Research On The Robust Iterative Learning Control Problem Of The Discrete-time Linear Repetitive Processes

For some systems with repetitive operation(such as manipulators,etc.),the tracking control problem of reference trajectory in a finite interval is often considered,and iterative learning control(ILC)technology is one of the effective tools to solve such problems.In recent years,most of the existing results about ILC focus on asymptotic tracking,that is,tracking control is achieved as the number of iterations tends to infinity.But in practical application,it is more meaningful to realize finite iteration tracking and improve the convergence speed of the algorithm.In addition,there are inevitably uncertain factors such as time delay,external disturbance and data dropout in the actual system.No doubt that the existence of these problems will not only affect the performance of the control system,and even lead to system instability.Therefore,in order to further analyze the trajectory tracking problem,it has important theoretical significance and application value to consider the influence of uncertain factors at the initial stage of system control design.Based on the above analysis,in this thesis,the problem of robust iterative learning control based on the linear repetitive process model is studied.The main research work of this thesis includes the following aspects:(1)The iterative learning control problem for discrete-time linear systems with time delays in finite frequency domain is studied.An observer-based iterative learning control algorithm in finite frequency domain is proposed for discrete linear repetitive systems with state delay.By using kalman-Yakubovech-Popov(KYP)lemma,a sufficient condition for the stability of the controlled system is given,which guarantees the monotone convergence of tracking error in finite time,and achieves the accurate tracking of the reference signal.Finally,the feasibility of the algorithm is illustrated by simulation.(2)The finite-iteration tracking of discrete-time linear systems with packet-loss via ILC scheme is investigated.For discrete linear repetitive systems with external disturbance and packet loss,the definition of finite-iteration tracking is introduced,and then the design method of robust iterative learning controller with no packet loss and with packet loss is proposed by means of lifting vector matrix technique and norm scaling technique.The proposed algorithms can track the desired trajectories within finite iterations,and the mathematical calculation methods of the upper bound of iteration are given respectively.Finally,the effectiveness of the proposed method is verified by simulation.(3)An improved robust ILC design problem based on sliding mode control is studied.For discrete linear repetitive systems with external disturbances,an improved fast iterative learning control algorithm is proposed based on sliding mode control.Corresponding to the fast arrival stage and sliding mode of sliding mode control system,the learning algorithm also has two stages.Then,Lyapunov function method is used to obtain the solvable condition of the system stability,and the optimal controller gain design scheme is proposed.Finally,the effectiveness and superiority of the proposed control design algorithm are demonstrated by the simulation of gantry robot.