This paper investigates adaptive containment control for a class of fractional-order multi-agent systems(FOMASs)with time-varying parameters and disturbances.By using the bounded estimation method,the difficulty gener...This paper investigates adaptive containment control for a class of fractional-order multi-agent systems(FOMASs)with time-varying parameters and disturbances.By using the bounded estimation method,the difficulty generated by the timevarying parameters and disturbances is overcome.The command filter is introduced to solve the complexity problem inherent in adaptive backstepping control.Meanwhile,in order to eliminate the effect of filter errors,a novel distributed error compensating scheme is constructed,in which only the local information from the neighbor agents is utilized.Then,a distributed adaptive containment control scheme for FOMASs is developed based on backstepping to guarantee that the outputs of all the followers are steered to the convex hull spanned by the leaders.Based on the extension of Barbalat's lemma to fractional-order integrals,it can be proven that the containment errors and the compensating signals have asymptotic convergence.Finally,three simulation examples are given to show the feasibility and effectiveness of the proposed control method.展开更多
A dynamics-based adaptive control approach is proposed for a planar dual-arm space robot in the presence of closed-loop constraints and uncertain inertial parameters of the payload. The controller is capable of contro...A dynamics-based adaptive control approach is proposed for a planar dual-arm space robot in the presence of closed-loop constraints and uncertain inertial parameters of the payload. The controller is capable of controlling the po- sition and attitude of both the satellite base and the payload grasped by the manipulator end effectors. The equations of motion in reduced-order form for the constrained system are derived by incorporating the constraint equations in terms of accelerations into Kane＇s equations of the unconstrained system. Model analysis shows that the resulting equations perfectly meet the requirement of adaptive controller design. Consequently, by using an indirect approach, an adaptive control scheme is proposed to accomplish position/attitude trajectory tracking control with the uncertain parameters be- ing estimated on-line. The actuator redundancy due to the closed-loop constraints is utilized to minimize a weighted norm of the joint torques. Global asymptotic stability is proven by using Lyapunov＇s method, and simulation results are also presented to demonstrate the effectiveness of the proposed approach.展开更多
The precise control of turbofan engines thrust is an important guarantee for an aircraft to obtain good flight performance and a challenge due to complex nonlinear dynamics of engines and time-varying parameters. The ...The precise control of turbofan engines thrust is an important guarantee for an aircraft to obtain good flight performance and a challenge due to complex nonlinear dynamics of engines and time-varying parameters. The main difficulties lie in the following two aspects. Firstly, it is hard to obtain an accurate kinetic model for the turbofan engine. Secondly, some model parameters often change in different flight conditions and states and even fluctuate sharply in some cases. These variable parameters bring huge challenge for the turbofan engine control. To solve the turbofan engine control problem, this paper presents a non-affine parameter-dependent Linear Parameter Varying(LPV) model-based adaptive control approach. In this approach, polynomial-based LPV modeling method is firstly employed to obtain the basis matrices, and then the Radial Basis Function Neural Networks(RBFNN) is introduced for the online estimation of the non-affine model parameters to improve the simulation performance. LPV model-based Linear Matrix Inequality(LMI) control method is applied to derive the control law. A robust control term is introduced to fix the estimation error of the nonlinear time-varying model parameters for better control performance. Finally, the Lyapunov stability analysis is performed to ensure the asymptotical convergence of the closed loop system. The simulation results show that the states of the engine can change smoothly and the thrust of the engine can accurately follow the desired trajectory, indicating that the proposed control approach is effective. The contribution of this work lies in the combination of linear system control and nonlinear system control methods to design an effective controller for the turbofan engine and to provide a new way for turbofan engine control research.展开更多
An adaptive actuator failure compensation control scheme is developed using an indirect adaptive control method,by calculating the controller parameters from adaptive estimates of system parameters and actuator failur...An adaptive actuator failure compensation control scheme is developed using an indirect adaptive control method,by calculating the controller parameters from adaptive estimates of system parameters and actuator failure parameters.A key technical issue is how to deal with the actuator failure uncertainties such as failure pattern,time and values.A complete parametrization covering all possible failures is used to solve this issue for adaptive parameter estimation.A simultaneous mapping from the estimated system/failure parameters to the controller parameters is employed to make the control system capable of ensuring the desired system performance under failures,which is verified by simulation results.展开更多
Based on Lyapunov stability theory, a novel adaptive controller is designed for a class of chaotic systems .The parameters identification and synchronization of chaotic systems can be carried out simultaneously. The c...Based on Lyapunov stability theory, a novel adaptive controller is designed for a class of chaotic systems .The parameters identification and synchronization of chaotic systems can be carried out simultaneously. The controller and the updating law of parameters identification are directly constructed by analytic formula. Simulation results with Chen’s system and R?ssler system show the effectiveness of the proposed controller.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
This paper investigates the adaptive trajectory tracking control problem and the unknown parameter identification problem of a class of rotor-missiles with parametric system uncertainties.First,considering the uncerta...This paper investigates the adaptive trajectory tracking control problem and the unknown parameter identification problem of a class of rotor-missiles with parametric system uncertainties.First,considering the uncertainty of structural and aerodynamic parameters,the six-degree-of-freedom(6Do F) nonlinear equations describing the position and attitude dynamics of the rotor-missile are established,respectively,in the inertial and body-fixed reference frames.Next,a hierarchical adaptive trajectory tracking controller that can guarantee closed-loop stability is proposed according to the cascade characteristics of the 6Do F dynamics.Then,a memory-augmented update rule of unknown parameters is proposed by integrating all historical data of the regression matrix.As long as the finitely excited condition is satisfied,the precise identification of unknown parameters can be achieved.Finally,the validity of the proposed trajectory tracking controller and the parameter identification method is proved through Lyapunov stability theory and numerical simulations.展开更多
A parameter adaptive control approach was applied to a kind of financial chaotic systems.According to Lyapunov stability theorem,synchronization of two financial chaotic systems with different certain parameters or th...A parameter adaptive control approach was applied to a kind of financial chaotic systems.According to Lyapunov stability theorem,synchronization of two financial chaotic systems with different certain parameters or the same uncertain parameters were implemented through designing proper control functions and using parameters self-adaptive control principle.The sufficient synchronization conditions of the two financial systems were obtained.Under the situation of the same uncertain parameters,the synchronization system has simpler controller and better performance.Numerical simulations show the effectiveness of the method.展开更多
Based on Lyapunov stability theory, an adaptive controller is designed for a class of chaotic systems. Globally exponential synchronization and parameter regulation for couple chaotic systems can be carried out simult...Based on Lyapunov stability theory, an adaptive controller is designed for a class of chaotic systems. Globally exponential synchronization and parameter regulation for couple chaotic systems can be carried out simultaneously. The controller and the regulating law of parameters are directly constructed by analytic formula. Simulation results with some chaotic systems show the effectiveness of the proposed controller.展开更多
Dear Editor,This letter is concerned with a coordinated path following control method for multiple unmanned underwater vehicles(UUVs)to carry out maritime search and rescue(MSR)missions.The kinetic model parameters of...Dear Editor,This letter is concerned with a coordinated path following control method for multiple unmanned underwater vehicles(UUVs)to carry out maritime search and rescue(MSR)missions.The kinetic model parameters of each UUV is totally unknown.Firstly,a kinematic control law is constructed by designing a vertical line-of-sight(LOS)guidance scheme.展开更多
Control parameters of original differential evolution （DE） are kept fixed throughout the entire evolutionary process. However, it is not an easy task to properly set control parameters in DE for different optiinizat...Control parameters of original differential evolution （DE） are kept fixed throughout the entire evolutionary process. However, it is not an easy task to properly set control parameters in DE for different optiinization problems. According to the relative position of two different individual vectors selected to generate a difference vector in the searching place, a self-adapting strategy for the scale factor F of the difference vector is proposed. In terms of the convergence status of the target vector in the current population, a self-adapting crossover probability constant CR strategy is proposed. Therefore, good target vectors have a lower CFI while worse target vectors have a large CFI. At the same time, the mutation operator is modified to improve the convergence speed. The performance of these proposed approaches are studied with the use of some benchmark problems and applied to the trajectory planning of a three-joint redundant manipulator. Finally, the experiment results show that the proposed approaches can greatly improve robustness and convergence speed.展开更多
This paper studies the parameter identification problem of chaotic systems. Adaptive identification laws are pro- posed to estimate the parameters of uncertain chaotic systems. It proves that the asymptotical identifi...This paper studies the parameter identification problem of chaotic systems. Adaptive identification laws are pro- posed to estimate the parameters of uncertain chaotic systems. It proves that the asymptotical identification is ensured by a persistently exciting condition. Additionally, the method can be applied to identify the uncertain parameters with any number. Numerical simulations are given to validate the theoretical analysis.展开更多
In this paper, an adaptive control scheme is developed to study the hybrid synchronization behavior between two identical and different hyperchaotic systems with unknown parameters. This adaptive hybrid synchronizatio...In this paper, an adaptive control scheme is developed to study the hybrid synchronization behavior between two identical and different hyperchaotic systems with unknown parameters. This adaptive hybrid synchronization controller is designed based on Lyapunov stability theory and an analytic expression of the controller with its adaptive laws of parameters is shown. The adaptive hybrid synchronization between two identical systems (hyperchaotic Chen system) and different systems (hyperchaotic Lorenz and hyperchaotic systems) are taken as two illustrative examples to show the effectiveness of the proposed method. Theoretical analysis and numerical simulations are shown to verify the results.展开更多
The adaptive H_∞ control problem of multi-machine power system in the case of disturbances and uncertain parameters is discussed,based on a Hamiltonian model.Considered the effect of time delay during control and tra...The adaptive H_∞ control problem of multi-machine power system in the case of disturbances and uncertain parameters is discussed,based on a Hamiltonian model.Considered the effect of time delay during control and transmission,a Hamilton model with control time delay is established.Lyapunov-Krasovskii function is selected,and a controller which makes the system asymptotically stable is got.The controller not only achieves the stability control for nonlinear systems with time delay,but also has the ability to suppress the external disturbances and adaptive ability to system parameter perturbation.The simulation results show the effect of the controller.展开更多
Dynamic impacts such as wind and earthquakes cause loss of life and economic damage.To ensure safety against these effects,various measures have been taken from past to present and solutions have been developed using ...Dynamic impacts such as wind and earthquakes cause loss of life and economic damage.To ensure safety against these effects,various measures have been taken from past to present and solutions have been developed using different technologies.Tall buildings are more susceptible to vibrations such as wind and earthquakes.Therefore,vibration control has become an important issue in civil engineering.This study optimizes tuned mass damper inerter(TMDI)using far-fault ground motion records.This study derives the optimum parameters of TMDI using the Adaptive Harmony Search algorithm.Structure displacement and total acceleration against earthquake load are analyzed to assess the performance of the TMDI system.The effect of the inerter when connected to different floors is observed,and the results are compared to the conventional tuned mass damper(TMD).It is indicated that the case of connecting the inerter force to the 5th floor gives better results.As a result,TMD and TMDI systems reduce the displacement by 21.87%and 25.45%,respectively,and the total acceleration by 25.45%and 19.59%,respectively.These percentage reductions indicated that the structure resilience against dynamic loads can be increased using control systems.展开更多
This paper proposes a new type of nonlinear controllers and a large phase angle allowance design method based on the multi-objective optimal control system. With the proposed method, the performance of the system beco...This paper proposes a new type of nonlinear controllers and a large phase angle allowance design method based on the multi-objective optimal control system. With the proposed method, the performance of the system becomes better than that of the original system. Then, an example of the radar servo system is designed with a large phase angle allowance multi-objective optimal design method. Finally, the performance based on computer simulation demonstrates that the multi-objective optimal system is superior to linear optimal systems.展开更多
This paper proposes an adaptive discrete finite-time synergetic control （ADFTSC） scheme based on a multi-rate sensor fusion estimator for flexible-joint mechanical systems in the presence of unmeasured states and dy...This paper proposes an adaptive discrete finite-time synergetic control （ADFTSC） scheme based on a multi-rate sensor fusion estimator for flexible-joint mechanical systems in the presence of unmeasured states and dynamic uncertainties. Multi-rate sensors are employed to observe the system states which cannot be directly obtained by encoders due to the existence of joint flexibilities. By using an extended Kalman filter （EKF）, the finite-time synergetic controller is designed based on a sensor fusion estimator which estimates states and parameters of the mechanical system with multi-rate measurements. The proposed controller can guarantee the finite-time convergence of tracking errors by the theoretical derivation. Simulation and experimental studies are included to validate the effectiveness of the proposed approach.展开更多
This paper employs a multi-parameter multi-step chaos control method, which is built up on the OGY method, to stabilize desirable UPOs of a gear system with elastomeric web as a high-dimensional and non-hyperbolic cha...This paper employs a multi-parameter multi-step chaos control method, which is built up on the OGY method, to stabilize desirable UPOs of a gear system with elastomeric web as a high-dimensional and non-hyperbolic chaotic system, and the analyses are carried out. Three types of relations between components of a certain control parameter combination are defined in a certain control process. Special emphasis is put on the comparison of control efficiencies of the multi-parameter multi-step method and single-parameter multi-step method. The numerical experiments show the ability to switch between different orbits and the method can be a good chaos control alternative since it provides a more effective UPOs stabilization of high-dimensional and non-hyperbolic chaotic systems than the single-parameter chaos control, and according to the relation between components of each parameter combination, the best combination for chaos control in a certain UPO stabilization process are obtained.展开更多
基金National Key R&D Program of China(2018YFA0702200)National Natural Science Foundation of China(61627809,62173080)Liaoning Revitalization Talents Program(XLYC1801005)。
文摘This paper investigates adaptive containment control for a class of fractional-order multi-agent systems(FOMASs)with time-varying parameters and disturbances.By using the bounded estimation method,the difficulty generated by the timevarying parameters and disturbances is overcome.The command filter is introduced to solve the complexity problem inherent in adaptive backstepping control.Meanwhile,in order to eliminate the effect of filter errors,a novel distributed error compensating scheme is constructed,in which only the local information from the neighbor agents is utilized.Then,a distributed adaptive containment control scheme for FOMASs is developed based on backstepping to guarantee that the outputs of all the followers are steered to the convex hull spanned by the leaders.Based on the extension of Barbalat's lemma to fractional-order integrals,it can be proven that the containment errors and the compensating signals have asymptotic convergence.Finally,three simulation examples are given to show the feasibility and effectiveness of the proposed control method.
基金supported by the National Natural Science Foundation of China(11272027)
文摘A dynamics-based adaptive control approach is proposed for a planar dual-arm space robot in the presence of closed-loop constraints and uncertain inertial parameters of the payload. The controller is capable of controlling the po- sition and attitude of both the satellite base and the payload grasped by the manipulator end effectors. The equations of motion in reduced-order form for the constrained system are derived by incorporating the constraint equations in terms of accelerations into Kane＇s equations of the unconstrained system. Model analysis shows that the resulting equations perfectly meet the requirement of adaptive controller design. Consequently, by using an indirect approach, an adaptive control scheme is proposed to accomplish position/attitude trajectory tracking control with the uncertain parameters be- ing estimated on-line. The actuator redundancy due to the closed-loop constraints is utilized to minimize a weighted norm of the joint torques. Global asymptotic stability is proven by using Lyapunov＇s method, and simulation results are also presented to demonstrate the effectiveness of the proposed approach.
基金supported by the National Natural Science Foundation of China(No.51766011)the Aeronautical Science Foundation of China(No.2014ZB56002)
文摘The precise control of turbofan engines thrust is an important guarantee for an aircraft to obtain good flight performance and a challenge due to complex nonlinear dynamics of engines and time-varying parameters. The main difficulties lie in the following two aspects. Firstly, it is hard to obtain an accurate kinetic model for the turbofan engine. Secondly, some model parameters often change in different flight conditions and states and even fluctuate sharply in some cases. These variable parameters bring huge challenge for the turbofan engine control. To solve the turbofan engine control problem, this paper presents a non-affine parameter-dependent Linear Parameter Varying(LPV) model-based adaptive control approach. In this approach, polynomial-based LPV modeling method is firstly employed to obtain the basis matrices, and then the Radial Basis Function Neural Networks(RBFNN) is introduced for the online estimation of the non-affine model parameters to improve the simulation performance. LPV model-based Linear Matrix Inequality(LMI) control method is applied to derive the control law. A robust control term is introduced to fix the estimation error of the nonlinear time-varying model parameters for better control performance. Finally, the Lyapunov stability analysis is performed to ensure the asymptotical convergence of the closed loop system. The simulation results show that the states of the engine can change smoothly and the thrust of the engine can accurately follow the desired trajectory, indicating that the proposed control approach is effective. The contribution of this work lies in the combination of linear system control and nonlinear system control methods to design an effective controller for the turbofan engine and to provide a new way for turbofan engine control research.
基金supported by the US National Science Foundation (ECS0601475)the National Natural Science Foundation of China (60904042)
文摘An adaptive actuator failure compensation control scheme is developed using an indirect adaptive control method,by calculating the controller parameters from adaptive estimates of system parameters and actuator failure parameters.A key technical issue is how to deal with the actuator failure uncertainties such as failure pattern,time and values.A complete parametrization covering all possible failures is used to solve this issue for adaptive parameter estimation.A simultaneous mapping from the estimated system/failure parameters to the controller parameters is employed to make the control system capable of ensuring the desired system performance under failures,which is verified by simulation results.
基金Supported by National Natural Science Foundation of China (No. 60074008, 60274007).
文摘Based on Lyapunov stability theory, a novel adaptive controller is designed for a class of chaotic systems .The parameters identification and synchronization of chaotic systems can be carried out simultaneously. The controller and the updating law of parameters identification are directly constructed by analytic formula. Simulation results with Chen’s system and R?ssler system show the effectiveness of the proposed controller.
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.
基金partially supported by the Natural Science Foundation of China (Grant Nos.62103052,52272358)partially supported by the Beijing Institute of Technology Research Fund Program for Young Scholars。
文摘This paper investigates the adaptive trajectory tracking control problem and the unknown parameter identification problem of a class of rotor-missiles with parametric system uncertainties.First,considering the uncertainty of structural and aerodynamic parameters,the six-degree-of-freedom(6Do F) nonlinear equations describing the position and attitude dynamics of the rotor-missile are established,respectively,in the inertial and body-fixed reference frames.Next,a hierarchical adaptive trajectory tracking controller that can guarantee closed-loop stability is proposed according to the cascade characteristics of the 6Do F dynamics.Then,a memory-augmented update rule of unknown parameters is proposed by integrating all historical data of the regression matrix.As long as the finitely excited condition is satisfied,the precise identification of unknown parameters can be achieved.Finally,the validity of the proposed trajectory tracking controller and the parameter identification method is proved through Lyapunov stability theory and numerical simulations.
基金supported by Doctor Fund Item of Chongqing University of Posts and Telecommunications granted A2006-85 and Science Fund Item of Chongqing teaching committee granted KJ060506the scienceand technology research program of the municipal education committee of chongqing of granted KJ080524
文摘A parameter adaptive control approach was applied to a kind of financial chaotic systems.According to Lyapunov stability theorem,synchronization of two financial chaotic systems with different certain parameters or the same uncertain parameters were implemented through designing proper control functions and using parameters self-adaptive control principle.The sufficient synchronization conditions of the two financial systems were obtained.Under the situation of the same uncertain parameters,the synchronization system has simpler controller and better performance.Numerical simulations show the effectiveness of the method.
基金Supported by the National Natural Science Foundation of China (No. 60474011) Foundation of Yong Bone Teacher of Henan Province (No. 2004240).
文摘Based on Lyapunov stability theory, an adaptive controller is designed for a class of chaotic systems. Globally exponential synchronization and parameter regulation for couple chaotic systems can be carried out simultaneously. The controller and the regulating law of parameters are directly constructed by analytic formula. Simulation results with some chaotic systems show the effectiveness of the proposed controller.
基金supported by the National Science and Technology Major Project(2022ZD0119902)the Doctoral Scientific Research Foundation of Liaoning Province(2023-BS-077)+2 种基金the Postdoctoral Research Foundation of China(2024M751980)the Open Project of State Key Laboratory of Maritime Technology and Safety(SKLMTA-DMU2024Y3)Bolian Research Funds of Dalian Maritime University/Fundamental Research Funds for the Central Universities(3132023616).
文摘Dear Editor,This letter is concerned with a coordinated path following control method for multiple unmanned underwater vehicles(UUVs)to carry out maritime search and rescue(MSR)missions.The kinetic model parameters of each UUV is totally unknown.Firstly,a kinematic control law is constructed by designing a vertical line-of-sight(LOS)guidance scheme.
基金This work was supported by the National Natural Science Foundation of China(No.60375001)the High School Doctoral Foundation of China(NO.20030532004).
文摘Control parameters of original differential evolution （DE） are kept fixed throughout the entire evolutionary process. However, it is not an easy task to properly set control parameters in DE for different optiinization problems. According to the relative position of two different individual vectors selected to generate a difference vector in the searching place, a self-adapting strategy for the scale factor F of the difference vector is proposed. In terms of the convergence status of the target vector in the current population, a self-adapting crossover probability constant CR strategy is proposed. Therefore, good target vectors have a lower CFI while worse target vectors have a large CFI. At the same time, the mutation operator is modified to improve the convergence speed. The performance of these proposed approaches are studied with the use of some benchmark problems and applied to the trajectory planning of a three-joint redundant manipulator. Finally, the experiment results show that the proposed approaches can greatly improve robustness and convergence speed.
基金supported by the National Natural Science Foundation of China(61374054,61203007)Natural Science Foundation Research Projection of Shaanxi Province(2013JQ8038).
基金Project supported in part by National Natural Science Foundation of China (Grant Nos. 11047114 and 60974081)in part by the Key Project of Chinese Ministry of Education (Grant No. 210141)
文摘This paper studies the parameter identification problem of chaotic systems. Adaptive identification laws are pro- posed to estimate the parameters of uncertain chaotic systems. It proves that the asymptotical identification is ensured by a persistently exciting condition. Additionally, the method can be applied to identify the uncertain parameters with any number. Numerical simulations are given to validate the theoretical analysis.
文摘In this paper, an adaptive control scheme is developed to study the hybrid synchronization behavior between two identical and different hyperchaotic systems with unknown parameters. This adaptive hybrid synchronization controller is designed based on Lyapunov stability theory and an analytic expression of the controller with its adaptive laws of parameters is shown. The adaptive hybrid synchronization between two identical systems (hyperchaotic Chen system) and different systems (hyperchaotic Lorenz and hyperchaotic systems) are taken as two illustrative examples to show the effectiveness of the proposed method. Theoretical analysis and numerical simulations are shown to verify the results.
基金Sponsored by the Natural Science Foundation of Hebei Province,China(Grant No.F2016203006)
文摘The adaptive H_∞ control problem of multi-machine power system in the case of disturbances and uncertain parameters is discussed,based on a Hamiltonian model.Considered the effect of time delay during control and transmission,a Hamilton model with control time delay is established.Lyapunov-Krasovskii function is selected,and a controller which makes the system asymptotically stable is got.The controller not only achieves the stability control for nonlinear systems with time delay,but also has the ability to suppress the external disturbances and adaptive ability to system parameter perturbation.The simulation results show the effect of the controller.
基金supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP)and the Ministry of Trade,Industry&Energy,Republic of Korea (RS-2024-00441420RS-2024-00442817).
文摘Dynamic impacts such as wind and earthquakes cause loss of life and economic damage.To ensure safety against these effects,various measures have been taken from past to present and solutions have been developed using different technologies.Tall buildings are more susceptible to vibrations such as wind and earthquakes.Therefore,vibration control has become an important issue in civil engineering.This study optimizes tuned mass damper inerter(TMDI)using far-fault ground motion records.This study derives the optimum parameters of TMDI using the Adaptive Harmony Search algorithm.Structure displacement and total acceleration against earthquake load are analyzed to assess the performance of the TMDI system.The effect of the inerter when connected to different floors is observed,and the results are compared to the conventional tuned mass damper(TMD).It is indicated that the case of connecting the inerter force to the 5th floor gives better results.As a result,TMD and TMDI systems reduce the displacement by 21.87%and 25.45%,respectively,and the total acceleration by 25.45%and 19.59%,respectively.These percentage reductions indicated that the structure resilience against dynamic loads can be increased using control systems.
基金partly supported by the Natural Science Foundation of Guangdong (No.06023131)
文摘This paper proposes a new type of nonlinear controllers and a large phase angle allowance design method based on the multi-objective optimal control system. With the proposed method, the performance of the system becomes better than that of the original system. Then, an example of the radar servo system is designed with a large phase angle allowance multi-objective optimal design method. Finally, the performance based on computer simulation demonstrates that the multi-objective optimal system is superior to linear optimal systems.
基金Project supported by the National Natural Science Foundation of China (Grant Nos.61273150 and 60974046)the Research Fund for the Doctoral Program of Higher Education of China (Grant No.20121101110029)
文摘This paper proposes an adaptive discrete finite-time synergetic control （ADFTSC） scheme based on a multi-rate sensor fusion estimator for flexible-joint mechanical systems in the presence of unmeasured states and dynamic uncertainties. Multi-rate sensors are employed to observe the system states which cannot be directly obtained by encoders due to the existence of joint flexibilities. By using an extended Kalman filter （EKF）, the finite-time synergetic controller is designed based on a sensor fusion estimator which estimates states and parameters of the mechanical system with multi-rate measurements. The proposed controller can guarantee the finite-time convergence of tracking errors by the theoretical derivation. Simulation and experimental studies are included to validate the effectiveness of the proposed approach.
基金Sponsored by the National High Technology Research and Development Program of China(Grant No.2009AA04Z404)
文摘This paper employs a multi-parameter multi-step chaos control method, which is built up on the OGY method, to stabilize desirable UPOs of a gear system with elastomeric web as a high-dimensional and non-hyperbolic chaotic system, and the analyses are carried out. Three types of relations between components of a certain control parameter combination are defined in a certain control process. Special emphasis is put on the comparison of control efficiencies of the multi-parameter multi-step method and single-parameter multi-step method. The numerical experiments show the ability to switch between different orbits and the method can be a good chaos control alternative since it provides a more effective UPOs stabilization of high-dimensional and non-hyperbolic chaotic systems than the single-parameter chaos control, and according to the relation between components of each parameter combination, the best combination for chaos control in a certain UPO stabilization process are obtained.
