Control Design And Stability Analysis Of Time-Delay Systems Under Multiple Constraints

Time delay is a common phenomenon in many practical systems,such as the signal propagation,biological reactions and physical processes in the network transmission.The stability analysis and controller design of the time delay systems are very important to guarantee the system stability and improve control performance.One can deep understand the time delay impact on system stability by investigating the time delay systems,and how to design the effective control strategies to address the problem caused by time delay,such that the adverse effects is reduced,the response speed and system robustness are improved.This dissertation focuses on the performance optimization problem of mixed time-delay systems under multiple constraint conditions,and investigates the time-delay fuzzy controller design and stability analysis strategy.The objective of this dissertation is to guarantee the stability of time delay system for improving the system response speed,anti interference ability,robustness and optimize system performance.The main research content of this dissertation is given as follows:(1)A dynamic output feedback controller is designed for a class of systems with mixed interval distributed delay and nonlinearity.Firstly,the Takagi-Sugeno(T-S)fuzzy model is employed to approximate the nonlinear system model based on system gain matrices.Secondly,the dynamic output feedback controller is constructed by using the fuzzified measurement output,and a hybrid intermittent feedback control law is designed to adjust the system output dynamically.Finally,the multiple continuous time Lyapunov-Krasovskii functions are constructed by introducing the Leibniz-Newton formula,such that two classes of sufficient stability conditions in the form of LMIs are derived and the closed-loop system is asymptotically stable.(2)A T-S fuzzy dynamic output feedback control scheme is designed for a class of systems with time-varying state delay and external disturbance.Firstly,the appropriate input and output variables are choosen based on the original system model,and the appropriate fuzzy set is defined to approximate the system model.Secondly,based on the T-S fuzzy control theory,the T-S fuzzification method is chosen to map the actual input and output variables onto the controller fuzzy set for designing the T-S fuzzy dynamic output feedback controller.Finally,the sufficient stability conditions for the system are derived by using Shur complement lemma and singular value decomposition method.The closed-loop system is stochastically mean square stable by constructing the multiple discrete time Lyapunov-Krasovskii functions.(3)A T-S fuzzy dynamic output feedback H_∞control strategy with-th Rice channel fading model is proposed for a class of systems with interval distributed delay and sector nonlinearity.Firstly,the T-S fuzzy rules are designed to describe the relationship between input and output based on the dynamic characteristic and system control requirements,and the nonlinear system model is approximated.Secondly,the weighted average inference mechanism is choosen based on the input variables and fuzzy rule library,and the T-S fuzzy dynamic output feedback controller is designed.Thridly,the-th Rice channel fading model is introduced to describe the actual measurement output of system,and the fading channel phenomenon is described clearly in the signal transmission by setting different channel coefficients.Finally,the closed-loop system is exponentially mean square stable and prescribed H_∞performance is guaranteed by constructing the multiple discrete time quadratic Lyapunov-Krasovskii functions.(4)A stochastic discrete time T-S fuzzy dynamic output feedback H_∞control mechanism is proposed for a class of systems with mixed interval distributed delay and stochastic nonlinearity.Firstly,the input variables and fuzzy rules are inferred by choosen the appropriate inference mechanism to obtain the fuzzy outputs for approximating nonlinear system model.Secondly,the T-S fuzzy dynamic output feedback controller is designed by designing fuzzy rule library and selecting appropriate control variables,and the control output is adjusted in real-time based on the system current state to achieve dynamic optimization.Thirdly,the data loss phenomenon of control inputs in signal transmission networks is described by employing stochastic system and Bernoulli probability distribution theory.Finally,the closed-loop system is stochastically finite-time bounded stable and prescribed H_∞performance is guaranteed by constructing multiple discrete time quadratic delay-dependent Lyapunov-Krasovskii functions.(5)A stochastic discrete time T-S fuzzy delay-dependent dynamic output feedback H_∞control framework is proposed for a class of nonlinear systems with time-varying state delay and Lesbergue uncertainties.Firstly,the system plant is approximated by using T-S fuzzy model to capture the system uncertainty and nonlinear characteristic,and the average weighted sum of linear subsystems model equivalent to original system model is presented for system stability analysis and controller design.Secondly,the stochastic T-S fuzzy delay-dependent dynamic output feedback controller is designed by employing delay-dependent parameters and stochastic system theory.Thirdly,the multiply data loss phenomenon from sensor to controller and controller to actuator is described at the same time in signal transmission networks by applying Bernoulli probability distribution theory.Finally,the closed-loop system is exponentially mean square stable and prescribed H_∞performance is guaranteed by constructing the multiple discrete time quadratic delay-dependent and fuzzy-membership-dependent Lyapunov-Krasovskii functions,such that the stability criterion is extended to the bounded set satisfying LMIs constraints.