Output-feedback Control For A Class Of Lower Triangle Nonlinear Systems Based On Dynamic Gain

With the rapid development of industrial automation and science and technology,the structure of control objects is becoming increasingly complex and it is often non-linear.Among them,As a representative system in the field of non-linear control,the lower triangle nonlinear system exists widely in engineering practice.At present,a large number of literatures have studied the lower triangle nonlinear system,but because of its complexity,there is still a lot of research space for the nonlinear system.Nonlinear systems usually have strong constraints,which affect the applicability of the research system.How to weaken the constraints of the system is the main problem to be solved in this paper.In this paper,a dynamic gain control method is proposed for the unmeasurable lower triangular nonlinear system.The main contents of this paper are summarized as follows.Firstly,we analyse the research status for lower triangular nonlinear systems and output feedback control.The Back-stepping recursive design procedure,dynamic gain,constrained control and other control strategies used in the design of controllers for two different types of nonlinear systems were briefly introduced.Secondly,we investigate the problem of full state constrained control based on event triggered for a class of high-order nonlinear systems.A novel reduced order dynamic gain observer is constructed to estimate the unmeasured state variables,and relax the non-linear conditions of the system.By introducing a symmetrical barrier Lyapunov function,the full-state constraints of nonlinear system are guaranteed.Then,to relax the requirement of continuous monitoring of controller,an event-triggered output feedback controller to deal with this matter,and ensure the stability of the closed-loop nonlinear system.The effectiveness of the designed controller is verified by numerical simulation.Finally,we investigate the problem of the distributed adaptive output feedback leader-following consensus control for a class of high-order nonlinear multi-agent systems with unknown parameters and nonlinear terms.In order to estimate the unmeasurable state variables of the multi-agent systems,the novel reduced order dynamic gain K-filters arebuilt.The problem of over-estimation is avoided by estimating the bounds of unknown parameters.Then,the dynamic surface control technique is used to design the distributed controller,which greatly reduces the computational burden of the multi-agent systems.And a numerical example is shown to verify the effectiveness of the designed controller.