This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temp...This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temperature distribution,suitable for control design due to its balance between physical fidelity and computational simplicity.The controller uses a wavelet-based neural proportional,integral,derivative(PID)controller with IIR filtering(infinite impulse response).The dynamic model captures the essential heat and mass transfer phenomena through a nonlinear energy balance,where the cooling capacity“Qevap”is expressed as a non-linear function of the compressor frequency and the temperature difference,specifically,Q_(evap)=k_(1)u(T_(in)−T_(e))with u as compressor frequency,Te evaporator temperature,and Tin inlet fluid temperature.The operating conditions of the system,in general terms,focus on the following variables,the overall thermal capacity is 1000 J/K,typical for small-capacity heat exchangers,The mass flow is 0.05 kg/s,typical for secondary liquid cooling circuits,the overall loss coefficient of 50 W/K that corresponds to small evaporators with partial insulation,the temperatures(inlet)of 10℃and the temperature of environment of 25℃,thermal load of 200 W that corresponds to a small-scaled air conditioning applications.To handle system nonlinearities and improve control performance,aMorlet wavelet-based neural network(Wavenet)is used to dynamically adjust the PID gains online.An IIR filter is incorporated to smooth the adaptive gains,improving stability and reducing oscillations.In contrast to prior wavelet-or neural-adaptive PID controllers in HVAC applications,which typically adjust gains without explicit filtering or not tailored to evaporator dynamics,this work introduces the first PID–Wavenet scheme augmented with an IIR-based stabilization layer,specifically designed to address the combined challenges of nonlinear evaporator behavior,gain oscillation,and real-time implementability.The proposed controller(PID-Wavenet+IIR)is implemented and validated inMATLAB/Simulink,demonstrating superior performance compared to a conventional PID tuned using Simulink’s auto-tuning function.Key results include a reduction in settling time from 13.3 to 8.2 s,a reduction in overshoot from 3.5%to 0.8%,a reduction in steady-state error from 0.12℃ to 0.02℃and a 13%reduction in energy overall consumption.The controller also exhibits greater robustness and adaptability under varying thermal loads.This explicit integration of wavelet-driven adaptation with IIR-filtered gain shaping constitutes the main methodological contribution and novelty of the work.These findings validate the effectiveness of the wavelet-based adaptive approach for advanced thermal management in refrigeration and HVAC systems,with potential applications in controlling variable-speed compressors,liquid chillers,and compact cooling units.展开更多
This study constructs a dual-capacitor neuron circuit(connected via a memristor)integrated with a phototube and a thermistor to simulate the ability of biological neurons to simultaneously perceive light and thermal s...This study constructs a dual-capacitor neuron circuit(connected via a memristor)integrated with a phototube and a thermistor to simulate the ability of biological neurons to simultaneously perceive light and thermal stimuli.The circuit model converts photothermal signals into electrical signals,and its dynamic behavior is described using dimensionless equations derived from Kirchhoff's laws.Based on Helmholtz's theorem,a pseudo-Hamiltonian energy function is introduced to characterize the system's energy metabolism.Furthermore,an adaptive control function is proposed to elucidate temperature-dependent firing mechanisms,in which temperature dynamics are regulated by pseudo-Hamiltonian energy.Numerical simulations using the fourth-order Runge-Kutta method,combined with bifurcation diagrams,Lyapunov exponent spectra,and phase portraits,reveal that parameters such as capacitance ratio,phototube voltage amplitude/frequency,temperature,and thermistor reference resistance significantly modulate neuronal firing patterns,inducing transitions between periodic and chaotic states.Periodic states typically exhibit higher average pseudo-Hamiltonian energy than chaotic states.Two-parameter analysis demonstrates that phototube voltage amplitude and temperature jointly govern firing modes,with chaotic behavior emerging within specific parameter ranges.Adaptive control studies show that gain/attenuation factors,energy thresholds,ceiling temperatures,and initial temperatures regulate the timing and magnitude of system temperature saturation.During both heating and cooling phases,temperature dynamics are tightly coupled with pseudoHamiltonian energy and neuronal firing activity.These findings validate the circuit's ability to simulate photothermal perception and adaptive temperature regulation,contributing to a deeper understanding of neuronal encoding mechanisms and multimodal sensory processing.展开更多
The present study investigates the quest for a fully distributed Nash equilibrium(NE) in networked non-cooperative games, with particular emphasis on actuator limitations. Existing distributed NE seeking approaches of...The present study investigates the quest for a fully distributed Nash equilibrium(NE) in networked non-cooperative games, with particular emphasis on actuator limitations. Existing distributed NE seeking approaches often overlook practical input constraints or rely on centralized information. To address these issues, a novel edge-based double-layer adaptive control framework is proposed. Specifically, adaptive scaling parameters are embedded into the edge weights of the communication graph, enabling a fully distributed scheme that avoids dependence on centralized or global knowledge. Every participant modifies its strategy by exclusively utilizing local information and communicating with its neighbors to iteratively approach the NE. By incorporating damping terms into the design of the adaptive parameters, the proposed approach effectively suppresses unbounded parameter growth and consequently guarantees the boundedness of the adaptive gains. In addition, to account for actuator saturation, the proposed distributed NE seeking approach incorporates a saturation function, which ensures that control inputs do not exceed allowable ranges. A rigorous Lyapunov-based analysis guarantees the convergence and boundedness of all system variables. Finally, the presentation of simulation results aims to validate the efficacy and theoretical soundness of the proposed approach.展开更多
This study examines the adaptive boundary control problem of flexible marine riser with internal flow coupling.The dynamic model of the flexible marine riser system with internal flow coupling is derived using the Ham...This study examines the adaptive boundary control problem of flexible marine riser with internal flow coupling.The dynamic model of the flexible marine riser system with internal flow coupling is derived using the Hamiltonian principle.An analysis of internal flow’s influence on the vibration characteristics of flexible marine risers is conducted.Then,for the uncertain environmental disturbance,the adaptive fuzzy logic system is introduced to dynamically approximate the boundary disturbance,and a robust adaptive fuzzy boundary control is proposed.The uniform boundedness of the closed-loop system is proved based on Lyapunov theory.The well-posedness of the closed-loop system is proved by operator semigroup theory.The proposed control’s effectiveness is validated through comparison with existing control methods.展开更多
Wireless communication-enabled Cooperative Adaptive Cruise Control(CACC)is expected to improve the safety and traffic capacity of vehicle platoons.Existing CACC considers a conventional communication delay with fixed ...Wireless communication-enabled Cooperative Adaptive Cruise Control(CACC)is expected to improve the safety and traffic capacity of vehicle platoons.Existing CACC considers a conventional communication delay with fixed Vehicular Communication Network(VCN)topologies.However,when the network is under attack,the communication delay may be much higher,and the stability of the system may not be guaranteed.This paper proposes a novel communication Delay Aware CACC with Dynamic Network Topologies(DADNT).The main idea is that for various communication delays,in order to maximize the traffic capacity while guaranteeing stability and minimizing the following error,the CACC should dynamically adjust the VCN network topology to achieve the minimum inter-vehicle spacing.To this end,a multi-objective optimization problem is formulated,and a 3-step Divide-And-Conquer sub-optimal solution(3DAC)is proposed.Simulation results show that with 3DAC,the proposed DADNT with CACC can reduce the inter-vehicle spacing by 5%,10%,and 14%,respectively,compared with the traditional CACC with fixed one-vehicle,two-vehicle,and three-vehicle look-ahead network topologies,thereby improving the traffic efficiency.展开更多
The stability of supersonic inlets faces challenges due to various changes in flight conditions,and flow control methods that address shock wave/boundary layer interactions under only one set of conditions cannot meet...The stability of supersonic inlets faces challenges due to various changes in flight conditions,and flow control methods that address shock wave/boundary layer interactions under only one set of conditions cannot meet developmental requirements.This paper proposes an adaptive bump control scheme and employs dynamic mesh technology for numerical simulation to investigate the unsteady control effects of adaptive bumps.The obtained results indicate that the use of moving bumps to control shock wave/boundary layer interactions is feasible.The adaptive control effects of five different bump speeds are evaluated.Within the range of bump speeds studied,the analysis of the flow field structure reveals the patterns of change in the separation zone area during the control process,as well as the relationship between the bump motion speed and the control effect on the separation zone.It is concluded that the moving bump endows the boundary layer with additional energy.展开更多
This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-tri...This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples.展开更多
Dear Editor,It is well known that event-triggered control(ETC)is an effective approach in addressing networked control problems for Industry 5.0.Its feasibility,however,is still restricted to canonical nonlinear syste...Dear Editor,It is well known that event-triggered control(ETC)is an effective approach in addressing networked control problems for Industry 5.0.Its feasibility,however,is still restricted to canonical nonlinear systems so far.Considering this,a gradient-based adaptive ETC scheme for noncanonical nonlinear systems is newly developed in this letter,where the hysteresis input constraints are considered also.By proper decomposition,the technical issue of handling ETC-induced measurement errors and hysteresis inputs can be transformed into the robustness problem to bounded disturbance-like terms,which is then addressed by integrating a switching modification strategy in adaptive design and developing a novel augmented error-based analysis framework.Experimental results based on a practical piezoactuator confirm the effectiveness of the proposed scheme.展开更多
The development of the adaptive cycle engine is a crucial direction of advanced fighter power sources in the near future.However,this new technology brings more uncertainty to the design of the control system.To addre...The development of the adaptive cycle engine is a crucial direction of advanced fighter power sources in the near future.However,this new technology brings more uncertainty to the design of the control system.To address the versatile thrust demand under complex dynamic characteristics of the adaptive cycle engine,this paper proposes a direct thrust estimation and control method based on the Model-Free Adaptive Control(MFAC)algorithm.First,an improved Sliding Mode Control-MFAC(SMC-MFAC)algorithm has been developed by introducing a sliding mode variable structure into the standard Full Format Dynamic Linearization-MFAC(FFDL-MFAC)and designing self-adaptive weight coefficients.Then a trivariate double-loop direct thrust control structure with a controller-based thrust estimator and an outer command compensation loop has been established.Through thrust feedback and command correction,accurate control under multi-mode and operation conditions is achieved.The main contribution of this paper is the improved algorithm that combines the tracking capability of the MFAC and the robustness of the SMC,thus enhancing the dynamic performance.Considering the requirements of the online thrust feedback,the designed MFAC-based thrust estimator significantly speeds up the calculation.Additionally,the proposed command correction module can achieve the adaptive thrust control without affecting the operation of the inner loop.Simulations and Hardware-in-Loop(HIL)experiments have been performed on an adaptive cycle engine component-level model to investigate the estimation and control effect under different modes and health conditions.The results demonstrate that both the thrust estimation precision and operation speed are significantly improved compared with Extended Kalman Filter(EKF).Furthermore,the system can accelerate the response of the controlled plant,reduce the overshoot,and realize the thrust recovery within the safety range when the engine encounters the degradation.展开更多
This paper investigates the problem of fuzzy adaptive finite-time inverse optimal control for active suspension systems(ASSs).The fuzzy logic systems(FLSs)are utilized to learn the unknown non-linear dynamics and an a...This paper investigates the problem of fuzzy adaptive finite-time inverse optimal control for active suspension systems(ASSs).The fuzzy logic systems(FLSs)are utilized to learn the unknown non-linear dynamics and an auxiliary system is established.Based on the finite-time stability theory and inverse optimal theory,a fuzzy adaptive inverse finite-time inverse optimal control method is proposed.It is proven that the formulated control approach guarantees the stability of the controlled systems,while ensuring that errors converge to a small neighborhood of zero within finite time.Moreover,the optimized control performance can be achieved.Eventually,the simulation results demonstrate the effectiveness of the proposed fuzzy adaptive finite-time inverse optimal control scheme.展开更多
This paper investigates the problem of cluster synchronization of master-slave complex net-works with time-varying delay via linear and adaptive feedback pinning controls.We need not non-delayed and delayed coupling m...This paper investigates the problem of cluster synchronization of master-slave complex net-works with time-varying delay via linear and adaptive feedback pinning controls.We need not non-delayed and delayed coupling matrices to be symmetric or irreducible.We have the advantages of using adaptive control method to reduce control gain and pinning control technology to reduce cost.By con-structing Lyapunov function,some sufficient synchronization criteria are established.Finally,numerical examples are employed to illustrate the effectiveness of the proposed approach.展开更多
In the field of flexible polishing,the accuracy of contact force control directly affects processing quality and material removal uniformity.However,the complex dynamic contact model and inherent strong hysteresis of ...In the field of flexible polishing,the accuracy of contact force control directly affects processing quality and material removal uniformity.However,the complex dynamic contact model and inherent strong hysteresis of pneumatic systems can significantly impact the force control accuracy of pneumatic polishing system end-effectors.To enhance responsiveness and control precision during the flexible polishing process,this study proposes an observer-based fuzzy adaptive control(OBFAC)scheme.To ensure control accuracy under an uncertain dynamic contact model,a fuzzy state observer is designed to estimate unmeasured states,while fuzzy logic approximates the uncertain nonlinear functions in the model to improve control performance.Additionally,the integral barrier Lyapunov function is employed to ensure that all states remain within predefined constraints.The stability of the proposed control scheme is analyzed using the Lyapunov function,and a pneumatic polishing experimental platform is constructed to conduct polishing contact force control experiments under multiple scenarios.Experimental results demonstrate that the proposed OBFAC scheme achieves superior tracking control performance compared to existing control schemes.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
Tracking control of tendon-driven manipulators has become a prevalent research area.However,the existence of flexible elastic tendons generates substantial residual vibrations,resulting in difficulties for trajectory ...Tracking control of tendon-driven manipulators has become a prevalent research area.However,the existence of flexible elastic tendons generates substantial residual vibrations,resulting in difficulties for trajectory tracking control of the manipulator.This paper proposes the radial basis function neural network adaptive hierarchical sliding mode control(RBFNNA-HSMC)method,which combines the dynamic model of the elastic tendon-driven manipulator(ETDM)with radial basis neural network adaptive control and hierarchical sliding mode control technology.The aim is to achieve trajectory tracking control of ETDM even under conditions of model inaccuracy and disturbance.The Lyapunov stability theory demonstrates the stability of the proposed RBFNNA-HSM controller.In order to assess the effectiveness and adaptability of the proposed control method,simulations and experiments were performed on a two-DOF ETDM.The RBFNNA-HSM method shows superior tracking accuracy compared to traditional modelbased HSM control.The experiment shows that the maximum tracking error for ETDM double-joint trajectory tracking is below 2.593×10-3rad and 1.624×10-3rad,respectively.展开更多
Sliding mode control(SMC)is a well-known robust nonlinear control method with strong robustness and fast response which has been widely used in many applications.This paper introduces the major results of SMC design m...Sliding mode control(SMC)is a well-known robust nonlinear control method with strong robustness and fast response which has been widely used in many applications.This paper introduces the major results of SMC design methods that the authors have achieved in the last decade.Undoubtedly,our results are obtained based on many other researchers'pioneer work in the literature which will not be discussed in detail here.Notably,our development has a main focus on tackling practical issues such that a proposed or enhanced SMC approach is effectively applicable to motion control systems.Issues on sliding function and adaptive gain designs in SMC and their control features will be both discussed in this paper.Those issues comprise fast convergent speed,predefined convergent time,input saturation restriction,chattering reduction,and unknown disturbance suppression.Lastly,conclusion and a few remarks on future research directions are presented.展开更多
In this study,we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults.First,an inverse hysteresis dynamics model is introduced,and then...In this study,we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults.First,an inverse hysteresis dynamics model is introduced,and then the control input is divided into an expected input and an error compensator.Second,a novel adaptive neural network-based control scheme is proposed to cancel the unknown input hysteresis.Subsequently,by modifying the adaptive laws and local control laws,a fault-tolerant control strategy is applied to address uncertain intermittent actuator faults in a flexible manipulator system.Through the direct Lyapunov theory,the proposed scheme allows the state errors to asymptotically converge to a specified interval.Finally,the effectiveness of the proposed scheme is verified through numerical simulations and experiments.展开更多
Dear Editor,Active magnetic bearings(AMBs)are of considerable interest and significance in smart manufacturing due to their zero-friction and adaptivity to noncontact rotor rotations.This paper proposes an active levi...Dear Editor,Active magnetic bearings(AMBs)are of considerable interest and significance in smart manufacturing due to their zero-friction and adaptivity to noncontact rotor rotations.This paper proposes an active levitation control algorithm based on adaptive sliding mode control(ASMC)equipped with linear extended state observer(LESO).Sufficient conditions are derived to guarantee the asymptotical stability of the associated closed-loop system.Experiments are conducted on a real AMB-rotor platform to demonstrate the effectiveness and superiority of the proposed algorithm.展开更多
Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncerta...Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.展开更多
A robust Adaptive Discrete-time Sliding Mode Controller (ADSMC) is formulated, and is applied to control the pitch motion of a simulated Flapping-Wing Micro Air Vehicle (FWMAV). There is great potential for FWMAVs to ...A robust Adaptive Discrete-time Sliding Mode Controller (ADSMC) is formulated, and is applied to control the pitch motion of a simulated Flapping-Wing Micro Air Vehicle (FWMAV). There is great potential for FWMAVs to be used as aerial tools to assist with gathering data and surveying environments. Thanks to modern manufacturing and technology, along with an increased comprehension behind the aerodynamics of wing flaps, these vehicles are now a reality, though not without limitations. Given their diminutive size, FWMAVs are susceptible to real-world disturbances, such as wind gusts, and are sensitive to particular variations in their build quality. While external forces such as wind gusts can be reasonably bounded, the unknown variations in the state may be difficult to characterize or bound without affecting performance. To address these problems, an ADSMC is developed. First, the FWMAV model is converted from continuous-time to discrete-time. Second, an ADSMC for the newly discretized FWMAV model is developed. Using this controller, the trajectory tracking performance of the FWMAV is assessed against a traditional discrete sliding mode controller, and is found to have a decreased chattering frequency and decreased control effort for the same task. Therefore, the ADSMC is assessed as the superior controller, despite being completely unaware of the model parameters or wind gust.展开更多
文摘This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temperature distribution,suitable for control design due to its balance between physical fidelity and computational simplicity.The controller uses a wavelet-based neural proportional,integral,derivative(PID)controller with IIR filtering(infinite impulse response).The dynamic model captures the essential heat and mass transfer phenomena through a nonlinear energy balance,where the cooling capacity“Qevap”is expressed as a non-linear function of the compressor frequency and the temperature difference,specifically,Q_(evap)=k_(1)u(T_(in)−T_(e))with u as compressor frequency,Te evaporator temperature,and Tin inlet fluid temperature.The operating conditions of the system,in general terms,focus on the following variables,the overall thermal capacity is 1000 J/K,typical for small-capacity heat exchangers,The mass flow is 0.05 kg/s,typical for secondary liquid cooling circuits,the overall loss coefficient of 50 W/K that corresponds to small evaporators with partial insulation,the temperatures(inlet)of 10℃and the temperature of environment of 25℃,thermal load of 200 W that corresponds to a small-scaled air conditioning applications.To handle system nonlinearities and improve control performance,aMorlet wavelet-based neural network(Wavenet)is used to dynamically adjust the PID gains online.An IIR filter is incorporated to smooth the adaptive gains,improving stability and reducing oscillations.In contrast to prior wavelet-or neural-adaptive PID controllers in HVAC applications,which typically adjust gains without explicit filtering or not tailored to evaporator dynamics,this work introduces the first PID–Wavenet scheme augmented with an IIR-based stabilization layer,specifically designed to address the combined challenges of nonlinear evaporator behavior,gain oscillation,and real-time implementability.The proposed controller(PID-Wavenet+IIR)is implemented and validated inMATLAB/Simulink,demonstrating superior performance compared to a conventional PID tuned using Simulink’s auto-tuning function.Key results include a reduction in settling time from 13.3 to 8.2 s,a reduction in overshoot from 3.5%to 0.8%,a reduction in steady-state error from 0.12℃ to 0.02℃and a 13%reduction in energy overall consumption.The controller also exhibits greater robustness and adaptability under varying thermal loads.This explicit integration of wavelet-driven adaptation with IIR-filtered gain shaping constitutes the main methodological contribution and novelty of the work.These findings validate the effectiveness of the wavelet-based adaptive approach for advanced thermal management in refrigeration and HVAC systems,with potential applications in controlling variable-speed compressors,liquid chillers,and compact cooling units.
基金supported by the Natural Science Founda tion of Chongqing(Grant No.CSTB2024NSCQ-MSX0944)。
文摘This study constructs a dual-capacitor neuron circuit(connected via a memristor)integrated with a phototube and a thermistor to simulate the ability of biological neurons to simultaneously perceive light and thermal stimuli.The circuit model converts photothermal signals into electrical signals,and its dynamic behavior is described using dimensionless equations derived from Kirchhoff's laws.Based on Helmholtz's theorem,a pseudo-Hamiltonian energy function is introduced to characterize the system's energy metabolism.Furthermore,an adaptive control function is proposed to elucidate temperature-dependent firing mechanisms,in which temperature dynamics are regulated by pseudo-Hamiltonian energy.Numerical simulations using the fourth-order Runge-Kutta method,combined with bifurcation diagrams,Lyapunov exponent spectra,and phase portraits,reveal that parameters such as capacitance ratio,phototube voltage amplitude/frequency,temperature,and thermistor reference resistance significantly modulate neuronal firing patterns,inducing transitions between periodic and chaotic states.Periodic states typically exhibit higher average pseudo-Hamiltonian energy than chaotic states.Two-parameter analysis demonstrates that phototube voltage amplitude and temperature jointly govern firing modes,with chaotic behavior emerging within specific parameter ranges.Adaptive control studies show that gain/attenuation factors,energy thresholds,ceiling temperatures,and initial temperatures regulate the timing and magnitude of system temperature saturation.During both heating and cooling phases,temperature dynamics are tightly coupled with pseudoHamiltonian energy and neuronal firing activity.These findings validate the circuit's ability to simulate photothermal perception and adaptive temperature regulation,contributing to a deeper understanding of neuronal encoding mechanisms and multimodal sensory processing.
基金supported by the National Natural Science Foundation of China (Grant No.62173009)the National Key Research and Development Program of China (Grant No.2021ZD0112302)。
文摘The present study investigates the quest for a fully distributed Nash equilibrium(NE) in networked non-cooperative games, with particular emphasis on actuator limitations. Existing distributed NE seeking approaches often overlook practical input constraints or rely on centralized information. To address these issues, a novel edge-based double-layer adaptive control framework is proposed. Specifically, adaptive scaling parameters are embedded into the edge weights of the communication graph, enabling a fully distributed scheme that avoids dependence on centralized or global knowledge. Every participant modifies its strategy by exclusively utilizing local information and communicating with its neighbors to iteratively approach the NE. By incorporating damping terms into the design of the adaptive parameters, the proposed approach effectively suppresses unbounded parameter growth and consequently guarantees the boundedness of the adaptive gains. In addition, to account for actuator saturation, the proposed distributed NE seeking approach incorporates a saturation function, which ensures that control inputs do not exceed allowable ranges. A rigorous Lyapunov-based analysis guarantees the convergence and boundedness of all system variables. Finally, the presentation of simulation results aims to validate the efficacy and theoretical soundness of the proposed approach.
基金financially supported by Sichuan Science and Technology Program(Grant No.2023NSFSC1980).
文摘This study examines the adaptive boundary control problem of flexible marine riser with internal flow coupling.The dynamic model of the flexible marine riser system with internal flow coupling is derived using the Hamiltonian principle.An analysis of internal flow’s influence on the vibration characteristics of flexible marine risers is conducted.Then,for the uncertain environmental disturbance,the adaptive fuzzy logic system is introduced to dynamically approximate the boundary disturbance,and a robust adaptive fuzzy boundary control is proposed.The uniform boundedness of the closed-loop system is proved based on Lyapunov theory.The well-posedness of the closed-loop system is proved by operator semigroup theory.The proposed control’s effectiveness is validated through comparison with existing control methods.
基金supported by the National Natural Science Foundation of China under Grant U21A20449in part by Jiangsu Provincial Key Research and Development Program under Grant BE2021013-2。
文摘Wireless communication-enabled Cooperative Adaptive Cruise Control(CACC)is expected to improve the safety and traffic capacity of vehicle platoons.Existing CACC considers a conventional communication delay with fixed Vehicular Communication Network(VCN)topologies.However,when the network is under attack,the communication delay may be much higher,and the stability of the system may not be guaranteed.This paper proposes a novel communication Delay Aware CACC with Dynamic Network Topologies(DADNT).The main idea is that for various communication delays,in order to maximize the traffic capacity while guaranteeing stability and minimizing the following error,the CACC should dynamically adjust the VCN network topology to achieve the minimum inter-vehicle spacing.To this end,a multi-objective optimization problem is formulated,and a 3-step Divide-And-Conquer sub-optimal solution(3DAC)is proposed.Simulation results show that with 3DAC,the proposed DADNT with CACC can reduce the inter-vehicle spacing by 5%,10%,and 14%,respectively,compared with the traditional CACC with fixed one-vehicle,two-vehicle,and three-vehicle look-ahead network topologies,thereby improving the traffic efficiency.
基金supported by the National Key R&D Program of China(Grant No.2019YFA0405300)the National Natural Science Foundation of China(Grant No.11972368)the Natural Science Foundation of Hunan Province(Grant No.2021JJ10045).
文摘The stability of supersonic inlets faces challenges due to various changes in flight conditions,and flow control methods that address shock wave/boundary layer interactions under only one set of conditions cannot meet developmental requirements.This paper proposes an adaptive bump control scheme and employs dynamic mesh technology for numerical simulation to investigate the unsteady control effects of adaptive bumps.The obtained results indicate that the use of moving bumps to control shock wave/boundary layer interactions is feasible.The adaptive control effects of five different bump speeds are evaluated.Within the range of bump speeds studied,the analysis of the flow field structure reveals the patterns of change in the separation zone area during the control process,as well as the relationship between the bump motion speed and the control effect on the separation zone.It is concluded that the moving bump endows the boundary layer with additional energy.
文摘This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples.
文摘Dear Editor,It is well known that event-triggered control(ETC)is an effective approach in addressing networked control problems for Industry 5.0.Its feasibility,however,is still restricted to canonical nonlinear systems so far.Considering this,a gradient-based adaptive ETC scheme for noncanonical nonlinear systems is newly developed in this letter,where the hysteresis input constraints are considered also.By proper decomposition,the technical issue of handling ETC-induced measurement errors and hysteresis inputs can be transformed into the robustness problem to bounded disturbance-like terms,which is then addressed by integrating a switching modification strategy in adaptive design and developing a novel augmented error-based analysis framework.Experimental results based on a practical piezoactuator confirm the effectiveness of the proposed scheme.
基金supported by National Natural Science Foundation of China(No.52302472)。
文摘The development of the adaptive cycle engine is a crucial direction of advanced fighter power sources in the near future.However,this new technology brings more uncertainty to the design of the control system.To address the versatile thrust demand under complex dynamic characteristics of the adaptive cycle engine,this paper proposes a direct thrust estimation and control method based on the Model-Free Adaptive Control(MFAC)algorithm.First,an improved Sliding Mode Control-MFAC(SMC-MFAC)algorithm has been developed by introducing a sliding mode variable structure into the standard Full Format Dynamic Linearization-MFAC(FFDL-MFAC)and designing self-adaptive weight coefficients.Then a trivariate double-loop direct thrust control structure with a controller-based thrust estimator and an outer command compensation loop has been established.Through thrust feedback and command correction,accurate control under multi-mode and operation conditions is achieved.The main contribution of this paper is the improved algorithm that combines the tracking capability of the MFAC and the robustness of the SMC,thus enhancing the dynamic performance.Considering the requirements of the online thrust feedback,the designed MFAC-based thrust estimator significantly speeds up the calculation.Additionally,the proposed command correction module can achieve the adaptive thrust control without affecting the operation of the inner loop.Simulations and Hardware-in-Loop(HIL)experiments have been performed on an adaptive cycle engine component-level model to investigate the estimation and control effect under different modes and health conditions.The results demonstrate that both the thrust estimation precision and operation speed are significantly improved compared with Extended Kalman Filter(EKF).Furthermore,the system can accelerate the response of the controlled plant,reduce the overshoot,and realize the thrust recovery within the safety range when the engine encounters the degradation.
基金supported by the National Natural Science Foundation of China under 62173172。
文摘This paper investigates the problem of fuzzy adaptive finite-time inverse optimal control for active suspension systems(ASSs).The fuzzy logic systems(FLSs)are utilized to learn the unknown non-linear dynamics and an auxiliary system is established.Based on the finite-time stability theory and inverse optimal theory,a fuzzy adaptive inverse finite-time inverse optimal control method is proposed.It is proven that the formulated control approach guarantees the stability of the controlled systems,while ensuring that errors converge to a small neighborhood of zero within finite time.Moreover,the optimized control performance can be achieved.Eventually,the simulation results demonstrate the effectiveness of the proposed fuzzy adaptive finite-time inverse optimal control scheme.
文摘This paper investigates the problem of cluster synchronization of master-slave complex net-works with time-varying delay via linear and adaptive feedback pinning controls.We need not non-delayed and delayed coupling matrices to be symmetric or irreducible.We have the advantages of using adaptive control method to reduce control gain and pinning control technology to reduce cost.By con-structing Lyapunov function,some sufficient synchronization criteria are established.Finally,numerical examples are employed to illustrate the effectiveness of the proposed approach.
基金Supported by National Key Research and Development Program of China(Grant No.2022YFB3403402)National Natural Science Foundation of China Basic Research Programme for PhD Students(Grant No.524B2049)。
文摘In the field of flexible polishing,the accuracy of contact force control directly affects processing quality and material removal uniformity.However,the complex dynamic contact model and inherent strong hysteresis of pneumatic systems can significantly impact the force control accuracy of pneumatic polishing system end-effectors.To enhance responsiveness and control precision during the flexible polishing process,this study proposes an observer-based fuzzy adaptive control(OBFAC)scheme.To ensure control accuracy under an uncertain dynamic contact model,a fuzzy state observer is designed to estimate unmeasured states,while fuzzy logic approximates the uncertain nonlinear functions in the model to improve control performance.Additionally,the integral barrier Lyapunov function is employed to ensure that all states remain within predefined constraints.The stability of the proposed control scheme is analyzed using the Lyapunov function,and a pneumatic polishing experimental platform is constructed to conduct polishing contact force control experiments under multiple scenarios.Experimental results demonstrate that the proposed OBFAC scheme achieves superior tracking control performance compared to existing control schemes.
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 Key R&D Project of Zhejiang(Grant No.2022C02052)。
文摘Tracking control of tendon-driven manipulators has become a prevalent research area.However,the existence of flexible elastic tendons generates substantial residual vibrations,resulting in difficulties for trajectory tracking control of the manipulator.This paper proposes the radial basis function neural network adaptive hierarchical sliding mode control(RBFNNA-HSMC)method,which combines the dynamic model of the elastic tendon-driven manipulator(ETDM)with radial basis neural network adaptive control and hierarchical sliding mode control technology.The aim is to achieve trajectory tracking control of ETDM even under conditions of model inaccuracy and disturbance.The Lyapunov stability theory demonstrates the stability of the proposed RBFNNA-HSM controller.In order to assess the effectiveness and adaptability of the proposed control method,simulations and experiments were performed on a two-DOF ETDM.The RBFNNA-HSM method shows superior tracking accuracy compared to traditional modelbased HSM control.The experiment shows that the maximum tracking error for ETDM double-joint trajectory tracking is below 2.593×10-3rad and 1.624×10-3rad,respectively.
基金supported by the Natural Science Basic Research Program of Shaanxi with Grant No.2025JC-YBQN-807。
文摘Sliding mode control(SMC)is a well-known robust nonlinear control method with strong robustness and fast response which has been widely used in many applications.This paper introduces the major results of SMC design methods that the authors have achieved in the last decade.Undoubtedly,our results are obtained based on many other researchers'pioneer work in the literature which will not be discussed in detail here.Notably,our development has a main focus on tackling practical issues such that a proposed or enhanced SMC approach is effectively applicable to motion control systems.Issues on sliding function and adaptive gain designs in SMC and their control features will be both discussed in this paper.Those issues comprise fast convergent speed,predefined convergent time,input saturation restriction,chattering reduction,and unknown disturbance suppression.Lastly,conclusion and a few remarks on future research directions are presented.
基金supported in part by the National Key Research and Development Program of China(2023YFB4706400)the National Natural Science Foundation of China(62273112,62073030,62203161)+6 种基金the Guangdong Basic and Applied Basic Research Foundation(2023B1515120018,2023B1515120019)the Open Project of Xiangjiang Laboratory(23XJ03012)the Natural Science Foundation of Hunan Province(2024JJ5087)the Natural Science Foundation of Jiangxi Province(20232BAB212024)the National Research Foundation of Korea funded by the Ministry of Science and ICT,South Korea(IRIS-2023-00207954)the Science and Technology Planning Project of Guangzhou,China(2023A03J0120)the Guangzhou University Research Project(RC2023037)
文摘In this study,we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults.First,an inverse hysteresis dynamics model is introduced,and then the control input is divided into an expected input and an error compensator.Second,a novel adaptive neural network-based control scheme is proposed to cancel the unknown input hysteresis.Subsequently,by modifying the adaptive laws and local control laws,a fault-tolerant control strategy is applied to address uncertain intermittent actuator faults in a flexible manipulator system.Through the direct Lyapunov theory,the proposed scheme allows the state errors to asymptotically converge to a specified interval.Finally,the effectiveness of the proposed scheme is verified through numerical simulations and experiments.
基金supported in part by the National Natural Science Foundation of China(62225306,U2141235,52188102).
文摘Dear Editor,Active magnetic bearings(AMBs)are of considerable interest and significance in smart manufacturing due to their zero-friction and adaptivity to noncontact rotor rotations.This paper proposes an active levitation control algorithm based on adaptive sliding mode control(ASMC)equipped with linear extended state observer(LESO).Sufficient conditions are derived to guarantee the asymptotical stability of the associated closed-loop system.Experiments are conducted on a real AMB-rotor platform to demonstrate the effectiveness and superiority of the proposed algorithm.
基金National Natural Science Foundation of China(62373102)Jiangsu Natural Science Foundation(BK20221455)Anhui Provincial Key Research and Development Project(2022i01020013)。
文摘Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.
文摘A robust Adaptive Discrete-time Sliding Mode Controller (ADSMC) is formulated, and is applied to control the pitch motion of a simulated Flapping-Wing Micro Air Vehicle (FWMAV). There is great potential for FWMAVs to be used as aerial tools to assist with gathering data and surveying environments. Thanks to modern manufacturing and technology, along with an increased comprehension behind the aerodynamics of wing flaps, these vehicles are now a reality, though not without limitations. Given their diminutive size, FWMAVs are susceptible to real-world disturbances, such as wind gusts, and are sensitive to particular variations in their build quality. While external forces such as wind gusts can be reasonably bounded, the unknown variations in the state may be difficult to characterize or bound without affecting performance. To address these problems, an ADSMC is developed. First, the FWMAV model is converted from continuous-time to discrete-time. Second, an ADSMC for the newly discretized FWMAV model is developed. Using this controller, the trajectory tracking performance of the FWMAV is assessed against a traditional discrete sliding mode controller, and is found to have a decreased chattering frequency and decreased control effort for the same task. Therefore, the ADSMC is assessed as the superior controller, despite being completely unaware of the model parameters or wind gust.
