Research On Prescribed Performance Robust Fault-Tolerant Control For A Class Of Nonlinear Systems With Sensor Faults

In the actual industrial process,the control accuracy and stability of many nonlinear systems are often affected by sensor faults,external disturbances,unmodeled dynamics and other factors.In order to further improve the control performance of the system and solve the problem that the traditional prescribed performance control depends on the initial conditions of the constrained variables,a new prescribed performance control method regardless of initial conditions is studied in this thesis.By using this method,the prescribed performance robust fault-tolerant control problems for nonlinear systems with sensor faults are solved.The main research contents of this thesis are as follows:1.Based on backstepping method,adaptive neural network control technology and bounded H_∞ control method,the adaptive prescribed performance bounded H_∞fault-tolerant control problem is studied for a class of strict feedback nonlinear systems with sensor faults and external disturbances.A new prescribed performance control design method is used to make the selection of prescribed performance function completely independent of the initial state of the constrained variables.The problem that the control effect of the traditional prescribed performance method depends on the initial condition of the constrained variable is solved in a new way.Based on this design method and bounded H_∞ control method,the adaptive prescribed performance bounded H_∞ controller of the system is obtained without the initial conditions of the system being known.The designed controller can ensure that all signals in the system are bounded stable,the output variables of the system can be constrained by prescribed performance functions,and it has a good suppression effect on external disturbances.Finally,the simulation results verify the feasibility and effectiveness of the proposed independent initial condition prescribed performance bounded H_∞ fault-tolerant controller.2.The mean value theorem is used to transform the pure feedback form into the strict feedback form,and the strategy of dynamic signals is used to deal with the existing unmodeled dynamics in the system.Based on backstepping method,adaptive neural network control technology,prescribed performance control method regardless of initial conditions and finite time control theory,a prescribed performance robust fault-tolerant controller regardless of initial conditions is designed for a class of pure feedback nonlinear systems with unmodeled dynamics and sensor faults.The designed controller can effectively suppress the influence of unmodeled dynamics on the system,so that the system has great robustness.Meanwhile,the scheme can improve the transient and steady-state performance and convergence rate of the system,and ensure that all signals in the system are finite-time bounded stable,and the system output can achieve the prescribed performance constraint effect within the limited time.Finally,the simulation results verify the feasibility and effectiveness of the proposed prescribed performance robust fault-tolerant controller regardless of initial conditions based on the finite time theory.