Optimization Tracking Control For The Complicate Dynamic Systems Based On Data Driven

Data driven optimization control and sliding mode control provides powerful technique for uncertain system tracking problems.The controller design based on the data driven optimization method using input or output data does not rely on the modelling information or need less modelling process shows advantages to other methods for tracking control.This dissertation uses typical data driven control methods,involving iterative feedback tuning,iterative learning control and sliding mode control methods to deal with the tracking problems of uncertain systems.The mainly work summarized as follows:(1)Iterative feedback tuning(IFT)with flow-rate convertor pH neutralisation control(IFTCNC)for the purpose of nonlinear system output tracking is proposed.A nonlinear tracking controller which tunes flow-rate using IFT is presented for pH neutralisation process.A flow-rate convertor with input and output data is designed to estimate the acids flow-rate reference input signal corresponding to the desired output pH value in the pH neutralisation process system,reducing the tracking errors in the tracking systems.The effectiveness of iterative feedback tuning with flow-rate convertor pH neutralisation control method is verified in simulation and the results clearly exhibit the high precision output tracking performance.(2)Aiming to the nonlinear time-varying system tracking problems,variable gain iterative learning control(VGILC)approach on the basis of data driven is proposed for a class of multi-input multi-output(MIMO)nonlinear time-varying systems in this paper.The updating law with variable gain is proposed to reduce tracking errors.The convergence of the tracking errors is proved.The proposed approach improves the output tracking performance within a few trials.The simulation results demonstrate the effectiveness of the proposed approach.(3)Sliding mode control for a class of uncertain systems with input constraints,unknown parameters and disturbances is proposed.The auxiliary system combined with sliding mode controller is designed to compensate the input constraints.The differential evolution algorithm is applied for the estimation of the unknown parameters,and the tracking controller is robust to the disturbances.The effectiveness of the proposed approach is verified via simulations.Considering two examples of motor system and mechanics dynamic system,the results exhibit the good output tracking performance.(4)Sliding mode tracking control for a class of uncertain nonlinear systems with unknown parameters and system states is proposed.The sliding mode control incorporates integral-chain differentiator(ICD)into the feedback system to estimate the unknown system states.The differential evolution(DE)optimization algorithm using ICD is also applied to the tracking system,which provides the unknown parametric identification with system states unknown nonlinear systems.The effectiveness of the proposed approach is verified via simulations.The results exhibit high precision output tracking performance in uncertain nonlinear systems.(5)Fast terminal sliding mode tracking control(FTSMC)for a class of uncertain nonlinear systems with unknown parameters and system states and time-varying disturbances is proposed.The fast terminal sliding mode tracking control based on the integral-chain differentiator(ICD)to the feedback system to estimate the unknown system states.The DE optimization algorithm using ICD is also applied to the tracking systems,which provides the unknown parametric estimation in the limitation of system states unknown.ICD in the tracking systems strengthens the tracking controller to be robust for the disturbances by filtering the noises.The effectiveness of the proposed approach is verified via simulations and the results exhibit high precision output tracking performance in uncertain nonlinear systems.