Adaptive Backstepping Fuzzy Control Design For Complicated Nonlinear Systems

In recent years,with the rapid development of modern science and technology,industrial control system towards to the direction of large-scale and complex,which leads to the nonlinearity of the controlled system significantly strong.On the one hand,in practical control engineering,non-smooth nonlinear characteristics,such as dead-zone and saturation,usually occur in actuators and sensors,such as mechanical connections,hydraulic actuators and electric servomotors.Therefore,the investigation on stability analysis and controller design for a class of nonlinear systems with non-smooth nonlinear phenomenon is a hot topic and has attracted increasing attention in the control community.Furthermore,in order to improve the performance of the system,many control systems have constraints on the output or states.Therefore,the research on control of nonlinear systems with constraints is important both to the development of control theory itself and to the synthesis of practical control engineering systems.Even though many researchers developed some significant results for a class of nonlinear systems,there still exist many problems that have not been fully considered.Based on the adaptive backstepping control method,the paper will investigate the following problems on the uncertain complex nonlinear systems:Chapter 2 investigates the problem of adaptive fuzzy tracking control for nonlinear strict-feedback systems with input delay and output constraint.Fuzzy logic systems are used to approximate the unknown functions during the procedure of controller design.Input delay is handled based on the information of Pade approximation and output constraint problem is solved by barrier Lypaunov function.Under the framework of adaptive fuzzy control,a novel adaptive fuzzy tracking control scheme is developed to guarantee the system performance.Chapter 3 investigates the problem of adaptive fuzzy tracking control for a category of pure-feedback nonlinear systems with time-varying delay and unknown dead zone.Fuzzy logic systems are used to identify unknown functions existing in systems.Bydesigning the Lyapunov-Krasovskii functional,the problem of time delay is handled.Based on the information of dead-zone slopes,dead zone is handled.Moverver,under the framework of adaptive backstepping,a novel adaptive fuzzy controller is designed to guarantee all signals of the closed-loop systems are bounded,and the tracking error can be regulated to the origin with a small neighborhood based on Lyapunov stability theory.Chapter 4 presents an adaptive fuzzy control approach for a category of uncertain nonstrict-feedback systems with input saturation and output constraint.Fuzzy logic systems are ultilized to approximate the unknown functions existing in the system.A hyperbolic tangent function is used to approximate the non-smooth saturation function.Based on the introduction of barrier Lyapunov function,the output of the system is strictly limited to a prescribed range.In the framework of adaptive backstepping control,a novel adaptive fuzzy control stragery is proposed,which can guarantee the system performance.Chapter 5 investigates the problem of adaptive fuzzy output feedback control for a category of nonstrict-feedback systems subject to both unmodeled dynamics and fuzzy dead zone input.Through constructing a fuzzy state observer and introducing a center of gravity method,unmeasurable states are estimated and the fuzzy dead zone input is defuzzified,respectively.By employing fuzzy logic systems to identify the unknown functions.In addition,combining small-gain approach with adaptive backstepping control technique,a novel adaptive fuzzy output feedback control strategy is developed,which ensures that all signals involved are semi-globally uniformly bounded.