopper model.Compared to linear compliance,the nonlinear compliance leads to better performance in all aspects;for example,a 70%reduction in energy consumption and tracking error for the manipulator simulation.Regarding gait optimality,for all robotic simulation models,compared to linear compliance,the nonlinear compliance has lower energy consumption and tracking error over the considered set of motions.The proposed analytical studies and simulation results strongly support the idea that using nonlinear compliance significantly improves robotic system performance in terms of energy efficiency,control robustness,and gait optimality.展开更多
Numerous uncertainties in practical production and operation can seriously affect the drive performance of permanent magnet synchronous machines(PMSMs).Various robust control methods have been developed to mitigate or...Numerous uncertainties in practical production and operation can seriously affect the drive performance of permanent magnet synchronous machines(PMSMs).Various robust control methods have been developed to mitigate or eliminate the effects of these uncertainties.However,the robustness to uncertainties of electrical drive systems has not been clearly defined.No systemic procedures have been proposed to evaluate a control system's robustness(how robust it is).This paper proposes a systemic method for evaluating control systems'robustness to uncertainties.The concept and fundamental theory of robust control are illustrated by considering a simple uncertain feedback control system.The effects of uncertainties on the control performance and stability are analyzed and discussed.The concept of design for six-sigma(a robust design method)is employed to numerically evaluate the robustness levels of control systems.To show the effectiveness of the proposed robustness evaluation method,case studies are conducted for second-order systems,DC motor drive systems,and PMSM drive systems.Besides the conventional predictive control of PMSM drive,three different robust predictive control methods are evaluated in terms of two different parametric uncertainty ranges and three application requirements against parametric uncertainties.展开更多
This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper cons...This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters.展开更多
The Nelder-Mead simplex method is a well-known algorithm enabling the minimization of functions that are not available in closed-form and that need not be differentiable or convex.Furthermore,it is particularly parsim...The Nelder-Mead simplex method is a well-known algorithm enabling the minimization of functions that are not available in closed-form and that need not be differentiable or convex.Furthermore,it is particularly parsimonious on the number of function evaluations,thus making it preferable to convex optimization paradigms in the case,common when dealing with control design problems,that the objective function of the optimization problem is non-differentiable,non-convex,and its closed-form is not available or difficult to be computed analytically.The main goal of this paper is to show how the joint use of the Nelder-Mead simplex method and the Morrison algorithm can be successfully used to solve relevant and challenging control problems that cannot be easily solved using analytic methods.In particular,it is shown how the problems of strong stabilization,static output feedback stabilization,and design of robust controllers having fixed structure can be framed as optimization problems,which,in turn,can be efficiently solved by coupling the two above mentioned algorithms.The performance of this procedure is compared with state-of-the-art techniques on dozens of static output feedback benchmark case studies,and its effectiveness is demonstrated by several examples.展开更多
The increasing demand for artillery firepower,coupled with the growing size of gun barrels,imposes significant challenges on servo system performance.To address these challenges while ensuring fast and stable response...The increasing demand for artillery firepower,coupled with the growing size of gun barrels,imposes significant challenges on servo system performance.To address these challenges while ensuring fast and stable response,this paper proposes an adaptive robust controller based on an asymmetric barrier Lyapunov function(ABLF).The controller design incorporates both load and driver states through a backstepping synthesis.The overshoot and lag of barrel position errors are constrained within asymmetric boundaries,accounting for complex rotational uncertainties via an adaptive law and linear extended state observers(LESO).Simulations and experiments under typical artillery operating conditions validate the effectiveness and dynamic tracking performance of the proposed control strategy in comparison with other methods.展开更多
With the prevalence of renewable distributed energy resources(DERs)such as photovoltaics(PVs),modern active distribution networks(ADNs)suffer from voltage deviation and power quality issues.However,traditional voltage...With the prevalence of renewable distributed energy resources(DERs)such as photovoltaics(PVs),modern active distribution networks(ADNs)suffer from voltage deviation and power quality issues.However,traditional voltage control methods often face a trade-off between efficiency and effectiveness,and rarely ensure robust voltage safety under typical state perturbations in practical distribution grids.In this paper,a robust model-free voltage regulation approach is proposed which simultaneously takes security and robustness into account.In this context,the voltage control problem is formulated as a constrained Markov decision process(CMDP).A safety-augmented multiagent deep deterministic policy gradient(MADDPG)algorithm is the trained to enable real-time collaborative optimization of ADNs,aiming to maintain nodal voltages within safe operational limits while minimizing total line losses.Moreover,a robust regulation loss is introduced to ensure reliable performance under various state perturbations in practical voltage controls.The proposed regulation algorithm effectively balance efficiency,safety,and robustness,and also demonstrates potential for generalizing these characteristics to other applications.Numerical studies vali-date the robustness of the proposed method under varying state perturbations on the IEEE test cases and the optimal integrated control performance when compared to other benchmarks.展开更多
Photovoltaic(PV)systems in the field operate under complex,uncertain conditions rapid irradiance ramps,partial shading,temperature swings,surface soiling,and weak-grid disturbances including off-nominal frequency and ...Photovoltaic(PV)systems in the field operate under complex,uncertain conditions rapid irradiance ramps,partial shading,temperature swings,surface soiling,and weak-grid disturbances including off-nominal frequency and voltage distortion that degrade energy yield and power quality.We propose a drift-aware,power-quality-constrained MPPT framework that co-optimizes MPPT,PLL,and current-loop gains under stochastic frequency drift,while enforcing IEEE-519 limits(per-order Ih/IL and TDD)during optimization.Unlike energy-only or THD-only methods,the design target integrates PQ constraints into the objective and is validated across calibrated drift scenarios with explicit per-order and TDD reporting.Operating scenarios are calibrated to Cameroon’s Southern Interconnected Grid and city-specific profiles(Douala/Yaoundé),combining measured-style irradiance/temperature traces,partial-shading patterns,and stochastic frequency drift up to±0.8 Hz with synthetic contingencies.Across a 30-scenario campaign,the proposed controller achievesηMPPT=99.3%–99.6%(vs.98.6%Incremental Conductance and 97.8%Perturb-and-Observe),lowers DC-link ripple by 35%–48%,reduces oscillatory PCC power by≈41%,maintains THD≤2.5%(5%limit)and PF≥0.99,and shortens irradiance-step settling from 85–110 ms to 50–65 ms.Sensitivity to PLL bandwidth shows a broad optimum(≈60–90 Hz)with minimum THD/ripple,and ablations confirm that explicit drift weighting is pivotal to ripple and THD suppression without sacrificing yield.The approach is controller-agnostic,firmware-deployable,and generalizes to other converter-interfaced renewables;we outline a short hardware-/HIL-validation path for adoption in Sub-Saharan grids.展开更多
In this paper, we present a quantitative analysis of the robustness of a generalized predictive controller. The result of stability analysis shows that, under a specific bounded modelling error, the closed-loop system...In this paper, we present a quantitative analysis of the robustness of a generalized predictive controller. The result of stability analysis shows that, under a specific bounded modelling error, the closed-loop system is BIBO stable in the presence of unmodelled dynamics.展开更多
A robustness-tracking control scheme based on combining H_∞ robust control and sliding mode control is proposed for a direct drive AC permanent-magnet linear motor servo system to solve the conflict between tracking ...A robustness-tracking control scheme based on combining H_∞ robust control and sliding mode control is proposed for a direct drive AC permanent-magnet linear motor servo system to solve the conflict between tracking and robustness of the linear servo system. The sliding mode tracking controller is designed to ensure the system has a fast tracking characteristic to the command, and the H_∞ robustness controller suppresses the disturbances well within the close loop(including the load and the end effect force of linear motor etc.) and effectively minimizes the chattering of sliding mode control which influences the steady state performance of the system. Simulation results show that this control scheme enhances the track-command-ability and the robustness of the linear servo system, and in addition, it has a strong robustness to parameter variations and resistance disturbances.展开更多
This paper tackles uncertainties between planning and actual models.It extends the concept of RCI(robust control invariant)tubes,originally a parameterized representation of closed-loop control robustness in tradition...This paper tackles uncertainties between planning and actual models.It extends the concept of RCI(robust control invariant)tubes,originally a parameterized representation of closed-loop control robustness in traditional feedback control,to the domain of motion planning for autonomous vehicles.Thus,closed-loop system uncertainty can be preemptively addressed during vehicle motion planning.This involves selecting collision-free trajectories to minimize the volume of robust invariant tubes.Furthermore,constraints on state and control variables are translated into constraints on the RCI tubes of the closed-loop system,ensuring that motion planning produces a safe and optimal trajectory while maintaining flexibility,rather than solely optimizing for the open-loop nominal model.Additionally,to expedite the solving process,we were inspired by L2gain to parameterize the RCI tubes and developed a parameterized explicit iterative expression for propagating ellipsoidal uncertainty sets within closedloop systems.Furthermore,we applied the pseudospectral orthogonal collocation method to parameterize the optimization problem of transcribing trajectories using high-order Lagrangian polynomials.Finally,under various operating conditions,we incorporate both the kinematic and dynamic models of the vehicle and also conduct simulations and analyses of uncertainties such as heading angle measurement,chassis response,and steering hysteresis.Our proposed robust motion planning framework has been validated to effectively address nearly all bounded uncertainties while anticipating potential tracking errors in control during the planning phase.This ensures fast,closed-loop safety and robustness in vehicle motion planning.展开更多
The electromagnetic levitation system(EMLS)serves as the most important part of any magnetic levitation system.However,its characteristics are defined by its highly nonlinear dynamics and instability.Furthermore,the u...The electromagnetic levitation system(EMLS)serves as the most important part of any magnetic levitation system.However,its characteristics are defined by its highly nonlinear dynamics and instability.Furthermore,the uncertainties in the dynamics of an electromagnetic levitation system make the controller design more difficult.Therefore,it is necessary to design a robust control law that will ensure the system’s stability in the presence of these uncertainties.In this framework,the dynamics of an electromagnetic levitation system are addressed in terms of matched and unmatched uncertainties.The robust control problem is translated into the optimal control problem,where the uncertainties of the electromagnetic levitation system are directly reflected in the cost function.The optimal control method is used to solve the robust control problem.The solution to the optimal control problem for the electromagnetic levitation system is indeed a solution to the robust control problem of the electromagnetic levitation system under matched and unmatched uncertainties.The simulation and experimental results demonstrate the performance of the designed control scheme.The performance indices such as integral absolute error(IAE),integral square error(ISE),integral time absolute error(ITAE),and integral time square error(ITSE)are compared for both uncertainties to showcase the robustness of the designed control scheme.展开更多
This paper investigates the prescribed-time tracking control problem for a class of multi-input multi-output(MIMO)nonlinear strict-feedback systems subject to non-vanishing uncertainties. The inherent unmatched and no...This paper investigates the prescribed-time tracking control problem for a class of multi-input multi-output(MIMO)nonlinear strict-feedback systems subject to non-vanishing uncertainties. The inherent unmatched and non-vanishing uncertainties make the prescribed-time control problem become much more nontrivial. The solution to address the challenges mentioned above involves incorporating a prescribed-time filter, as opposed to a finite-time filter, and formulating a prescribed-time Lyapunov stability lemma(Lemma 5). The prescribed-time Lyapunov stability lemma is based on time axis shifting time-varying yet bounded gain, which establishes a novel link between the fixed-time and prescribed-time control method. This allows the restriction condition that the time-varying gain function must satisfy as imposed in most exist prescribed-time control works to be removed. Under the proposed control method, the desire trajectory is ensured to closely track the output of the system in prescribed time. The effectiveness of the theoretical results are verified through numerical simulation.展开更多
Due to errors in vehicle dynamics modeling,uncertainty in model parameters,and disturbances from curvature,the performance of the path tracking controller is poor or even unstable under high-speed and large-curvature ...Due to errors in vehicle dynamics modeling,uncertainty in model parameters,and disturbances from curvature,the performance of the path tracking controller is poor or even unstable under high-speed and large-curvature conditions.Therefore,a path tracking robust control strategy based on force-driven H_(∞)and MPC is proposed.To fully exploit the nonlinear dynamics characteristics of tires,a force-driven state space model of a path tracking system based on a linear time-varying tire model is established;the H_(∞)and MPC methods are used to design a robust controller.Considering disturbance and system state constraints,the robust control constraint model based on LMI is established.Finally,the proposed controller is validated through joint simulations using CarSim and MATLAB.The results show that the maximum lateral deviation is reduced by 17.07%,and the maximum course angle deviation is reduced by 13.04%under large curvature disturbance conditions.The maximum lateral deviation is reduced by 27.85%,and the maximum course angle deviation is reduced by 31.17%under conditions of uncertain road adhesion coefficients.Based on the controller’s performance,the proposed controller effectively mitigates modeling errors,parameter uncertainties,and curvature disturbances.展开更多
The paper develops a robust control approach for nonaffine nonlinear continuous systems with input constraints and unknown uncertainties. Firstly, this paper constructs an affine augmented system(AAS) within a pre-com...The paper develops a robust control approach for nonaffine nonlinear continuous systems with input constraints and unknown uncertainties. Firstly, this paper constructs an affine augmented system(AAS) within a pre-compensation technique for converting the original nonaffine dynamics into affine dynamics. Secondly, the paper derives a stability criterion linking the original nonaffine system and the auxiliary system, demonstrating that the obtained optimal policies from the auxiliary system can achieve the robust controller of the nonaffine system. Thirdly, an online adaptive dynamic programming(ADP) algorithm is designed for approximating the optimal solution of the Hamilton–Jacobi–Bellman(HJB) equation.Moreover, the gradient descent approach and projection approach are employed for updating the actor-critic neural network(NN) weights, with the algorithm's convergence being proven. Then, the uniformly ultimately bounded stability of state is guaranteed. Finally, in simulation, some examples are offered for validating the effectiveness of this presented approach.展开更多
In order to enhance the dynamic control precision of inertial stabilization platform(ISP),a disturbance sliding mode observer(DSMO)is proposed in this paper suppressing disturbance torques inherent within the system.T...In order to enhance the dynamic control precision of inertial stabilization platform(ISP),a disturbance sliding mode observer(DSMO)is proposed in this paper suppressing disturbance torques inherent within the system.The control accuracy of ISP is fundamentally circumscribed by various disturbance torques in rotating shaft.Therefore,a dynamic model of ISP incorporating composite perturbations is established with regard to the stabilization of axis in the inertial reference frame.Subsequently,an online estimator for control loop uncertainties based on the sliding mode control algorithm is designed to estimate the aggregate disturbances of various parameters uncertainties and other unmodeled disturbances that cannot be accurately calibrated.Finally,the proposed DSMO is integrated into a classical proportional-integral-derivative(PID)control scheme,utilizing feedforward approach to compensate the composite disturbance in the control loop online.The effectiveness of the proposed disturbance observer is validated through simulation and hardware experimentation,demonstrating a significant improvement in the dynamic control performance and robustness of the classical PID controller extensively utilized in the field of engineering.展开更多
An innovative design method is outlined in this paper for the pointing control mechanism of large space flexible antennas.This method focuses on enhancing the accuracy and stability that are crucial for large spacecra...An innovative design method is outlined in this paper for the pointing control mechanism of large space flexible antennas.This method focuses on enhancing the accuracy and stability that are crucial for large spacecraft applications,such as space solar power stations.Utilizing potential energy function analysis,the dynamics of the antenna are modeled,treating it as an equivalent n-joint robotic arm.This approach simulates the rigid-flexible coupling effect through joint angle manipulations.The proposed HJI(Hamilton-Jacobi-Inequality)sliding mode robust control integrates HJI principle,dissipative system theory,and sliding mode control,offering improved pointing accuracy and robustness.Simulation results underscore the superiority of HJI sliding mode robust control over traditional PD(proportional-derivative)control in initial response,precision,and control smoothness,albeit at the cost of higher control torque requirements.This research underscores the potential of HJI sliding mode robust control in facilitating precise pointing control for future large space structures,enabling efficient space missions and reliable energy transmission.展开更多
Lithography machines operate in scanning mode for the fabrication of large-scale integrated circuits(ICs),requiring high-precision synchronous motion between the reticle and wafer stages.Disturbances generated by each...Lithography machines operate in scanning mode for the fabrication of large-scale integrated circuits(ICs),requiring high-precision synchronous motion between the reticle and wafer stages.Disturbances generated by each stage during high-acceleration movements are transmitted through the base frame,resulting in degradation of synchronization performance.To address this challenge,this paper proposes a tube-based model predictive control(tube-MPC)approach for synchronization in lithography machines.First,the proposed modeling method accurately characterizes the coupling disturbances and synchronization dynamics.Subsequently,a tube-MPC approach is developed to ensure that the states of the nominal system are constrained within the terminal constraint set.To reduce the complexity of online computations,an approach is employed to transform online optimization problems into offline problems by creating an online lookup table.This enables the determination of optimal control inputs via a simplified online optimization algorithm.The robustness and trajectory tracking performance of the proposed approach are verified through simulation experiments,demonstrating its effectiveness in enhancing the synchronization performance of multiple motion systems.展开更多
As a crucial component of intelligent chassis systems,air suspension significantly enhances driver comfort and vehicle stability.To further improve the adaptability of commercial vehicles to complex and variable road ...As a crucial component of intelligent chassis systems,air suspension significantly enhances driver comfort and vehicle stability.To further improve the adaptability of commercial vehicles to complex and variable road conditions,this paper proposes a linear motor active suspension with quasi-zero stiffness(QZS)air spring system.Firstly,a dynamic model of the linear motor active suspension with QZS air spring system is established.Secondly,considering the random uncertainties in the linear motor parameters due to manufacturing and environmental factors,a dynamic model and state equations incorporating these uncertainties are constructed using the polynomial chaos expansion(PCE)method.Then,based on H_(2) robust control theory and the Kalman filter,a state feedback control law is derived,accounting for the random parameter uncertainties.Finally,simulation and hardware-in-the-loop(HIL)experimental results demonstrate that the PCE-H_(2) robust controller not only provides better performance in terms of vehicle ride comfort compared to general H_(2) robust controller but also exhibits higher robustness to the effects of random uncertain parameters,resulting in more stable control performance.展开更多
This paper highlights the utilization of parallel control and adaptive dynamic programming(ADP) for event-triggered robust parallel optimal consensus control(ETRPOC) of uncertain nonlinear continuous-time multiagent s...This paper highlights the utilization of parallel control and adaptive dynamic programming(ADP) for event-triggered robust parallel optimal consensus control(ETRPOC) of uncertain nonlinear continuous-time multiagent systems(MASs).First, the parallel control system, which consists of a virtual control variable and a specific auxiliary variable obtained from the coupled Hamiltonian, allows general systems to be transformed into affine systems. Of interest is the fact that the parallel control technique's introduction provides an unprecedented perspective on eliminating the negative effects of disturbance. Then, an eventtriggered mechanism is adopted to save communication resources while ensuring the system's stability. The coupled HamiltonJacobi(HJ) equation's solution is approximated using a critic neural network(NN), whose weights are updated in response to events. Furthermore, theoretical analysis reveals that the weight estimation error is uniformly ultimately bounded(UUB). Finally,numerical simulations demonstrate the effectiveness of the developed ETRPOC method.展开更多
Hollow fiber membrane contactor(HFMC)units are one of the most promising technologies for improving conventional absorption processes.Traditionally,the optimization and control of this process is based on simplified m...Hollow fiber membrane contactor(HFMC)units are one of the most promising technologies for improving conventional absorption processes.Traditionally,the optimization and control of this process is based on simplified mathematical models or linearized control proposals that may present limitations.This work introduces a robust control based on modeling error compensation(MEC)applied to CO_(2)and H_(2)S absorption in a HFMC for natural gas sweetening.The HFMC model considers the concentration distribution in radial and axial coordinates.A classical PI controller and a sliding model controller(SMC)are applied for comparison purposes.Simulation results show that the proposed control MEC is suitable for regulating the sour gas concentration to values that reduce their presence at the HFMC from 0.85%to 0.45%(mol)of CO_(2)and from 4 to 1.2μl·L^(-1)of H_(2)S,independent of external disturbances and setpoint changes.Likewise,MEC's ability to compensate for modeling uncertainties through a simple and easily implemented design provides robust performance that satisfies international standards in natural gas quality,showing a 40%better performance according to the integral of squared error compared with the SMC controller.展开更多
基金the University of Tehran for providing support with this study.
文摘Nonlinearity in parallel compliance can be exploited to improve the performance of locomotion systems in terms of(1)energy efficiency,(2)control robustness,and(3)gait optimality;that is,attaining energy efficiency across a set of motions.Thus far,the literature has investigated and validated only the first two benefits.In this study,we present a new mathematical framework for designing nonlinear compliances in cyclic tasks encompassing all three benefits.We present an optimization-based formulation for each benefit to obtain the desired compliance profile.Furthermore,we analytically prove that,compared to linear compliance,using nonlinear compliance leads to(1)lower energy consumption,(2)better closed-loop performance,specifically in terms of tracking error,and(3)a higher diversity of natural frequencies.To compare the performance of linear and nonlinear compliance,we apply the proposed methods to a diverse set of robotic systems performing cyclic tasks,including a 2-DOF manipulator,a 3-DOF bipedal walker,and a hopper model.Compared to linear compliance,the nonlinear compliance leads to better performance in all aspects;for example,a 70%reduction in energy consumption and tracking error for the manipulator simulation.Regarding gait optimality,for all robotic simulation models,compared to linear compliance,the nonlinear compliance has lower energy consumption and tracking error over the considered set of motions.The proposed analytical studies and simulation results strongly support the idea that using nonlinear compliance significantly improves robotic system performance in terms of energy efficiency,control robustness,and gait optimality.
文摘Numerous uncertainties in practical production and operation can seriously affect the drive performance of permanent magnet synchronous machines(PMSMs).Various robust control methods have been developed to mitigate or eliminate the effects of these uncertainties.However,the robustness to uncertainties of electrical drive systems has not been clearly defined.No systemic procedures have been proposed to evaluate a control system's robustness(how robust it is).This paper proposes a systemic method for evaluating control systems'robustness to uncertainties.The concept and fundamental theory of robust control are illustrated by considering a simple uncertain feedback control system.The effects of uncertainties on the control performance and stability are analyzed and discussed.The concept of design for six-sigma(a robust design method)is employed to numerically evaluate the robustness levels of control systems.To show the effectiveness of the proposed robustness evaluation method,case studies are conducted for second-order systems,DC motor drive systems,and PMSM drive systems.Besides the conventional predictive control of PMSM drive,three different robust predictive control methods are evaluated in terms of two different parametric uncertainty ranges and three application requirements against parametric uncertainties.
基金Supported by the Fundamental Research Funds for the Central Universities(2024ZYGXZR047)the National Natural Science Foundation of China(62373156)the Guangdong Basic and Applied Basic Research Foundation(2024A1515011736)。
文摘This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters.
基金partially supported by the Italian Ministry for Research in the framework of the 2020 Program for Research Projects of National Interest(2020RTWES4)。
文摘The Nelder-Mead simplex method is a well-known algorithm enabling the minimization of functions that are not available in closed-form and that need not be differentiable or convex.Furthermore,it is particularly parsimonious on the number of function evaluations,thus making it preferable to convex optimization paradigms in the case,common when dealing with control design problems,that the objective function of the optimization problem is non-differentiable,non-convex,and its closed-form is not available or difficult to be computed analytically.The main goal of this paper is to show how the joint use of the Nelder-Mead simplex method and the Morrison algorithm can be successfully used to solve relevant and challenging control problems that cannot be easily solved using analytic methods.In particular,it is shown how the problems of strong stabilization,static output feedback stabilization,and design of robust controllers having fixed structure can be framed as optimization problems,which,in turn,can be efficiently solved by coupling the two above mentioned algorithms.The performance of this procedure is compared with state-of-the-art techniques on dozens of static output feedback benchmark case studies,and its effectiveness is demonstrated by several examples.
文摘The increasing demand for artillery firepower,coupled with the growing size of gun barrels,imposes significant challenges on servo system performance.To address these challenges while ensuring fast and stable response,this paper proposes an adaptive robust controller based on an asymmetric barrier Lyapunov function(ABLF).The controller design incorporates both load and driver states through a backstepping synthesis.The overshoot and lag of barrel position errors are constrained within asymmetric boundaries,accounting for complex rotational uncertainties via an adaptive law and linear extended state observers(LESO).Simulations and experiments under typical artillery operating conditions validate the effectiveness and dynamic tracking performance of the proposed control strategy in comparison with other methods.
基金supported in part by the National Natural Science Foundation of China(No.52177109)Key R&D Program of Hubei Province,China(No.2020BAB109).
文摘With the prevalence of renewable distributed energy resources(DERs)such as photovoltaics(PVs),modern active distribution networks(ADNs)suffer from voltage deviation and power quality issues.However,traditional voltage control methods often face a trade-off between efficiency and effectiveness,and rarely ensure robust voltage safety under typical state perturbations in practical distribution grids.In this paper,a robust model-free voltage regulation approach is proposed which simultaneously takes security and robustness into account.In this context,the voltage control problem is formulated as a constrained Markov decision process(CMDP).A safety-augmented multiagent deep deterministic policy gradient(MADDPG)algorithm is the trained to enable real-time collaborative optimization of ADNs,aiming to maintain nodal voltages within safe operational limits while minimizing total line losses.Moreover,a robust regulation loss is introduced to ensure reliable performance under various state perturbations in practical voltage controls.The proposed regulation algorithm effectively balance efficiency,safety,and robustness,and also demonstrates potential for generalizing these characteristics to other applications.Numerical studies vali-date the robustness of the proposed method under varying state perturbations on the IEEE test cases and the optimal integrated control performance when compared to other benchmarks.
基金Deanship of Research and Graduate Studies at King Khalid University for funding this work through the Large Research Project(Grant No.RGP2/587/46).
文摘Photovoltaic(PV)systems in the field operate under complex,uncertain conditions rapid irradiance ramps,partial shading,temperature swings,surface soiling,and weak-grid disturbances including off-nominal frequency and voltage distortion that degrade energy yield and power quality.We propose a drift-aware,power-quality-constrained MPPT framework that co-optimizes MPPT,PLL,and current-loop gains under stochastic frequency drift,while enforcing IEEE-519 limits(per-order Ih/IL and TDD)during optimization.Unlike energy-only or THD-only methods,the design target integrates PQ constraints into the objective and is validated across calibrated drift scenarios with explicit per-order and TDD reporting.Operating scenarios are calibrated to Cameroon’s Southern Interconnected Grid and city-specific profiles(Douala/Yaoundé),combining measured-style irradiance/temperature traces,partial-shading patterns,and stochastic frequency drift up to±0.8 Hz with synthetic contingencies.Across a 30-scenario campaign,the proposed controller achievesηMPPT=99.3%–99.6%(vs.98.6%Incremental Conductance and 97.8%Perturb-and-Observe),lowers DC-link ripple by 35%–48%,reduces oscillatory PCC power by≈41%,maintains THD≤2.5%(5%limit)and PF≥0.99,and shortens irradiance-step settling from 85–110 ms to 50–65 ms.Sensitivity to PLL bandwidth shows a broad optimum(≈60–90 Hz)with minimum THD/ripple,and ablations confirm that explicit drift weighting is pivotal to ripple and THD suppression without sacrificing yield.The approach is controller-agnostic,firmware-deployable,and generalizes to other converter-interfaced renewables;we outline a short hardware-/HIL-validation path for adoption in Sub-Saharan grids.
文摘In this paper, we present a quantitative analysis of the robustness of a generalized predictive controller. The result of stability analysis shows that, under a specific bounded modelling error, the closed-loop system is BIBO stable in the presence of unmodelled dynamics.
文摘A robustness-tracking control scheme based on combining H_∞ robust control and sliding mode control is proposed for a direct drive AC permanent-magnet linear motor servo system to solve the conflict between tracking and robustness of the linear servo system. The sliding mode tracking controller is designed to ensure the system has a fast tracking characteristic to the command, and the H_∞ robustness controller suppresses the disturbances well within the close loop(including the load and the end effect force of linear motor etc.) and effectively minimizes the chattering of sliding mode control which influences the steady state performance of the system. Simulation results show that this control scheme enhances the track-command-ability and the robustness of the linear servo system, and in addition, it has a strong robustness to parameter variations and resistance disturbances.
基金Supported by National Natural Science Foundation of China(Grant Nos.52025121,52394263)National Key R&D Plan of China(Grant No.2023YFD2000301)+2 种基金Foundation of State Key Laboratory of Automobile Safety and Energy Saving of China(Grant No.KFZ2201)the Jiangsu Provincial Scientific Research Center of Applied Mathematics under(Grant No.BK20233002)Special Fund of Jiangsu Province for the Transformation of Scientific and Technological Achievements under(Grant No.BA2021023)。
文摘This paper tackles uncertainties between planning and actual models.It extends the concept of RCI(robust control invariant)tubes,originally a parameterized representation of closed-loop control robustness in traditional feedback control,to the domain of motion planning for autonomous vehicles.Thus,closed-loop system uncertainty can be preemptively addressed during vehicle motion planning.This involves selecting collision-free trajectories to minimize the volume of robust invariant tubes.Furthermore,constraints on state and control variables are translated into constraints on the RCI tubes of the closed-loop system,ensuring that motion planning produces a safe and optimal trajectory while maintaining flexibility,rather than solely optimizing for the open-loop nominal model.Additionally,to expedite the solving process,we were inspired by L2gain to parameterize the RCI tubes and developed a parameterized explicit iterative expression for propagating ellipsoidal uncertainty sets within closedloop systems.Furthermore,we applied the pseudospectral orthogonal collocation method to parameterize the optimization problem of transcribing trajectories using high-order Lagrangian polynomials.Finally,under various operating conditions,we incorporate both the kinematic and dynamic models of the vehicle and also conduct simulations and analyses of uncertainties such as heading angle measurement,chassis response,and steering hysteresis.Our proposed robust motion planning framework has been validated to effectively address nearly all bounded uncertainties while anticipating potential tracking errors in control during the planning phase.This ensures fast,closed-loop safety and robustness in vehicle motion planning.
文摘The electromagnetic levitation system(EMLS)serves as the most important part of any magnetic levitation system.However,its characteristics are defined by its highly nonlinear dynamics and instability.Furthermore,the uncertainties in the dynamics of an electromagnetic levitation system make the controller design more difficult.Therefore,it is necessary to design a robust control law that will ensure the system’s stability in the presence of these uncertainties.In this framework,the dynamics of an electromagnetic levitation system are addressed in terms of matched and unmatched uncertainties.The robust control problem is translated into the optimal control problem,where the uncertainties of the electromagnetic levitation system are directly reflected in the cost function.The optimal control method is used to solve the robust control problem.The solution to the optimal control problem for the electromagnetic levitation system is indeed a solution to the robust control problem of the electromagnetic levitation system under matched and unmatched uncertainties.The simulation and experimental results demonstrate the performance of the designed control scheme.The performance indices such as integral absolute error(IAE),integral square error(ISE),integral time absolute error(ITAE),and integral time square error(ITSE)are compared for both uncertainties to showcase the robustness of the designed control scheme.
基金supported in part by the National Key Research and Development Program of China(2023YFA1011803)the National Natural Science Foundation of China(62273064,61991400/61991403,61933012,62250710167,62203078)+2 种基金Natural Science Foundation of Chongqing(CSTB2023NSCQ-MSX0588)the Central University Project(2023CDJKYJH047)the Innovation Support Program for International Students Returning to China(cx2022016)
文摘This paper investigates the prescribed-time tracking control problem for a class of multi-input multi-output(MIMO)nonlinear strict-feedback systems subject to non-vanishing uncertainties. The inherent unmatched and non-vanishing uncertainties make the prescribed-time control problem become much more nontrivial. The solution to address the challenges mentioned above involves incorporating a prescribed-time filter, as opposed to a finite-time filter, and formulating a prescribed-time Lyapunov stability lemma(Lemma 5). The prescribed-time Lyapunov stability lemma is based on time axis shifting time-varying yet bounded gain, which establishes a novel link between the fixed-time and prescribed-time control method. This allows the restriction condition that the time-varying gain function must satisfy as imposed in most exist prescribed-time control works to be removed. Under the proposed control method, the desire trajectory is ensured to closely track the output of the system in prescribed time. The effectiveness of the theoretical results are verified through numerical simulation.
基金Supported by Qinghai University Youth Research Fund,China(Grant No.2023-QGY-15)。
文摘Due to errors in vehicle dynamics modeling,uncertainty in model parameters,and disturbances from curvature,the performance of the path tracking controller is poor or even unstable under high-speed and large-curvature conditions.Therefore,a path tracking robust control strategy based on force-driven H_(∞)and MPC is proposed.To fully exploit the nonlinear dynamics characteristics of tires,a force-driven state space model of a path tracking system based on a linear time-varying tire model is established;the H_(∞)and MPC methods are used to design a robust controller.Considering disturbance and system state constraints,the robust control constraint model based on LMI is established.Finally,the proposed controller is validated through joint simulations using CarSim and MATLAB.The results show that the maximum lateral deviation is reduced by 17.07%,and the maximum course angle deviation is reduced by 13.04%under large curvature disturbance conditions.The maximum lateral deviation is reduced by 27.85%,and the maximum course angle deviation is reduced by 31.17%under conditions of uncertain road adhesion coefficients.Based on the controller’s performance,the proposed controller effectively mitigates modeling errors,parameter uncertainties,and curvature disturbances.
基金Project supported by the National Natural Science Foundation of China (Grant No. 62103408)Beijing Nova Program (Grant No. 20240484516)the Fundamental Research Funds for the Central Universities (Grant No. KG16314701)。
文摘The paper develops a robust control approach for nonaffine nonlinear continuous systems with input constraints and unknown uncertainties. Firstly, this paper constructs an affine augmented system(AAS) within a pre-compensation technique for converting the original nonaffine dynamics into affine dynamics. Secondly, the paper derives a stability criterion linking the original nonaffine system and the auxiliary system, demonstrating that the obtained optimal policies from the auxiliary system can achieve the robust controller of the nonaffine system. Thirdly, an online adaptive dynamic programming(ADP) algorithm is designed for approximating the optimal solution of the Hamilton–Jacobi–Bellman(HJB) equation.Moreover, the gradient descent approach and projection approach are employed for updating the actor-critic neural network(NN) weights, with the algorithm's convergence being proven. Then, the uniformly ultimately bounded stability of state is guaranteed. Finally, in simulation, some examples are offered for validating the effectiveness of this presented approach.
基金supported by the National Natural Science Foundation of China(61803015).
文摘In order to enhance the dynamic control precision of inertial stabilization platform(ISP),a disturbance sliding mode observer(DSMO)is proposed in this paper suppressing disturbance torques inherent within the system.The control accuracy of ISP is fundamentally circumscribed by various disturbance torques in rotating shaft.Therefore,a dynamic model of ISP incorporating composite perturbations is established with regard to the stabilization of axis in the inertial reference frame.Subsequently,an online estimator for control loop uncertainties based on the sliding mode control algorithm is designed to estimate the aggregate disturbances of various parameters uncertainties and other unmodeled disturbances that cannot be accurately calibrated.Finally,the proposed DSMO is integrated into a classical proportional-integral-derivative(PID)control scheme,utilizing feedforward approach to compensate the composite disturbance in the control loop online.The effectiveness of the proposed disturbance observer is validated through simulation and hardware experimentation,demonstrating a significant improvement in the dynamic control performance and robustness of the classical PID controller extensively utilized in the field of engineering.
基金Sponsored by Strategic Priority Research Program on Space Science,Chinese Academy of Sciences(Grant No.XDA1502030505).
文摘An innovative design method is outlined in this paper for the pointing control mechanism of large space flexible antennas.This method focuses on enhancing the accuracy and stability that are crucial for large spacecraft applications,such as space solar power stations.Utilizing potential energy function analysis,the dynamics of the antenna are modeled,treating it as an equivalent n-joint robotic arm.This approach simulates the rigid-flexible coupling effect through joint angle manipulations.The proposed HJI(Hamilton-Jacobi-Inequality)sliding mode robust control integrates HJI principle,dissipative system theory,and sliding mode control,offering improved pointing accuracy and robustness.Simulation results underscore the superiority of HJI sliding mode robust control over traditional PD(proportional-derivative)control in initial response,precision,and control smoothness,albeit at the cost of higher control torque requirements.This research underscores the potential of HJI sliding mode robust control in facilitating precise pointing control for future large space structures,enabling efficient space missions and reliable energy transmission.
基金supported by National Natural Science Foundation of China(52375530,52075132)Natural Science Foundation of Heilongjiang Province(YQ2022E025)+2 种基金State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment(Guangdong University of Technology)(JMDZ202312)Fundamental Research Funds for the Central Universities(HIT.OCEF.2024034)Space Drive and Manipulation Mechanism Laboratory of BICE and National Key Laboratory of Space Intelligent Control(BICE-SDMM-2024-01).
文摘Lithography machines operate in scanning mode for the fabrication of large-scale integrated circuits(ICs),requiring high-precision synchronous motion between the reticle and wafer stages.Disturbances generated by each stage during high-acceleration movements are transmitted through the base frame,resulting in degradation of synchronization performance.To address this challenge,this paper proposes a tube-based model predictive control(tube-MPC)approach for synchronization in lithography machines.First,the proposed modeling method accurately characterizes the coupling disturbances and synchronization dynamics.Subsequently,a tube-MPC approach is developed to ensure that the states of the nominal system are constrained within the terminal constraint set.To reduce the complexity of online computations,an approach is employed to transform online optimization problems into offline problems by creating an online lookup table.This enables the determination of optimal control inputs via a simplified online optimization algorithm.The robustness and trajectory tracking performance of the proposed approach are verified through simulation experiments,demonstrating its effectiveness in enhancing the synchronization performance of multiple motion systems.
基金Supported by National Natural Science Foundation of China(Grant No.51875256)Open Platform Fund of Human Institute of Technology(Grant No.KFA22009).
文摘As a crucial component of intelligent chassis systems,air suspension significantly enhances driver comfort and vehicle stability.To further improve the adaptability of commercial vehicles to complex and variable road conditions,this paper proposes a linear motor active suspension with quasi-zero stiffness(QZS)air spring system.Firstly,a dynamic model of the linear motor active suspension with QZS air spring system is established.Secondly,considering the random uncertainties in the linear motor parameters due to manufacturing and environmental factors,a dynamic model and state equations incorporating these uncertainties are constructed using the polynomial chaos expansion(PCE)method.Then,based on H_(2) robust control theory and the Kalman filter,a state feedback control law is derived,accounting for the random parameter uncertainties.Finally,simulation and hardware-in-the-loop(HIL)experimental results demonstrate that the PCE-H_(2) robust controller not only provides better performance in terms of vehicle ride comfort compared to general H_(2) robust controller but also exhibits higher robustness to the effects of random uncertain parameters,resulting in more stable control performance.
基金supported in part by the National Key Research and Development Program of China(2021YFE0206100)the National Natural Science Foundation of China(62425310,62073321)+2 种基金the National Defense Basic Scientific Research Program(JCKY2019203C029,JCKY2020130C025)the Science and Technology Development FundMacao SAR(FDCT-22-009-MISE,0060/2021/A2,0015/2020/AMJ)
文摘This paper highlights the utilization of parallel control and adaptive dynamic programming(ADP) for event-triggered robust parallel optimal consensus control(ETRPOC) of uncertain nonlinear continuous-time multiagent systems(MASs).First, the parallel control system, which consists of a virtual control variable and a specific auxiliary variable obtained from the coupled Hamiltonian, allows general systems to be transformed into affine systems. Of interest is the fact that the parallel control technique's introduction provides an unprecedented perspective on eliminating the negative effects of disturbance. Then, an eventtriggered mechanism is adopted to save communication resources while ensuring the system's stability. The coupled HamiltonJacobi(HJ) equation's solution is approximated using a critic neural network(NN), whose weights are updated in response to events. Furthermore, theoretical analysis reveals that the weight estimation error is uniformly ultimately bounded(UUB). Finally,numerical simulations demonstrate the effectiveness of the developed ETRPOC method.
文摘Hollow fiber membrane contactor(HFMC)units are one of the most promising technologies for improving conventional absorption processes.Traditionally,the optimization and control of this process is based on simplified mathematical models or linearized control proposals that may present limitations.This work introduces a robust control based on modeling error compensation(MEC)applied to CO_(2)and H_(2)S absorption in a HFMC for natural gas sweetening.The HFMC model considers the concentration distribution in radial and axial coordinates.A classical PI controller and a sliding model controller(SMC)are applied for comparison purposes.Simulation results show that the proposed control MEC is suitable for regulating the sour gas concentration to values that reduce their presence at the HFMC from 0.85%to 0.45%(mol)of CO_(2)and from 4 to 1.2μl·L^(-1)of H_(2)S,independent of external disturbances and setpoint changes.Likewise,MEC's ability to compensate for modeling uncertainties through a simple and easily implemented design provides robust performance that satisfies international standards in natural gas quality,showing a 40%better performance according to the integral of squared error compared with the SMC controller.
