Research On Adaptive Control For Nonlinear Systems With Input And Output Constraint Characteristics

Because the influence of physical limitation of control system components, externalenvironmental interference and security factors, the constraint characteristics such as thedead-zone input, sector input and output constraint inevitably exist in control system.However, the existences of these factors will make the controller design of nonlinearsystems to be more complex and more difficult. Therefore, the adaptive control problemfor nonlinear systems with input and output constraint characteristics is focused on in thispaper. For different types of nonlinear systems, consider the condition of the systems withdead-zone input, sector input and output constraint respectively, the correspondingadaptive controller is designed based on Lyapunov stability theory. The main researchresults of this paper can be summarized as follows:Firstly, we investigate the tracking control problem for a class of nonlinear systemswith dead-zone input. For the nonlinear system with dead-zone input and linearizationunknown parameters, the controller is given based on adaptive backstepping technique.Also, the smooth controller is designed. Then, the tracking control problem of thenonlinearly parameterized systems with dead-zone is studied. Utilizing neural network toapproximate unknwon uncertainties and combining parameter separation lemma withbackstepping technique, the state feedback controller is presented in the case that theparameters of the dead-zone input model are completely unknown. Further, consider theunmodeled dynamic nonlinear system with dead-zone input, the output feedbackcontroller based on adaptive observer is proposed. However, the nonlinear term of thesystem is bounded by a function which includes not only the output, but also theunmeasured state variables of the system and unmodelled dynamics.Secondly, for a class of uncertain nonlinear system with sector input, adaptive slidingmode controller is designed based on sliding mode surface. The nonlinear delayedperturbance of the system satisfies more general bounded condition. And the unknownnonlinear function is approximated by fuzzy logic system. Simultaneously, by introducinga mathematical transformation, the limitation for knowing the sector input model parameters in the existing references is cancelled. Then, for a class of uncertain chaoticsystems with sector input, we first design adaptive sliding mode surface under the casethat system parameters are complete unknown. And, based on this adaptive sliding modesurface, the adaptive controller is given, which makes the closed-loop system isasymptotically stable.Finally, the adaptive dynamic surface controller is designed for a class of N-ordernonlinear time delay systems with output constraint, when the uncertain time delay termssatisfy some assumptions. In the design process, we introduce a new barrier Lyapunovfunction, which ensure that the closed-loop system is asymptotically stable in the sense ofuniform ultimate boundedness without violation of the output constraint. Moreover, thedynamic surface control method is extended to the control of a electrostatic microactuatorsystem which can be actively driven in both directions. And, the closed-loop systemoutput tracks the given signal primely in a desired region to prevent contact between themovable and fixed electrodes.