Research On Adaptive Constraint Control Of Non-strict Feedback Nonlinear Systems

Actual industrial production systems are often nonlinear and highly uncertain.In order to realize the automatic control of industrial production,the control research of nonlinear systems has been widely concerned by experts and scholars.Combining adaptive control with fuzzy control method,fuzzy logic systems are used to approximate estimate the unknown nonlinear terms in the systems.And the controller of nonlinear systems can be designed by adaptive backstepping method to control nonlinear systems effectively.In addition,there are still some problems that need further study.Due to the limitation of actual production conditions and the consideration of production safety,it is often necessary to limit the states of the systems in the actual production process.How to realize the full state constraints of nonlinear systems in the design stage of controller is a problem worthy of further study.On the other hand,most of the existing researches on adaptive fuzzy control of nonlinear systems are based on strict feedback or pure feedback systems,but many complex practical systems can not be represented by strict feedback or pure feedback systems.Nonlinear systems in the form of non-strict feedback have more general applicability.But the controller design of non-strict feedback systems is more difficult.For the above problems,this paper carries out the following work:(1)An adaptive fuzzy controller is designed for a class of non-strict feedback nonlinear systems with input delay and external disturbance.The system input delay problem is solved by Pade approximation method,and the adaptive backstepping design method is applied to the non-strict feedback systems by using the properties of fuzzy basis function.During the controller design process,the unknown nonlinear functions in the systems are estimated by the fuzzy logic systems,and the barrier Lyapunov function is introduced in every step of the design process,and all the states of the systems are constrained.Lyapunov stability theory is applied to prove the boundedness of all variables of the systems and satisfy the constraints.Finally,the effectiveness of the designed controller is verified by numerical simulation.Compared with the method without constraint control,the controller designed in this paper has better control effect.And the controller is applied to a simulation experiment of electromechanical system.The electromechanical system is controlled accurately,and all states of the system are constrained.(2)In order to further realize the full state time-varying asymmetric constraints of the system,based on the above research results,an adaptive fuzzy controller for a class of non-strict feedback nonlinear systems is designed based on the dynamic surface control method.By using the time-varying asymmetric barrier Lyapunov function,the time-varying asymmetric constraints are applied to all states of nonlinear systems.The first-order filter is introduced to deal with the virtual control function in the process of adaptive backstepping design,which solves the problem of continuous differential calculation of the virtual control function and reduced the time-varying asymmetric barrier Lyapunov function order requirements.The computational burden is reduced.By Lyapunov stability theory,it is proved that all states of nonlinear systems remain in time-varying asymmetric constraint intervals.Finally,the effectiveness of the controller is verified by numerical simulation and one-link manipulator system simulation.The simulation results show that the nonlinear systems are effectively controlled under the action of the designed adaptive fuzzy controller.All states do not violate the time-varying asymmetric constraints and the systems have faster tracking speed.