1 Active Disturbance Rejection Control(ADRC):a brief survey Since its inception,Active Disturbance Rejection Control(ADRC)has re-centered feedback controller design around two fundamental ideas—along with a consequen...1 Active Disturbance Rejection Control(ADRC):a brief survey Since its inception,Active Disturbance Rejection Control(ADRC)has re-centered feedback controller design around two fundamental ideas—along with a consequential design simplification:real-time estimation and online cancellation of the“total disturbance”conceived as the lumped effect of unknown internal dynamics and external inputs.The simplified design then proceeds in a customary fashion for the ideally remaining system model,which is devoid of the total disturbance.展开更多
In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial...In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial vehicles (UAVs). A leader–follower structure is adopted, wherein the leader moves with reference dynamics (a target). Different from the existing approaches that necessitate full knowledge of the time-varying reference trajectory, in this paper, it is assumed that only some vehicles (at least one) have access to the bearing relative to the target, and all other vehicles are equipped with sensors capable of measuring the bearings relative to neighboring vehicles. In this paper, a consensus estimator is proposed to estimate the global position for each vehicle using relative bearing measurements and an estimate of neighboring vehicles received from a direct communication network. Then, a continuous robust integral of the sign of the error (RISE) control approach is effectively integrated with the distributed vector field approach to ensure UAV formation orbiting around the moving target while avoiding obstacles and maintaining network links within available communication ranges. In contrast to the classical RISE control rule, a \(\tanh (\cdot )\) function is used instead of the \(\text {sgn}(\cdot )\) function to further decrease the high-gain feedback and to obtain a smoother control signal. Furthermore, by using the localized radial basis function (RBF) neural networks (NNs) in a cooperative way, deterministic learning theory is employed to accurately identify/learn model uncertainties resulting from the attitude dynamics. The convergence of the entire closed-loop system is illustrated using the Lyapunov theory and is shown to be uniformly ultimately bounded. Finally, numerical simulations show the effectiveness of the proposed approach.展开更多
Mason Reset(MR),a groundbreaking invention by Clesson E.Mason in 1930 that later became a part of“the universal approach to process control instrumentation”,is revisited in this paper and is shown to consists of thr...Mason Reset(MR),a groundbreaking invention by Clesson E.Mason in 1930 that later became a part of“the universal approach to process control instrumentation”,is revisited in this paper and is shown to consists of three actions:fast(errorcorrection),medium(negative feedback for expanded proportional band)and slow(reset for zero steady-state error).The focus of the paper is on the reset action,generated from a positive feedback loop,and its underlying principles with profound implications to our understanding and practice of automatic control,both basic and advanced.For example,we note that reset control and integral control,contrary to common belief,differ fundamentally in design principle and in practicality.Such difference comes to a head in the event of integrator windup:while reset windup is a problem of actuator saturation,the integrator windup is a runaway situation due to controller instability.In fact,there is no advantage gained in replacing MR with an integrator.In other words,one should not integrate the error directly as in standard PID,since doing so makes the closed-loop system internally unstable.With MR-based control formulated in this paper,there is no such threat of instability and,therefore,no need for any anti-windup mechanisms.Furthermore,the integral control is made scalable in this framework as a tradeoff between the steady-state accuracy and the controller stability.This leads to a novel MR-based control design,scalable in gain and in time to accommodate various process characteristics and design specifications.Simple in construction and transparent in principle,this MR-based control,as a basic framework of design,is readily deployable in scale.展开更多
This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems posses...This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems possess two important characteristics: (i) The uncertain nonlinear terms meet the linearly unmeasurable-states dependent growth with the growth rate being an unknown function of the input and output. (ii) There exist input matching uncertainty and unknown measurement sensitivity. By introducing a single dynamic gain and employing a cleverly devised event-triggering mechanism (ETM), we design a new gain-based event-triggered output-feedback controller, which globally regulates all states of the considered systems and maintains global boundedness of the closed-loop system. Furthermore, the estimation of input matching uncertainty achieves convergence towards its actual value, and Zeno behavior does not happen. Two simulation examples including a practical one show that the proposed approach is effective.展开更多
An aileron is a crucial control surface for rolling.Any jitter or shaking caused by the aileron mechatronics could have catastrophic consequences for the aircraft’s stability,maneuverability,safety,and lifespan.This ...An aileron is a crucial control surface for rolling.Any jitter or shaking caused by the aileron mechatronics could have catastrophic consequences for the aircraft’s stability,maneuverability,safety,and lifespan.This paper presents a robust solution in the form of a fast flutter suppression digital control logic of edge computing aileron mechatronics(ECAM).We have effectively eliminated passive and active oscillating response biases by integrating nonlinear functional parameters and an antiphase hysteresis Schmitt trigger.Our findings demonstrate that self-tuning nonlinear parameters can optimize stability,robustness,and accuracy.At the same time,the antiphase hysteresis Schmitt trigger effectively rejects flutters without the need for collaborative navigation and guidance.Our hardware-in-the-loop simulation results confirm that this approach can eliminate aircraft jitter and shaking while ensuring expected stability and maneuverability.In conclusion,this nonlinear aileron mechatronics with a Schmitt positive feedback mechanism is a highly effective solution for distributed flight control and active flutter rejection.展开更多
The objective of this paper is to present a robust safety-critical control system based on the active disturbance rejection control approach, designed to guarantee safety even in the presence of model inaccuracies, un...The objective of this paper is to present a robust safety-critical control system based on the active disturbance rejection control approach, designed to guarantee safety even in the presence of model inaccuracies, unknown dynamics, and external disturbances. The proposed method combines control barrier functions and control Lyapunov functions with a nonlinear extended state observer to produce a robust and safe control strategy for dynamic systems subject to uncertainties and disturbances. This control strategy employs an optimization-based control, supported by the disturbance estimation from a nonlinear extended state observer. Using a quadratic programming algorithm, the controller computes an optimal, stable, and safe control action at each sampling instant. The effectiveness of the proposed approach is demonstrated through numerical simulations of a safety-critical interconnected adaptive cruise control system.展开更多
In recent years,there has been a growing demand for more efficient and robust control strategies in cooperative multi-robot systems.This paper introduces the cascade explicit tube model predictive controller(CET-MPC),...In recent years,there has been a growing demand for more efficient and robust control strategies in cooperative multi-robot systems.This paper introduces the cascade explicit tube model predictive controller(CET-MPC),a control architecture designed specifically for distributed aerial robot systems.By integrating an explicit model predictive controller(MPC)with a tube MPC,our approach significantly reduces online computational demands while enhancing robustness against disturbances such as wind and measurement noise,as well as uncertainties in inertia parameters.Further,we incorporate a cascade controller to minimize steady-state errors and improve system performance dynamically.The results of this assessment provide valuable insights into the effectiveness and reliability of the CET-MPC approach under realistic operating conditions.The simulation results of flight scenarios for multi-agent quadrotors demonstrate the controller’s stability and accurate tracking of the desired path.By addressing the complexities of quadrotors’six degrees of freedom,this controller serves as a versatile solution applicable to a wide range of multi-robot systems with varying degrees of freedom,demonstrating its adaptability and scalability beyond the quadrotor domain.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
In this paper,a new study concerning the usage of artificial neural networks in the control application is given.It is shown,that the data gathered during proper operation of a given control plant can be used in the l...In this paper,a new study concerning the usage of artificial neural networks in the control application is given.It is shown,that the data gathered during proper operation of a given control plant can be used in the learning process to fully embrace the control pattern.Interestingly,the instances driven by neural networks have the ability to outperform the original analytically driven scenarios.Three different control schemes,namely perfect,linear-quadratic,and generalized predictive controllers were used in the theoretical study.In addition,the nonlinear recurrent neural network-based generalized predictive controller with the radial basis function-originated predictor was obtained to exemplify the main results of the paper regarding the real-world application.展开更多
This article presents an adaptive optimal control method for a semi-active suspension system.The model of the suspension system is built,in which the components of uncertain parameters and exogenous disturbance are de...This article presents an adaptive optimal control method for a semi-active suspension system.The model of the suspension system is built,in which the components of uncertain parameters and exogenous disturbance are described.The adaptive optimal control law consists of the sum of the optimal control component and the adaptive control component.First,the optimal control law is designed for the model of the suspension system after ignoring the components of uncertain parameters and exogenous disturbance caused by the road surface.The optimal control law expresses the desired dynamic characteristics of the suspension system.Next,the adaptive component is designed with the purpose of compensating for the effects caused by uncertain parameters and exogenous disturbance caused by the road surface;the adaptive component has adaptive parameter rules to estimate uncertain parameters and exogenous disturbance.When exogenous disturbances are eliminated,the system responds with an optimal controller designed.By separating theoretically the dynamic of a semi-active suspension system,this solution allows the design of two separate controllers easily and has reduced the computational burden and the use of too many tools,thus allowing for more convenient hardware implementation.The simulation results also show the effectiveness of damping oscillations of the proposed solution in this article.展开更多
Siamese tracking algorithms usually take convolutional neural networks(CNNs)as feature extractors owing to their capability of extracting deep discriminative features.However,the convolution kernels in CNNs have limit...Siamese tracking algorithms usually take convolutional neural networks(CNNs)as feature extractors owing to their capability of extracting deep discriminative features.However,the convolution kernels in CNNs have limited receptive fields,making it difficult to capture global feature dependencies which is important for object detection,especially when the target undergoes large-scale variations or movement.In view of this,we develop a novel network called effective convolution mixed Transformer Siamese network(SiamCMT)for visual tracking,which integrates CNN-based and Transformer-based architectures to capture both local information and long-range dependencies.Specifically,we design a Transformer-based module named lightweight multi-head attention(LWMHA)which can be flexibly embedded into stage-wise CNNs and improve the network’s representation ability.Additionally,we introduce a stage-wise feature aggregation mechanism which integrates features learned from multiple stages.By leveraging both location and semantic information,this mechanism helps the SiamCMT to better locate and find the target.Moreover,to distinguish the contribution of different channels,a channel-wise attention mechanism is introduced to enhance the important channels and suppress the others.Extensive experiments on seven challenging benchmarks,i.e.,OTB2015,UAV123,GOT10K,LaSOT,DTB70,UAVTrack112_L,and VOT2018,demonstrate the effectiveness of the proposed algorithm.Specially,the proposed method outperforms the baseline by 3.5%and 3.1%in terms of precision and success rates with a real-time speed of 59.77 FPS on UAV123.展开更多
In this article,the dynamical model and trajectory tracking problem for a tilt-rotor unmanned aerial vehicle is tackled through linear Active Disturbance Rejection Control(ADRC)applied on the tangent linearized system...In this article,the dynamical model and trajectory tracking problem for a tilt-rotor unmanned aerial vehicle is tackled through linear Active Disturbance Rejection Control(ADRC)applied on the tangent linearized system.To apply the ADRC scheme,it is considered the subsystem without the Y-axis component,which is differentially flat and whose flat outputs are obtained using the Kronecker matrix.Numerical assessment using as system parameters the ones of a scale prototype is provided to show the effectiveness of the proposal leading to accurate tracking results using admissible control values for an experimental scenario.展开更多
This article investigates the anti-disturbance and stabilization problems for the nonlinear uncertain permanent magnet synchronous motor(PMSM)with stator voltage saturation and unknown load.A smooth switching mechanis...This article investigates the anti-disturbance and stabilization problems for the nonlinear uncertain permanent magnet synchronous motor(PMSM)with stator voltage saturation and unknown load.A smooth switching mechanism is presented to structure the adaptive integral terminal sliding mode control(SMC)strategy.The control design consists of compensation control and nominal control,which improves the rapidity and accuracy of trajectory tracking.The smooth saturation model based on the error function is applied to approximate the voltage saturation phenomenon.Additionally,to deal with the adverse effects of various unknown disturbances,including model parameter uncertainties and unknown external load disturbances,an improved disturbance observer(DO)is proposed.This observer effectively suppresses the fluctuations caused by fixed gain during the starting period of the system.Finally,the experimental results under different conditions show that the proposed strategy has good tracking and disturbance suppression performances.展开更多
This paper presents a robust finite-time visual servo control strategy for the tracking problem of omni-directional mobile manipulators(OMMs)subject to mismatched disturbances.First,the nonlinear kinematic model of vi...This paper presents a robust finite-time visual servo control strategy for the tracking problem of omni-directional mobile manipulators(OMMs)subject to mismatched disturbances.First,the nonlinear kinematic model of visual servoing for OMMs with mismatched disturbances is explicitly presented to solve the whole-body inverse kinematic problem.Second,a sliding mode observer augmented with an integral terminal sliding mode controller is proposed to handle these uncertainties and ensure that the system converges to a small region around the equilibrium point.The boundary layer technique is employed to mitigate the chattering phenomenon.Furthermore,a strict finite-time Lyapunov stability analysis is conducted.An experimental comparison between the proposed algorithm and a traditional position-based visual servo controller is carried out,and the results demonstrate the superiority of the proposed control algorithm.展开更多
This paper aims to fuse two well-established and,at the same time,opposed control techniques,namely,model predictive control(MPC)and active disturbance rejection control(ADRC),to develop a dynamic motion controller fo...This paper aims to fuse two well-established and,at the same time,opposed control techniques,namely,model predictive control(MPC)and active disturbance rejection control(ADRC),to develop a dynamic motion controller for a laser beam steering system.The proposed technique uses the ADRC philosophy to lump disturbances and model uncertainties into a total disturbance.Then,the total disturbance is estimated via a discrete extended state disturbance observer(ESO),and it is used to(1)handle the system constraints in a quadratic optimization problem and(2)injected as a feedforward term to the plant to reject the total disturbance,together with the feedback term obtained by the MPC.The main advantage of the proposed approach is that the MPC is designed based on a straightforward integrator-chain model such that a simple convex optimization problem is performed.Several experiments show the real-time closed-loop performance regarding trajectory tracking and disturbance rejection.Owing to simplicity,the self-contained approach MPC+ESO becomes a Frugal MPC,which is computationally economical,adaptable,efficient,resilient,and suitable for applications where on-board computational resources are limited.展开更多
This paper deals with reduction of losses in electric power distribution system through a dynamic reconfiguration case study of a grid in the city of Mostar,Bosnia and Herzegovina.The proposed solution is based on a n...This paper deals with reduction of losses in electric power distribution system through a dynamic reconfiguration case study of a grid in the city of Mostar,Bosnia and Herzegovina.The proposed solution is based on a nonlinear model predictive control algorithm which determines the optimal switching operations of the distribution system.The goal of the control algorithm is to find the optimal radial network topology which minimizes cumulative active power losses and maximizes voltages across the network while simultaneously satisfying all system constraints.The optimization results are validated through multiple simulations(using real power demand data collected for a few characteristic days during winter and summer)which demonstrate the efficiency and usefulness of the developed control algorithm in reducing the grid losses by up to 14%.展开更多
With the increasing penetration of renewable energy resources in power systems,conventional timescale separated load frequency control(LFC)and economic dispatch may degrade frequency performance and reduce economic ef...With the increasing penetration of renewable energy resources in power systems,conventional timescale separated load frequency control(LFC)and economic dispatch may degrade frequency performance and reduce economic efficiency.This paper proposes a novel data-driven adaptive distributed optimal disturbance rejection control(DODRC)method for real-time economic LFC problem in nonlinear power systems.Firstly,a basic DODRC method is proposed by integrating the active disturbance rejection control method and the partial primal–dual algorithm.Then,to deal with the tie-line power flow constraints,the logarithmic barrier function is employed to reconstruct the Lagrange function to obtain the constrained DODRC method.By analyzing the sensitivity of the uncertain parameters of power systems,a data-driven adaptive DODRC method is finally proposed with a neural network.The effectiveness of the proposed method is demonstrated by experimental results using real-time equipment.展开更多
The work proposes a distributed Kalman filtering(KF)algorithm to track a time-varying unknown signal process for a stochastic regression model over network systems in a cooperative way.We provide the stability analysi...The work proposes a distributed Kalman filtering(KF)algorithm to track a time-varying unknown signal process for a stochastic regression model over network systems in a cooperative way.We provide the stability analysis of the proposed distributed KF algorithm without independent and stationary signal assumptions,which implies that the theoretical results are able to be applied to stochastic feedback systems.Note that the main difficulty of stability analysis lies in analyzing the properties of the product of non-independent and non-stationary random matrices involved in the error equation.We employ analysis techniques such as stochastic Lyapunov function,stability theory of stochastic systems,and algebraic graph theory to deal with the above issue.The stochastic spatio-temporal cooperative information condition shows the cooperative property of multiple sensors that even though any local sensor cannot track the time-varying unknown signal,the distributed KF algorithm can be utilized to finish the filtering task in a cooperative way.At last,we illustrate the property of the proposed distributed KF algorithm by a simulation example.展开更多
To address the issue of disturbance compensation deviation in linear active disturbance rejection control(LADRC),a linear active disturbance rejection control method with reference to the integral chain model(LADRC-R)...To address the issue of disturbance compensation deviation in linear active disturbance rejection control(LADRC),a linear active disturbance rejection control method with reference to the integral chain model(LADRC-R)is proposed.By constructing an ideal control reference model,a dynamic correlation between output deviation and uncompensated disturbances is established,and a dual-loop compensation mechanism is designed.Based on theoretical analysis and frequency-domain characteristics of typical first/second-order systems,this method maintains the parameter-tuning advantages of LADRC while reducing disturbance effects by 50%and introducing no phase lag during low-frequency disturbance suppression.Simulations on second-order systems verify its robustness under parameter perturbations,gain mismatch,and complex disturbances,and an optimized design scheme for the deviation compensator is proposed to suppress discontinuous measurement noise interference.Finally,the engineering effectiveness of this method in precision motion control is validated on an electromagnetic suspension platform,providing a new approach to improving the control performance of LADRC in environments with uncertain disturbances.展开更多
With the growing adoption of artificial intelligence algorithms and neural networks,online learning and adaptive methods for updating the bandwidth have become increasingly prevalent.However,the conditions required to...With the growing adoption of artificial intelligence algorithms and neural networks,online learning and adaptive methods for updating the bandwidth have become increasingly prevalent.However,the conditions required to ensure closed-loop stability when employing a time-varying bandwidth,as well as the supporting mathematical foundations,remain insufficiently studied.This paper investigates the stability condition for active disturbance rejection control(ADRC)with a time-varying bandwidth extended state observer(ESO).A new stability condition is derived,which means that the upper bound of rate of change for ESO bandwidth should be restricted.Moreover,under the proposed condition,the closed-loop stability of ADRC with a time-varying bandwidth observer is rigorously proved for nonlinear uncertainties.In simulations,the necessity of the proposed condition is illustrated,demonstrating that the rate of change of ESO bandwidth is crucial for closed-loop stability.展开更多
文摘1 Active Disturbance Rejection Control(ADRC):a brief survey Since its inception,Active Disturbance Rejection Control(ADRC)has re-centered feedback controller design around two fundamental ideas—along with a consequential design simplification:real-time estimation and online cancellation of the“total disturbance”conceived as the lumped effect of unknown internal dynamics and external inputs.The simplified design then proceeds in a customary fashion for the ideally remaining system model,which is devoid of the total disturbance.
文摘In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial vehicles (UAVs). A leader–follower structure is adopted, wherein the leader moves with reference dynamics (a target). Different from the existing approaches that necessitate full knowledge of the time-varying reference trajectory, in this paper, it is assumed that only some vehicles (at least one) have access to the bearing relative to the target, and all other vehicles are equipped with sensors capable of measuring the bearings relative to neighboring vehicles. In this paper, a consensus estimator is proposed to estimate the global position for each vehicle using relative bearing measurements and an estimate of neighboring vehicles received from a direct communication network. Then, a continuous robust integral of the sign of the error (RISE) control approach is effectively integrated with the distributed vector field approach to ensure UAV formation orbiting around the moving target while avoiding obstacles and maintaining network links within available communication ranges. In contrast to the classical RISE control rule, a \(\tanh (\cdot )\) function is used instead of the \(\text {sgn}(\cdot )\) function to further decrease the high-gain feedback and to obtain a smoother control signal. Furthermore, by using the localized radial basis function (RBF) neural networks (NNs) in a cooperative way, deterministic learning theory is employed to accurately identify/learn model uncertainties resulting from the attitude dynamics. The convergence of the entire closed-loop system is illustrated using the Lyapunov theory and is shown to be uniformly ultimately bounded. Finally, numerical simulations show the effectiveness of the proposed approach.
文摘Mason Reset(MR),a groundbreaking invention by Clesson E.Mason in 1930 that later became a part of“the universal approach to process control instrumentation”,is revisited in this paper and is shown to consists of three actions:fast(errorcorrection),medium(negative feedback for expanded proportional band)and slow(reset for zero steady-state error).The focus of the paper is on the reset action,generated from a positive feedback loop,and its underlying principles with profound implications to our understanding and practice of automatic control,both basic and advanced.For example,we note that reset control and integral control,contrary to common belief,differ fundamentally in design principle and in practicality.Such difference comes to a head in the event of integrator windup:while reset windup is a problem of actuator saturation,the integrator windup is a runaway situation due to controller instability.In fact,there is no advantage gained in replacing MR with an integrator.In other words,one should not integrate the error directly as in standard PID,since doing so makes the closed-loop system internally unstable.With MR-based control formulated in this paper,there is no such threat of instability and,therefore,no need for any anti-windup mechanisms.Furthermore,the integral control is made scalable in this framework as a tradeoff between the steady-state accuracy and the controller stability.This leads to a novel MR-based control design,scalable in gain and in time to accommodate various process characteristics and design specifications.Simple in construction and transparent in principle,this MR-based control,as a basic framework of design,is readily deployable in scale.
基金supported by the fund of Beijing Municipal Commission of Education(KM202210017001 and 22019821001)the Natural Science Foundation of Henan Province(222300420253).
文摘This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems possess two important characteristics: (i) The uncertain nonlinear terms meet the linearly unmeasurable-states dependent growth with the growth rate being an unknown function of the input and output. (ii) There exist input matching uncertainty and unknown measurement sensitivity. By introducing a single dynamic gain and employing a cleverly devised event-triggering mechanism (ETM), we design a new gain-based event-triggered output-feedback controller, which globally regulates all states of the considered systems and maintains global boundedness of the closed-loop system. Furthermore, the estimation of input matching uncertainty achieves convergence towards its actual value, and Zeno behavior does not happen. Two simulation examples including a practical one show that the proposed approach is effective.
基金supported in part by the Aeronautical Science Foundation of China under Grant 2022Z005057001the Joint Research Fund of Shanghai Commercial Aircraft System Engineering Science and Technology Innovation Center under CASEF-2023-M19.
文摘An aileron is a crucial control surface for rolling.Any jitter or shaking caused by the aileron mechatronics could have catastrophic consequences for the aircraft’s stability,maneuverability,safety,and lifespan.This paper presents a robust solution in the form of a fast flutter suppression digital control logic of edge computing aileron mechatronics(ECAM).We have effectively eliminated passive and active oscillating response biases by integrating nonlinear functional parameters and an antiphase hysteresis Schmitt trigger.Our findings demonstrate that self-tuning nonlinear parameters can optimize stability,robustness,and accuracy.At the same time,the antiphase hysteresis Schmitt trigger effectively rejects flutters without the need for collaborative navigation and guidance.Our hardware-in-the-loop simulation results confirm that this approach can eliminate aircraft jitter and shaking while ensuring expected stability and maneuverability.In conclusion,this nonlinear aileron mechatronics with a Schmitt positive feedback mechanism is a highly effective solution for distributed flight control and active flutter rejection.
基金supported by the Fondo para el Primer Proyecto of the Comitépara el Desarrollo de la Investigación(CODI)at the Universidad de Antioquia(Grant Number PRV2024-78509)。
文摘The objective of this paper is to present a robust safety-critical control system based on the active disturbance rejection control approach, designed to guarantee safety even in the presence of model inaccuracies, unknown dynamics, and external disturbances. The proposed method combines control barrier functions and control Lyapunov functions with a nonlinear extended state observer to produce a robust and safe control strategy for dynamic systems subject to uncertainties and disturbances. This control strategy employs an optimization-based control, supported by the disturbance estimation from a nonlinear extended state observer. Using a quadratic programming algorithm, the controller computes an optimal, stable, and safe control action at each sampling instant. The effectiveness of the proposed approach is demonstrated through numerical simulations of a safety-critical interconnected adaptive cruise control system.
文摘In recent years,there has been a growing demand for more efficient and robust control strategies in cooperative multi-robot systems.This paper introduces the cascade explicit tube model predictive controller(CET-MPC),a control architecture designed specifically for distributed aerial robot systems.By integrating an explicit model predictive controller(MPC)with a tube MPC,our approach significantly reduces online computational demands while enhancing robustness against disturbances such as wind and measurement noise,as well as uncertainties in inertia parameters.Further,we incorporate a cascade controller to minimize steady-state errors and improve system performance dynamically.The results of this assessment provide valuable insights into the effectiveness and reliability of the CET-MPC approach under realistic operating conditions.The simulation results of flight scenarios for multi-agent quadrotors demonstrate the controller’s stability and accurate tracking of the desired path.By addressing the complexities of quadrotors’six degrees of freedom,this controller serves as a versatile solution applicable to a wide range of multi-robot systems with varying degrees of freedom,demonstrating its adaptability and scalability beyond the quadrotor domain.
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.
文摘In this paper,a new study concerning the usage of artificial neural networks in the control application is given.It is shown,that the data gathered during proper operation of a given control plant can be used in the learning process to fully embrace the control pattern.Interestingly,the instances driven by neural networks have the ability to outperform the original analytically driven scenarios.Three different control schemes,namely perfect,linear-quadratic,and generalized predictive controllers were used in the theoretical study.In addition,the nonlinear recurrent neural network-based generalized predictive controller with the radial basis function-originated predictor was obtained to exemplify the main results of the paper regarding the real-world application.
基金supported in part by the Thai Nguyen University of Technology,Vietnam.
文摘This article presents an adaptive optimal control method for a semi-active suspension system.The model of the suspension system is built,in which the components of uncertain parameters and exogenous disturbance are described.The adaptive optimal control law consists of the sum of the optimal control component and the adaptive control component.First,the optimal control law is designed for the model of the suspension system after ignoring the components of uncertain parameters and exogenous disturbance caused by the road surface.The optimal control law expresses the desired dynamic characteristics of the suspension system.Next,the adaptive component is designed with the purpose of compensating for the effects caused by uncertain parameters and exogenous disturbance caused by the road surface;the adaptive component has adaptive parameter rules to estimate uncertain parameters and exogenous disturbance.When exogenous disturbances are eliminated,the system responds with an optimal controller designed.By separating theoretically the dynamic of a semi-active suspension system,this solution allows the design of two separate controllers easily and has reduced the computational burden and the use of too many tools,thus allowing for more convenient hardware implementation.The simulation results also show the effectiveness of damping oscillations of the proposed solution in this article.
基金supported by the National Natural Science Foundation of China(Grant No.62033007)the Major Fundamental Research Program of Shandong Province(Grant No.ZR2023ZD37).
文摘Siamese tracking algorithms usually take convolutional neural networks(CNNs)as feature extractors owing to their capability of extracting deep discriminative features.However,the convolution kernels in CNNs have limited receptive fields,making it difficult to capture global feature dependencies which is important for object detection,especially when the target undergoes large-scale variations or movement.In view of this,we develop a novel network called effective convolution mixed Transformer Siamese network(SiamCMT)for visual tracking,which integrates CNN-based and Transformer-based architectures to capture both local information and long-range dependencies.Specifically,we design a Transformer-based module named lightweight multi-head attention(LWMHA)which can be flexibly embedded into stage-wise CNNs and improve the network’s representation ability.Additionally,we introduce a stage-wise feature aggregation mechanism which integrates features learned from multiple stages.By leveraging both location and semantic information,this mechanism helps the SiamCMT to better locate and find the target.Moreover,to distinguish the contribution of different channels,a channel-wise attention mechanism is introduced to enhance the important channels and suppress the others.Extensive experiments on seven challenging benchmarks,i.e.,OTB2015,UAV123,GOT10K,LaSOT,DTB70,UAVTrack112_L,and VOT2018,demonstrate the effectiveness of the proposed algorithm.Specially,the proposed method outperforms the baseline by 3.5%and 3.1%in terms of precision and success rates with a real-time speed of 59.77 FPS on UAV123.
基金supported by the Secretaría de Investigación y Posgrado del Instituto Politécnico Nacional(SIP-IPN)under grants 20250098,20250168,20251291 and 20254791by Universidad Iberoamericana Ciudad de México+1 种基金Victor G.Sánchez-Meza is a Secretaría de Ciencia,Humanidades,Tecnología e Innovación(Secihti)fellow(CVU 964590)support received.Yair Lozano thanks the support of the Coordinación de Operación y Redes de Investigación y Posgrado of the IPN through the Red de Inteligencia Artificial y Ciencia de Datos and the Red de Expertos en Innovación Automotriz.
文摘In this article,the dynamical model and trajectory tracking problem for a tilt-rotor unmanned aerial vehicle is tackled through linear Active Disturbance Rejection Control(ADRC)applied on the tangent linearized system.To apply the ADRC scheme,it is considered the subsystem without the Y-axis component,which is differentially flat and whose flat outputs are obtained using the Kronecker matrix.Numerical assessment using as system parameters the ones of a scale prototype is provided to show the effectiveness of the proposal leading to accurate tracking results using admissible control values for an experimental scenario.
基金supported by the National Natural Science Foundation under Grant 62273189the Shandong Province Natural Science Foundation under Grant ZR2021MF005Systems Science Plus Joint Research Program of Qingdao University under Grant XT2024201 of China supporting this research work.
文摘This article investigates the anti-disturbance and stabilization problems for the nonlinear uncertain permanent magnet synchronous motor(PMSM)with stator voltage saturation and unknown load.A smooth switching mechanism is presented to structure the adaptive integral terminal sliding mode control(SMC)strategy.The control design consists of compensation control and nominal control,which improves the rapidity and accuracy of trajectory tracking.The smooth saturation model based on the error function is applied to approximate the voltage saturation phenomenon.Additionally,to deal with the adverse effects of various unknown disturbances,including model parameter uncertainties and unknown external load disturbances,an improved disturbance observer(DO)is proposed.This observer effectively suppresses the fluctuations caused by fixed gain during the starting period of the system.Finally,the experimental results under different conditions show that the proposed strategy has good tracking and disturbance suppression performances.
基金supported by the Artificial Intelligence Innovation and Development Special Fund of Shanghai(No.2019RGZN01041)the National Natural Science Foundation of China(No.92048205).
文摘This paper presents a robust finite-time visual servo control strategy for the tracking problem of omni-directional mobile manipulators(OMMs)subject to mismatched disturbances.First,the nonlinear kinematic model of visual servoing for OMMs with mismatched disturbances is explicitly presented to solve the whole-body inverse kinematic problem.Second,a sliding mode observer augmented with an integral terminal sliding mode controller is proposed to handle these uncertainties and ensure that the system converges to a small region around the equilibrium point.The boundary layer technique is employed to mitigate the chattering phenomenon.Furthermore,a strict finite-time Lyapunov stability analysis is conducted.An experimental comparison between the proposed algorithm and a traditional position-based visual servo controller is carried out,and the results demonstrate the superiority of the proposed control algorithm.
基金support through his Master scholarshipThe Vicerrectoría de Investigación y Estudios de Posgrado(VIEP-BUAP)partially funded this work under grant number 00593-PV/2025.
文摘This paper aims to fuse two well-established and,at the same time,opposed control techniques,namely,model predictive control(MPC)and active disturbance rejection control(ADRC),to develop a dynamic motion controller for a laser beam steering system.The proposed technique uses the ADRC philosophy to lump disturbances and model uncertainties into a total disturbance.Then,the total disturbance is estimated via a discrete extended state disturbance observer(ESO),and it is used to(1)handle the system constraints in a quadratic optimization problem and(2)injected as a feedforward term to the plant to reject the total disturbance,together with the feedback term obtained by the MPC.The main advantage of the proposed approach is that the MPC is designed based on a straightforward integrator-chain model such that a simple convex optimization problem is performed.Several experiments show the real-time closed-loop performance regarding trajectory tracking and disturbance rejection.Owing to simplicity,the self-contained approach MPC+ESO becomes a Frugal MPC,which is computationally economical,adaptable,efficient,resilient,and suitable for applications where on-board computational resources are limited.
基金supported in part by the European Regional Development Fund under Grant KK.01.1.1.01.0009(DATACROSS).
文摘This paper deals with reduction of losses in electric power distribution system through a dynamic reconfiguration case study of a grid in the city of Mostar,Bosnia and Herzegovina.The proposed solution is based on a nonlinear model predictive control algorithm which determines the optimal switching operations of the distribution system.The goal of the control algorithm is to find the optimal radial network topology which minimizes cumulative active power losses and maximizes voltages across the network while simultaneously satisfying all system constraints.The optimization results are validated through multiple simulations(using real power demand data collected for a few characteristic days during winter and summer)which demonstrate the efficiency and usefulness of the developed control algorithm in reducing the grid losses by up to 14%.
基金supported in part by the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources under Grant LAPS24009in part by the Guangdong Basic and Applied Basic Research Foundation under Grant 2021A1515110016in part by the National Natural Science Foundation of China under Grant 52206009.
文摘With the increasing penetration of renewable energy resources in power systems,conventional timescale separated load frequency control(LFC)and economic dispatch may degrade frequency performance and reduce economic efficiency.This paper proposes a novel data-driven adaptive distributed optimal disturbance rejection control(DODRC)method for real-time economic LFC problem in nonlinear power systems.Firstly,a basic DODRC method is proposed by integrating the active disturbance rejection control method and the partial primal–dual algorithm.Then,to deal with the tie-line power flow constraints,the logarithmic barrier function is employed to reconstruct the Lagrange function to obtain the constrained DODRC method.By analyzing the sensitivity of the uncertain parameters of power systems,a data-driven adaptive DODRC method is finally proposed with a neural network.The effectiveness of the proposed method is demonstrated by experimental results using real-time equipment.
基金supported in part by Sichuan Science and Technology Program under Grant No.2025ZNSFSC151in part by the Strategic Priority Research Program of Chinese Academy of Sciences under Grant No.XDA27030201+1 种基金the Natural Science Foundation of China under Grant No.U21B6001in part by the Natural Science Foundation of Tianjin under Grant No.24JCQNJC01930.
文摘The work proposes a distributed Kalman filtering(KF)algorithm to track a time-varying unknown signal process for a stochastic regression model over network systems in a cooperative way.We provide the stability analysis of the proposed distributed KF algorithm without independent and stationary signal assumptions,which implies that the theoretical results are able to be applied to stochastic feedback systems.Note that the main difficulty of stability analysis lies in analyzing the properties of the product of non-independent and non-stationary random matrices involved in the error equation.We employ analysis techniques such as stochastic Lyapunov function,stability theory of stochastic systems,and algebraic graph theory to deal with the above issue.The stochastic spatio-temporal cooperative information condition shows the cooperative property of multiple sensors that even though any local sensor cannot track the time-varying unknown signal,the distributed KF algorithm can be utilized to finish the filtering task in a cooperative way.At last,we illustrate the property of the proposed distributed KF algorithm by a simulation example.
基金supported by the National Natural Science Foundation of China(Nos.62063009,52262050)the National Key Research and Development Program during the 14th 5-Year Plan(No.2023YFB4302100)the Major Science and Technology Research and Development Special Project in Jiangxi Province(No.20232ACE01011).
文摘To address the issue of disturbance compensation deviation in linear active disturbance rejection control(LADRC),a linear active disturbance rejection control method with reference to the integral chain model(LADRC-R)is proposed.By constructing an ideal control reference model,a dynamic correlation between output deviation and uncompensated disturbances is established,and a dual-loop compensation mechanism is designed.Based on theoretical analysis and frequency-domain characteristics of typical first/second-order systems,this method maintains the parameter-tuning advantages of LADRC while reducing disturbance effects by 50%and introducing no phase lag during low-frequency disturbance suppression.Simulations on second-order systems verify its robustness under parameter perturbations,gain mismatch,and complex disturbances,and an optimized design scheme for the deviation compensator is proposed to suppress discontinuous measurement noise interference.Finally,the engineering effectiveness of this method in precision motion control is validated on an electromagnetic suspension platform,providing a new approach to improving the control performance of LADRC in environments with uncertain disturbances.
基金supported partially by the National Natural Science Foundation(No.62473344)the T-Flight Laboratory in ShanXi Provincial(No.GSFC2024NBKY05)+1 种基金the Natural Science Basic Research Program of Shaanxi(No.2025JC-YBQN-035)the National Natural Science Foundation of China(Grant No.92471204).
文摘With the growing adoption of artificial intelligence algorithms and neural networks,online learning and adaptive methods for updating the bandwidth have become increasingly prevalent.However,the conditions required to ensure closed-loop stability when employing a time-varying bandwidth,as well as the supporting mathematical foundations,remain insufficiently studied.This paper investigates the stability condition for active disturbance rejection control(ADRC)with a time-varying bandwidth extended state observer(ESO).A new stability condition is derived,which means that the upper bound of rate of change for ESO bandwidth should be restricted.Moreover,under the proposed condition,the closed-loop stability of ADRC with a time-varying bandwidth observer is rigorously proved for nonlinear uncertainties.In simulations,the necessity of the proposed condition is illustrated,demonstrating that the rate of change of ESO bandwidth is crucial for closed-loop stability.
