| The control performnace of the system is not only related to the controlled object itself,but also affected by the physical characteristics of the components such as actuators in the execution loop.Actuators are often constrainted by a variety of nonlinear characteristics,which yield large gaps between the input and output of the actuator.If these actuator constraints are not taken into account,the stability of the system and the control accuracy of the controller will be seriously degraded.Actuator constraints are often nonlinear and pose some challenges to the controller design.Moreover,actuators may malfunction during operation,and these failures may even cause instability of the controlled system.In addition,the controlled object is also affected by the external working environment and the modeling error of the system itself,which makes the system uncertain and nonlinear.Therefore,it is of theoretical and practical significance to investigate the control problems of the nonlinear systems with dead zones or actuator failures.In this paper,fuzzy logic systems are used as the approximators of the unknown nonlinear functions,and by combining with backstepping technique,adaptive control and dynamic surface control technology,the adaptive fuzzy control problems of several kinds of nonlinear systems are solved:(1)The adaptive fuzzy dynamic surface control problem for uncertain nonlinear systems with fuzzy dead zones is incestigated.The fuzzy value slope of the dead zone is defuzzified by employing a center-of-gravity defuzzification method.Firstly,an effective adaptive fuzzy controller is designed for a class of single input and signle output strict-feedback nonlinear systems with fuzzy dead zones,unmodeled dynamics and unknown control gain functions.At each step of the controller design,a fuzzy logic system is constructed to approximate the auxiliary intermediate control signal.Then,the adaptive fuzzy tracking control problem for multi-input multi-output nonlinear systems with fuzzy dead zones is investigated,and the controller is designed for each order subsystem whether the dead zone slope is a certain value or a fuzzy value.For the aforementioned two types of systems,dynamic surface control technology is employed to avoid the problem of "explosion of complexity" caused by the derivation of virtual control signal,multi-order derivation and system complexity.The proposed control scheme guarantees that the system output can track the given reference signal well and all the signals in the closed-loop system are bounded.(2)The adaptive fuzzy tracking control problem for nonlinear systems with dead zone outputs is investigated.Firstly,the tracking control problem for a class of pure-feedback stochastic nonlinear systems with dead zone outputs is considered.By applying the mean-value theorem,the considered non-affine system is transformed into an affine nonlinear system.By introducing the properties of Nussbaum function,an auxiliary virtual controller is designed to solve the problem caused by output nonlinearity.By combining with backstepping technology,an effective controller is designed for the considered nonlinear systems.The proposed control scheme not only guarantees better tracking performance of the systems but also ensures that all signals of the closed-loop system are bounded in probability.Then,the prescribed performance adaptive control problem for a class of nonstrict-feedback nonlinear systems with dead zone outputs is researched.In oeder to ensure that the tracking error of the system converges to a limited area,the performance function is designed to enable the system to meet the requirements of both transient performance and steady-state performance.The proposed control scheme not only guarantees the boundedness of all signals in the closed-loop system but also ensures that the tracking error is limited to a predetermined range.(3)The adaptive fuzzy control problem for a class of strict-feedback nonlinear systems with actuator failures,unmodeled dynamics and immeasurable states is investigated.Actuator failures include both lock-in-place fault models and loss of effectiveness fault models.By introducing input-driven filter,the problem of immeasurable system states is solved.By emlopying backstepping technique and combining with the small-gain theorem and input-state practical stable theory,an effective adaptive fuzzy fault-tolerant controller is designed.The proposed control strategy guarantees that the closed-loop system is input-state practical stable even in the case of with the actuator faults.(4)The adaptive fuzzy fault-tolerant control problem for nonstrict-feedback nonlinear systems is investigated.Firstly,an adaptive fuzzy fault-tolerant controller is designed for nonstrict-feedback stochastic nonlinear systems with actuator faults.At each step of the controller design,a fuzzy logic system is constructed to approximate the auxiliary virtual control signal.The maximum norm of the ideal weighting vectors is taken as the estimation parameter,therefore,only one adaptive parameter is generated,which alleviates the computation complex.From the simulation results,it is verified that the proposed control strategy not only has robustness to actuator failure and random disturbance,but also guarantees that the system signals are bounded in probability.Then,an adaptive fuzzy fault-tolerant control problem for a class of nonstrict-feedback nonlinear systems with quantized inputs is considered.By employing asymmetric hysteresis-type quantizer,introducing the nonlinear decomposition strategy of the quantizer ouput,and considering the influence of actuator faults,an effective adaptive control strategy is proposed for the more general system.The proposed control strategy guarantees that better tracking performance and the boundedness of all signals in the closed-loop system are obtained.From the simulation,the effects of the quantization parameters on system performance are compared,and the effectiveness of the proposed quantized control method is verified. |
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