In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to ...In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.展开更多
Dear Editor,This letter proposes a reinforcement learning-based predictive learning algorithm for unknown continuous-time nonlinear systems with observation loss.Firstly,we construct a temporal nonzero-sum game over p...Dear Editor,This letter proposes a reinforcement learning-based predictive learning algorithm for unknown continuous-time nonlinear systems with observation loss.Firstly,we construct a temporal nonzero-sum game over predictive control input sequences,deriving multiple optimal predictive control input sequences from its solution.展开更多
The bipartite containment control problem for heterogeneous nonlinear multi-agent systems(HNMASs)within multi-group networks under signed digraphs is investigated,where the first-order and second-order nonlinear dynam...The bipartite containment control problem for heterogeneous nonlinear multi-agent systems(HNMASs)within multi-group networks under signed digraphs is investigated,where the first-order and second-order nonlinear dynamic agents belong to distinct groups.Interactions are cooperative-antagonistic within each group and sign-in-degree balanced across the inter-groups.Firstly,a state feedback control protocol is designed to ensure that the trajectories of followers in diverse groups can converge to distinct convex hulls formed by their corresponding leaders,respectively.As an extension,the bipartite control problem with time-variant formation for the multi-agent system(MAS)is also considered,and a corresponding control protocol with formation compensation vectors is given.Finally,in view of Lyapunov stability theory and matrix inequality,the sufficient conditions for realizing the bipartite containment control are obtained,and several simulations are provided to verify the validity of the above methods.展开更多
To address the finite-time tracking control problem for fractional-order nonlinear systems(FONSs) with actuator faults and external disturbance,a novel strategy of the finite-time adaptive fuzzy fault-tolerant control...To address the finite-time tracking control problem for fractional-order nonlinear systems(FONSs) with actuator faults and external disturbance,a novel strategy of the finite-time adaptive fuzzy fault-tolerant controller is presented in this paper by utilizing the finite-time stability theory and fractional-order dynamic surface control scheme combined with backstepping method.A new lemma is developed for analyzing the finite-time stability of FONSs in terms of fractional differential inequality,which modifies some existing results.Fuzzy logic systems are adopted to identify unknown nonlinear characteristics in FONS.In order to compensate for the influence of unknown external disturbance and estimation error for fuzzy logic systems,an auxiliary function is employed to estimate the upper bound of parameters online.Furthermore,a global coordinate transformation is first introduced initially to decouple the fractional-order dynamic system of a specific class of underactuated single-link flexible manipulator systems,thereby transforming it into lower triangular systems.Simulation analyses and experimental results verify the feasibility and effectiveness of finite-time tracking control algorithm.展开更多
Trajectory tracking for nonlinear robotic systems remains a fundamental yet challenging problem in control engineering,particularly when both precision and efficiency must be ensured.Conventional control methods are o...Trajectory tracking for nonlinear robotic systems remains a fundamental yet challenging problem in control engineering,particularly when both precision and efficiency must be ensured.Conventional control methods are often effective for stabilization but may not directly optimize long-term performance.To address this limitation,this study develops an integrated framework that combines optimal control principles with reinforcement learning for a single-link robotic manipulator.The proposed scheme adopts an actor–critic structure,where the critic network approximates the value function associated with the Hamilton–Jacobi–Bellman equation,and the actor network generates near-optimal control signals in real time.This dual adaptation enables the controller to refine its policy online without explicit system knowledge.Stability of the closed-loop system is analyzed through Lyapunov theory,ensuring boundedness of the tracking error.Numerical simulations on the single-link manipulator demonstrate that themethod achieves accurate trajectory followingwhile maintaining lowcontrol effort.The results further showthat the actor–critic learning mechanism accelerates convergence of the control policy compared with conventional optimization-based strategies.This work highlights the potential of reinforcement learning integrated with optimal control for robotic manipulators and provides a foundation for future extensions to more complex multi-degree-of-freedom systems.The proposed controller is further validated in a physics-based virtual Gazebo environment,demonstrating stable adaptation and real-time feasibility.展开更多
Traditional dynamic analysis of mechanical structures,often limited to individual beams or plates,fails to fully capture their dynamic behaviors.In systems where space and mass are constrained,such as the battery supp...Traditional dynamic analysis of mechanical structures,often limited to individual beams or plates,fails to fully capture their dynamic behaviors.In systems where space and mass are constrained,such as the battery support structures in electric aircraft,conventional absorbers and isolators are insufficient for effective vibration control.This study simplifies the battery support structure of electric aircraft as an integrated composite beam consisting of three interconnected beams,and investigated its structural dynamics properties and nonlinear vibration control under thermal conditions caused by battery heat.The nonlinear vibration control is performed using the Nitinol steel wire ropes(Ni Ti-ST),with nonlinear damping properties.The natural frequencies of system are determined using the Rayleigh-Ritz technique.Theoretical results are validated through both Finite Element Method(FEM)and hammer tests.Moreover,the dynamic equations are derived using the Lagrange method and discretized via the Galerkin Truncation Method(GTM).The Harmonic Balance Method(HBM)is used to evaluate the vibration responses of the integrated model,with further verification through the Runge-Kutta Method(RKM).The experiments are conducted to corroborate the theoretical analysis.The results show that the system frequency changes in stages with the increase of the stiffness of the integrated composite beam connection.Especially in the case of varying environments,as the temperature increases,the frequency of system will first increase to a certain maximum value and then gradually decrease.Furthermore,the NiTi-ST effectively reduces vibration in the integrated composite beam,particularly under varying temperatures and external excitations.展开更多
Future manufacturing systems need to cope with frequent changes and disturbances, therefore their control architectures require constant adaptability, agility, stability, self-organization, intelligence, and robustnes...Future manufacturing systems need to cope with frequent changes and disturbances, therefore their control architectures require constant adaptability, agility, stability, self-organization, intelligence, and robustness. Bio-inspired manufacturing system can well satisfy these requirements. For this purpose, by referencing the biological organization structure and the mechanism, a bio-inspired manufacturing cell is presented from a novel view, and then a bio-inspired self-adaptive manufacturing model is established based on the ultra-short feedback mechanism of the neuro-endocrine system. A hio-inspired self-adaptive manufacturing system coordinated model is also established based on the neuro-endocrine-immunity system （NEIS）. Finally, an example based on pheromone communication mechanism indicates that the robustness of the whole manufacturing system is improved by bio-inspired technologies.展开更多
The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and wi...The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.展开更多
The element energy projection （EEP） method for computation of super- convergent resulting in a one-dimensional finite element method （FEM） is successfully used to self-adaptive FEM analysis of various linear probl...The element energy projection （EEP） method for computation of super- convergent resulting in a one-dimensional finite element method （FEM） is successfully used to self-adaptive FEM analysis of various linear problems, based on which this paper presents a substantial extension of the whole set of technology to nonlinear problems. The main idea behind the technology transfer from linear analysis to nonlinear analysis is to use Newton＇s method to linearize nonlinear problems into a series of linear problems so that the EEP formulation and the corresponding adaptive strategy can be directly used without the need for specific super-convergence formulation for nonlinear FEM. As a re- sult, a unified and general self-adaptive algorithm for nonlinear FEM analysis is formed. The proposed algorithm is found to be able to produce satisfactory finite element results with accuracy satisfying the user-preset error tolerances by maximum norm anywhere on the mesh. Taking the nonlinear ordinary differential equation （ODE） of second-order as the model problem, this paper describes the related fundamental idea, the imple- mentation strategy, and the computational algorithm. Representative numerical exam- ples are given to show the efficiency, stability, versatility, and reliability of the proposed approach.展开更多
This paper investigates a multiplayer Pareto game for affine nonlinear stochastic systems disturbed by both external and the internal multiplicative noises.The Pareto cooperative optimal strategies with the H_(∞) con...This paper investigates a multiplayer Pareto game for affine nonlinear stochastic systems disturbed by both external and the internal multiplicative noises.The Pareto cooperative optimal strategies with the H_(∞) constraint are resolved by integrating H_(2)/H_(∞) theory with Pareto game theory.First,a nonlinear stochastic bounded real lemma(SBRL)is derived,explicitly accounting for non-zero initial conditions.Through the analysis of four cross-coupled Hamilton-Jacobi equations(HJEs),we establish necessary and sufficient conditions for the existence of Pareto optimal strategies with the H_(∞) constraint.Secondly,to address the complexity of solving these nonlinear partial differential HJEs,we propose a neural network(NN)framework with synchronous tuning rules for the actor,critic,and disturbance components,based on a reinforcement learning(RL)approach.The designed tuning rules ensure convergence of the actor-critic-disturbance components to the desired values,enabling the realization of robust Pareto control strategies.The convergence of the proposed algorithm is rigorously analyzed using a constructed Lyapunov function for the NN weight errors.Finally,a numerical simulation example is provided to demonstrate the effectiveness of the proposed methods and main results.展开更多
Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectiv...Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.展开更多
This article studies the existence and uniqueness of the mild solution of a family of control systems with a delay that are governed by the nonlinear fractional evolution differential equations in Banach spaces.Moreov...This article studies the existence and uniqueness of the mild solution of a family of control systems with a delay that are governed by the nonlinear fractional evolution differential equations in Banach spaces.Moreover,we establish the controllability of the considered system.To do so,first,we investigate the approximate controllability of the corresponding linear system.Subsequently,we prove the nonlinear system is approximately controllable if the corresponding linear system is approximately controllable.To reach the conclusions,the theory of resolvent operators,the Banach contraction mapping principle,and fixed point theorems are used.While concluding,some examples are given to demonstrate the efficacy of the proposed results.展开更多
In micro electrical discharge machining （micro EDM）, it is difficult for servo controlling the narrow discharge gap with the characters of non-linear and quick change. In this paper, aiming at solving the problems a...In micro electrical discharge machining （micro EDM）, it is difficult for servo controlling the narrow discharge gap with the characters of non-linear and quick change. In this paper, aiming at solving the problems above, a self-adaptive fuzzy controller with formulary rule （SAFCFR） is presented based on the dual feedbacks composed by gap electric signal and discharge-ratio statistics. To ensure the properties of self-optimizing and fast stabilization, the formulary rule was designed with a tuning factor. In addition, the fast-convergence algorithms were introduced to adjust control target center and output scale factor. In this way, the normal discharge ratio can tend to the highest value during micro-EDM process. Experimental results show that the proposed algorithms are effective in improving the servo-control performance. According to the drilling-micro-EDM experiments, the machining efficiency is improved by 20% through applying SAFCFR. Moreover, SAFCFR is a prompt way to optimize parameters of discharge-gap servo control.展开更多
A variable parameter self-adaptive control strategy based on driving condition identification is proposed to take full advantage of the fuel saving potential of the plug-in hybrid electric bus(PHEB).Firstly,the princi...A variable parameter self-adaptive control strategy based on driving condition identification is proposed to take full advantage of the fuel saving potential of the plug-in hybrid electric bus(PHEB).Firstly,the principal component analysis(PCA)and the fuzzy c-means clustering(FCM)algorithm is used to construct the comprehensive driving cycle,congestion driving cycle,urban driving cycle and suburban driving cycle of Chinese urban buses.Secondly,an improved particle swarm optimization(IPSO)algorithm is proposed,and is used to optimize the control parameters of PHEB under different driving cycles,respectively.Then,the variable parameter self-adaptive control strategy based on driving condition identification is given.Finally,for an actual running vehicle,the driving condition is identified by relevance vector machine(RVM),and the corresponding control parameters are selected to control the vehicle.The simulation results show that the fuel consumption of using the variable parameter self-adaptive control strategy is reduced by 4.2% compared with that of the fixed parameter control strategy,and the feasibility of the variable parameter self-adaptive control strategy is verified.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
In this work,a self-healing predictive control method for discrete-time nonlinear systems is presented to ensure the system can be safely operated under abnormal states.First,a robust MPC controller for the normal cas...In this work,a self-healing predictive control method for discrete-time nonlinear systems is presented to ensure the system can be safely operated under abnormal states.First,a robust MPC controller for the normal case is constructed,which can drive the system to the equilibrium point when the closed-loop states are in the predetermined safe set.In this controller,the tubes are built based on the incremental Lyapunov function to tighten nominal constraints.To deal with the infeasible controller when abnormal states occur,a self-healing predictive control method is further proposed to realize self-healing by driving the system towards the safe set.This is achieved by an auxiliary softconstrained recovery mechanism that can solve the constraint violation caused by the abnormal states.By extending the discrete-time robust control barrier function theory,it is proven that the auxiliary problem provides a predictive control barrier bounded function to make the system asymptotically stable towards the safe set.The theoretical properties of robust recursive feasibility and bounded stability are further analyzed.The efficiency of the proposed controller is verified by a numerical simulation of a continuous stirred-tank reactor process.展开更多
Dear Editor,This letter investigates the fuzzy prescribed-time control(PTC)problem for a class of uncertain pure feedback nonlinear systems.Firstly,a novel prescribed-time stability lemma is introduced,which plays a c...Dear Editor,This letter investigates the fuzzy prescribed-time control(PTC)problem for a class of uncertain pure feedback nonlinear systems.Firstly,a novel prescribed-time stability lemma is introduced,which plays a critical role in stability analysis.Unlike existing PTC algorithms,where the nonlinear functions are typically known or satisfy a linear growth condition,our approach does not require such assumptions.To address these unknown factors,fuzzy logic systems(FLSs)are employed.Based on the new prescribed-time stability lemma,it is proven that the controller and all system states converge to the origin within the prescribed time and remain there.Finally,the effectiveness of the proposed algorithm is validated through a simulation example.展开更多
Dear Editor,This letter investigates a low-complexity data-driven adaptive proportional-integral-derivative(APID)control scheme to address the output tracking problem of a class of nonlinear systems.First,the relation...Dear Editor,This letter investigates a low-complexity data-driven adaptive proportional-integral-derivative(APID)control scheme to address the output tracking problem of a class of nonlinear systems.First,the relationship between PID parameters is established to reduce the number of adjustable parameters to one.Then,based on the incremental triangular data model,a data-driven APID tracking control(DD-APIDTC)method is proposed to adjust only one controller parameter and one model parameter online,both of which have clear physical meaning.Subsequently,sufficient conditions are derived for the boundedness of the system tracking error.Finally,simulation results are given to illustrate the effectiveness of the proposed method.展开更多
Dear Editor,This letter deals with the stabilization problem of nonlinear stochastic systems via self-triggered impulsive control(STIC), where the timing of impulsive control actions is not dependent on continuous sta...Dear Editor,This letter deals with the stabilization problem of nonlinear stochastic systems via self-triggered impulsive control(STIC), where the timing of impulsive control actions is not dependent on continuous state monitoring. In contrast to the existing self-triggered control method, novel self-triggered mechanism(STM) is proposed by incorporating a waiting time for stabilizing impulses. This allows for direct prediction of the next impulsive instant.展开更多
The flow control at low Reynolds numbers is one of the most promising technologies in the field of aerodynamics,and it is also an important source of the innovation for novel aircraft.In this study,a new way of nonlin...The flow control at low Reynolds numbers is one of the most promising technologies in the field of aerodynamics,and it is also an important source of the innovation for novel aircraft.In this study,a new way of nonlinear flow control by interaction between two flexible flaps is proposed,and their flow control mechanism is studied employing the self-constructed immersed boundary-lattice Boltzmann-finite element method(IB-LB-FEM).The effects of the difference in material properties and flap length between the two flexible flaps on the nonlinear flow control of the airfoil are discussed.It is suggested that the relationship between the deformation of the two flexible flaps and the evolution of the vortex under the fluid-structure interaction(FSI).It is shown that the upstream flexible flap plays a key role in the flow control of the two flexible flaps.The FSI effect of the upstream flexible flap will change the unsteady flow behind it and affect the deformation of the downstream flexible flap.Two flexible flaps with different material properties and different lengths will change their own FSI characteristics by the induced vortex,effectively suppressing the flow separation on the airfoil’s upper surface.The interaction of two flexible flaps plays an extremely important role in improving the autonomy and adjustability of flow control.The numerical results will provide a theoretical basis and technical guidance for the development and application of a new flap passive control technology.展开更多
基金Supported in part by Natural Science Foundation of Guangxi(2023GXNSFAA026246)in part by the Central Government's Guide to Local Science and Technology Development Fund(GuikeZY23055044)in part by the National Natural Science Foundation of China(62363003)。
文摘In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(62433014,62373287,62573324,62333005,62273255)in part by the International Exchange Program for Graduate Students of Tongji University(4360143306)+3 种基金in part by the Fundamental Research Funds for Central Universities(22120230311)supported by DeutscheForschungsgemeinschaft(DFG,German Research Foundation)under Germany’s Excellence Strategy(EXC 2075390740016,468094890)support by the Stuttgart Center for Simulation Science(SimTech)the International Max Planck Research School for Intelligent Systems(IMPRS-IS)for supporting Y.Xie。
文摘Dear Editor,This letter proposes a reinforcement learning-based predictive learning algorithm for unknown continuous-time nonlinear systems with observation loss.Firstly,we construct a temporal nonzero-sum game over predictive control input sequences,deriving multiple optimal predictive control input sequences from its solution.
基金National Natural Science Foundation of China(No.12071370)。
文摘The bipartite containment control problem for heterogeneous nonlinear multi-agent systems(HNMASs)within multi-group networks under signed digraphs is investigated,where the first-order and second-order nonlinear dynamic agents belong to distinct groups.Interactions are cooperative-antagonistic within each group and sign-in-degree balanced across the inter-groups.Firstly,a state feedback control protocol is designed to ensure that the trajectories of followers in diverse groups can converge to distinct convex hulls formed by their corresponding leaders,respectively.As an extension,the bipartite control problem with time-variant formation for the multi-agent system(MAS)is also considered,and a corresponding control protocol with formation compensation vectors is given.Finally,in view of Lyapunov stability theory and matrix inequality,the sufficient conditions for realizing the bipartite containment control are obtained,and several simulations are provided to verify the validity of the above methods.
基金supported by the National Natural Science Foundation of China(62403340,62303339)Sichuan Science and Technology Program(2026NSFSC1518)+2 种基金China Postdoctoral Science Foundation(CPSF)(2025T180940,2024M762208)Postdoctoral Fellowship Program of CPSF(GZC20231783)Guangxi Key Laboratory of Brain-Inspired Computing and Intelligent Chips(BCIC-24-K2)。
文摘To address the finite-time tracking control problem for fractional-order nonlinear systems(FONSs) with actuator faults and external disturbance,a novel strategy of the finite-time adaptive fuzzy fault-tolerant controller is presented in this paper by utilizing the finite-time stability theory and fractional-order dynamic surface control scheme combined with backstepping method.A new lemma is developed for analyzing the finite-time stability of FONSs in terms of fractional differential inequality,which modifies some existing results.Fuzzy logic systems are adopted to identify unknown nonlinear characteristics in FONS.In order to compensate for the influence of unknown external disturbance and estimation error for fuzzy logic systems,an auxiliary function is employed to estimate the upper bound of parameters online.Furthermore,a global coordinate transformation is first introduced initially to decouple the fractional-order dynamic system of a specific class of underactuated single-link flexible manipulator systems,thereby transforming it into lower triangular systems.Simulation analyses and experimental results verify the feasibility and effectiveness of finite-time tracking control algorithm.
基金supported in part by the National Science and Technology Council under Grant NSTC 114-2221-E-027-104.
文摘Trajectory tracking for nonlinear robotic systems remains a fundamental yet challenging problem in control engineering,particularly when both precision and efficiency must be ensured.Conventional control methods are often effective for stabilization but may not directly optimize long-term performance.To address this limitation,this study develops an integrated framework that combines optimal control principles with reinforcement learning for a single-link robotic manipulator.The proposed scheme adopts an actor–critic structure,where the critic network approximates the value function associated with the Hamilton–Jacobi–Bellman equation,and the actor network generates near-optimal control signals in real time.This dual adaptation enables the controller to refine its policy online without explicit system knowledge.Stability of the closed-loop system is analyzed through Lyapunov theory,ensuring boundedness of the tracking error.Numerical simulations on the single-link manipulator demonstrate that themethod achieves accurate trajectory followingwhile maintaining lowcontrol effort.The results further showthat the actor–critic learning mechanism accelerates convergence of the control policy compared with conventional optimization-based strategies.This work highlights the potential of reinforcement learning integrated with optimal control for robotic manipulators and provides a foundation for future extensions to more complex multi-degree-of-freedom systems.The proposed controller is further validated in a physics-based virtual Gazebo environment,demonstrating stable adaptation and real-time feasibility.
基金supported by the National Natural Science Foundation of China(No.12272240)the Liaoning Revitalization Talents Program,China(No.XLYC2203197)。
文摘Traditional dynamic analysis of mechanical structures,often limited to individual beams or plates,fails to fully capture their dynamic behaviors.In systems where space and mass are constrained,such as the battery support structures in electric aircraft,conventional absorbers and isolators are insufficient for effective vibration control.This study simplifies the battery support structure of electric aircraft as an integrated composite beam consisting of three interconnected beams,and investigated its structural dynamics properties and nonlinear vibration control under thermal conditions caused by battery heat.The nonlinear vibration control is performed using the Nitinol steel wire ropes(Ni Ti-ST),with nonlinear damping properties.The natural frequencies of system are determined using the Rayleigh-Ritz technique.Theoretical results are validated through both Finite Element Method(FEM)and hammer tests.Moreover,the dynamic equations are derived using the Lagrange method and discretized via the Galerkin Truncation Method(GTM).The Harmonic Balance Method(HBM)is used to evaluate the vibration responses of the integrated model,with further verification through the Runge-Kutta Method(RKM).The experiments are conducted to corroborate the theoretical analysis.The results show that the system frequency changes in stages with the increase of the stiffness of the integrated composite beam connection.Especially in the case of varying environments,as the temperature increases,the frequency of system will first increase to a certain maximum value and then gradually decrease.Furthermore,the NiTi-ST effectively reduces vibration in the integrated composite beam,particularly under varying temperatures and external excitations.
基金Supported by the National Natural Science Foundation of China (50505017)Fok Ying Tung Edu-cation Foundation (111056)+1 种基金the Innovative and Excellent Foundation for Doctoral Dissertation of Nanjing University of Aeronautics and Astronautics (BCXJ08-07)the New Century Excellent Talents in University,China (NCET-08)~~
文摘Future manufacturing systems need to cope with frequent changes and disturbances, therefore their control architectures require constant adaptability, agility, stability, self-organization, intelligence, and robustness. Bio-inspired manufacturing system can well satisfy these requirements. For this purpose, by referencing the biological organization structure and the mechanism, a bio-inspired manufacturing cell is presented from a novel view, and then a bio-inspired self-adaptive manufacturing model is established based on the ultra-short feedback mechanism of the neuro-endocrine system. A hio-inspired self-adaptive manufacturing system coordinated model is also established based on the neuro-endocrine-immunity system （NEIS）. Finally, an example based on pheromone communication mechanism indicates that the robustness of the whole manufacturing system is improved by bio-inspired technologies.
基金Project(51090385) supported by the Major Program of National Natural Science Foundation of ChinaProject(2011IB001) supported by Yunnan Provincial Science and Technology Program,China+1 种基金Project(2012DFA70570) supported by the International Science & Technology Cooperation Program of ChinaProject(2011IA004) supported by the Yunnan Provincial International Cooperative Program,China
文摘The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.
基金supported by the National Natural Science Foundation of China(Nos.51378293,51078199,50678093,and 50278046)the Program for Changjiang Scholars and the Innovative Research Team in University of China(No.IRT00736)
文摘The element energy projection （EEP） method for computation of super- convergent resulting in a one-dimensional finite element method （FEM） is successfully used to self-adaptive FEM analysis of various linear problems, based on which this paper presents a substantial extension of the whole set of technology to nonlinear problems. The main idea behind the technology transfer from linear analysis to nonlinear analysis is to use Newton＇s method to linearize nonlinear problems into a series of linear problems so that the EEP formulation and the corresponding adaptive strategy can be directly used without the need for specific super-convergence formulation for nonlinear FEM. As a re- sult, a unified and general self-adaptive algorithm for nonlinear FEM analysis is formed. The proposed algorithm is found to be able to produce satisfactory finite element results with accuracy satisfying the user-preset error tolerances by maximum norm anywhere on the mesh. Taking the nonlinear ordinary differential equation （ODE） of second-order as the model problem, this paper describes the related fundamental idea, the imple- mentation strategy, and the computational algorithm. Representative numerical exam- ples are given to show the efficiency, stability, versatility, and reliability of the proposed approach.
基金supported by the National Natural Science Foundation of China(12426609,62203220,62373229)the Taishan Scholar Project Foundation of Shandong Province(tsqnz20230619,tsqn202408110)+2 种基金the Fundamental Research Foundation of the Central Universities(23Cx06024A)the Natural Science Foundation of Shandong Province(ZR2024QF096)the Outstanding Youth Innovation Team in Shandong Higher Education Institutions(2023KJ061).
文摘This paper investigates a multiplayer Pareto game for affine nonlinear stochastic systems disturbed by both external and the internal multiplicative noises.The Pareto cooperative optimal strategies with the H_(∞) constraint are resolved by integrating H_(2)/H_(∞) theory with Pareto game theory.First,a nonlinear stochastic bounded real lemma(SBRL)is derived,explicitly accounting for non-zero initial conditions.Through the analysis of four cross-coupled Hamilton-Jacobi equations(HJEs),we establish necessary and sufficient conditions for the existence of Pareto optimal strategies with the H_(∞) constraint.Secondly,to address the complexity of solving these nonlinear partial differential HJEs,we propose a neural network(NN)framework with synchronous tuning rules for the actor,critic,and disturbance components,based on a reinforcement learning(RL)approach.The designed tuning rules ensure convergence of the actor-critic-disturbance components to the desired values,enabling the realization of robust Pareto control strategies.The convergence of the proposed algorithm is rigorously analyzed using a constructed Lyapunov function for the NN weight errors.Finally,a numerical simulation example is provided to demonstrate the effectiveness of the proposed methods and main results.
基金supported in part by the National Natural Science Foundation of China(62173255,62188101)Shenzhen Key Laboratory of Control Theory and Intelligent Systems(ZDSYS20220330161800001)
文摘Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.
文摘This article studies the existence and uniqueness of the mild solution of a family of control systems with a delay that are governed by the nonlinear fractional evolution differential equations in Banach spaces.Moreover,we establish the controllability of the considered system.To do so,first,we investigate the approximate controllability of the corresponding linear system.Subsequently,we prove the nonlinear system is approximately controllable if the corresponding linear system is approximately controllable.To reach the conclusions,the theory of resolvent operators,the Banach contraction mapping principle,and fixed point theorems are used.While concluding,some examples are given to demonstrate the efficacy of the proposed results.
基金Supported by the National High Technology Research and Development Program of China （No. 2007AA04Z346） , the National Natural Science Foundation of China （ No. 50905094） and China Postdoctoral Science Foundation （ No. 20080440378, 200902097）.
文摘In micro electrical discharge machining （micro EDM）, it is difficult for servo controlling the narrow discharge gap with the characters of non-linear and quick change. In this paper, aiming at solving the problems above, a self-adaptive fuzzy controller with formulary rule （SAFCFR） is presented based on the dual feedbacks composed by gap electric signal and discharge-ratio statistics. To ensure the properties of self-optimizing and fast stabilization, the formulary rule was designed with a tuning factor. In addition, the fast-convergence algorithms were introduced to adjust control target center and output scale factor. In this way, the normal discharge ratio can tend to the highest value during micro-EDM process. Experimental results show that the proposed algorithms are effective in improving the servo-control performance. According to the drilling-micro-EDM experiments, the machining efficiency is improved by 20% through applying SAFCFR. Moreover, SAFCFR is a prompt way to optimize parameters of discharge-gap servo control.
基金Supported by China Automobile Test Cycle Development Project(CATC2015)
文摘A variable parameter self-adaptive control strategy based on driving condition identification is proposed to take full advantage of the fuel saving potential of the plug-in hybrid electric bus(PHEB).Firstly,the principal component analysis(PCA)and the fuzzy c-means clustering(FCM)algorithm is used to construct the comprehensive driving cycle,congestion driving cycle,urban driving cycle and suburban driving cycle of Chinese urban buses.Secondly,an improved particle swarm optimization(IPSO)algorithm is proposed,and is used to optimize the control parameters of PHEB under different driving cycles,respectively.Then,the variable parameter self-adaptive control strategy based on driving condition identification is given.Finally,for an actual running vehicle,the driving condition is identified by relevance vector machine(RVM),and the corresponding control parameters are selected to control the vehicle.The simulation results show that the fuel consumption of using the variable parameter self-adaptive control strategy is reduced by 4.2% compared with that of the fixed parameter control strategy,and the feasibility of the variable parameter self-adaptive control strategy is verified.
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 in part the National Key Research and Development Program of China(2021YFC2902703)Open Foundation of State Key Laboratory of Process Automation in Mining&Metallurgy/Beijing Key Laboratory of Process Automation in Mining&Metallurgy(BGRIMM-KZSKL-2022-6)the National Natural Science Foundation of China(62173078,61873049).
文摘In this work,a self-healing predictive control method for discrete-time nonlinear systems is presented to ensure the system can be safely operated under abnormal states.First,a robust MPC controller for the normal case is constructed,which can drive the system to the equilibrium point when the closed-loop states are in the predetermined safe set.In this controller,the tubes are built based on the incremental Lyapunov function to tighten nominal constraints.To deal with the infeasible controller when abnormal states occur,a self-healing predictive control method is further proposed to realize self-healing by driving the system towards the safe set.This is achieved by an auxiliary softconstrained recovery mechanism that can solve the constraint violation caused by the abnormal states.By extending the discrete-time robust control barrier function theory,it is proven that the auxiliary problem provides a predictive control barrier bounded function to make the system asymptotically stable towards the safe set.The theoretical properties of robust recursive feasibility and bounded stability are further analyzed.The efficiency of the proposed controller is verified by a numerical simulation of a continuous stirred-tank reactor process.
基金supported by the National Natural Science Foundation of China(U20A20187,U22A2050)the Science Fund of Hebei Province(F2024203134,F2023203100)+3 种基金the Science and Technology Development Grant of Hebei Province(20311803D)Hebei Innovation Capability Improvement Plan project(22567619H)Basic Research Project of Shijiazhuang(241791007A)the China Scholarship Council(CSC 202308130190).
文摘Dear Editor,This letter investigates the fuzzy prescribed-time control(PTC)problem for a class of uncertain pure feedback nonlinear systems.Firstly,a novel prescribed-time stability lemma is introduced,which plays a critical role in stability analysis.Unlike existing PTC algorithms,where the nonlinear functions are typically known or satisfy a linear growth condition,our approach does not require such assumptions.To address these unknown factors,fuzzy logic systems(FLSs)are employed.Based on the new prescribed-time stability lemma,it is proven that the controller and all system states converge to the origin within the prescribed time and remain there.Finally,the effectiveness of the proposed algorithm is validated through a simulation example.
基金supported by the National Natural Science Foundation of China(62173002,62403010,52301408)the Beijing Natural Science Foundation(L241015,4222045)+1 种基金the Yuxiu Innovation Project of NCUT(2024NCUTYXCX111)the China Postdoctoral Science Foundation(2024M750192).
文摘Dear Editor,This letter investigates a low-complexity data-driven adaptive proportional-integral-derivative(APID)control scheme to address the output tracking problem of a class of nonlinear systems.First,the relationship between PID parameters is established to reduce the number of adjustable parameters to one.Then,based on the incremental triangular data model,a data-driven APID tracking control(DD-APIDTC)method is proposed to adjust only one controller parameter and one model parameter online,both of which have clear physical meaning.Subsequently,sufficient conditions are derived for the boundedness of the system tracking error.Finally,simulation results are given to illustrate the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(62403393,12202058,62103118)the China Postdoctoral Science Foundation(2021T140160,2023 T160051)the Natural Science Foundation of Chongqing(CSTB 2023NSCQ-MSX0152)
文摘Dear Editor,This letter deals with the stabilization problem of nonlinear stochastic systems via self-triggered impulsive control(STIC), where the timing of impulsive control actions is not dependent on continuous state monitoring. In contrast to the existing self-triggered control method, novel self-triggered mechanism(STM) is proposed by incorporating a waiting time for stabilizing impulses. This allows for direct prediction of the next impulsive instant.
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.92371201,52192633,11872293,and 92152301)the Natural Science Basic Research Program of Shaanxi(Grant Nos.2024JC-YBQN-0008,and 2022JC-03)+1 种基金Shaanxi Key Research and Development Program(Grant No.2022ZDLGY02-07)the Joint Natural Science Foundation of China with Guangdong Province for TianHe-II Supercomputer Resources,and the Research Start-up Foundation of Xi’an University of Science and Technology for the High-Level Talent.
文摘The flow control at low Reynolds numbers is one of the most promising technologies in the field of aerodynamics,and it is also an important source of the innovation for novel aircraft.In this study,a new way of nonlinear flow control by interaction between two flexible flaps is proposed,and their flow control mechanism is studied employing the self-constructed immersed boundary-lattice Boltzmann-finite element method(IB-LB-FEM).The effects of the difference in material properties and flap length between the two flexible flaps on the nonlinear flow control of the airfoil are discussed.It is suggested that the relationship between the deformation of the two flexible flaps and the evolution of the vortex under the fluid-structure interaction(FSI).It is shown that the upstream flexible flap plays a key role in the flow control of the two flexible flaps.The FSI effect of the upstream flexible flap will change the unsteady flow behind it and affect the deformation of the downstream flexible flap.Two flexible flaps with different material properties and different lengths will change their own FSI characteristics by the induced vortex,effectively suppressing the flow separation on the airfoil’s upper surface.The interaction of two flexible flaps plays an extremely important role in improving the autonomy and adjustability of flow control.The numerical results will provide a theoretical basis and technical guidance for the development and application of a new flap passive control technology.
