Adaptive Control For Nonlinear Systems With Constraints And Its Application

In daily life,due to the limitations of physical conditions,system performance and security requirements,many practical systems often have constraints.For the control system,if the controller does not obey the constraint rules in the process of execution,it may lead to the performance degradation of the system,or even harm or damage the whole system.Therefore,the development of constraint control has become a hot and difficult issue in the field of control in recent years.For the adaptive constrained control of nonlinear systems,this paper mainly studies the following contents:Firstly,for two kinds of switched uncertain nonlinear systems with single input single output and multiple input and multiple output,the adaptive control method with time-varying output constraints and input saturation characteristics,and the adaptive control with time-varying full-state constraints are considered respectively.Based on the conditions of arbitrary switching rules,the Tangent Barrier Lyapunov function is used to ensure that the output and state of systems does not violate the time-varying constraint bounds.The fuzzy logic systems is used to approximate the unknown continuous function,and the asymmetric saturation model is established to deal with the input saturation problem in the system.The controller and adaptive law are designed by the Backstepping technology.The Lyapunov stability is combined,then the stability of the system is analyzed.Then,the effectiveness of the proposed method is verified by simulation.Secondly,for the output feedback control of a class of switched uncertain nonlinear systems,the tracking control issue of the system with time-varying full state constraints are researched.Constructing the nonlinear adaptive fuzzy observer to estimate the unmeasurable system states.In order to ensure that the system state does not exceed the preset time-varying constraints,the Tangent Barrier Lyapunov function are selected.The adaptive fuzzy output feedback controller and adaptive law are designed by combining the Backstepping technology and fuzzy logic systems.The Lyapunov stability analysis method is used to prove that the stability of the closed-loop system,and the tracking errors and observation errors converge to the minor neighborhood of zero.The effectiveness of the proposed control scheme is proved by simulation examples.Finally,for the active seat suspension system with full state constraints,the adaptive control of the seat suspension system is proposed.In order to reduce the vibration and impact of the vehicle in the process of driving and ensure the comfort and safety of passengers,the displacement and speed constraints of human body and suspension in the active seat suspension system are discussed.According to the theory of Backstepping algorithm and the approximation characteristics of neural network,the adaptive law and controller are designed,and all signals in the system are proved to be bounded by Lyapunov stability analysis method.In addition,the simulation examples of the seat suspension system verify that the human body displacement,suspension displacement,human body speed and suspension speed are all within the set time-varying constraints.