Predictive extended state observer-based robust control for uncertain linear systems with experimental validation

Abstract

This paper describes a predictive extended state observer-based robust control for uncertain process control applications. The technique discussed in the article uses the extended state observer (ESO) that can estimate the dynamics of the system as well as total disturbance encountered in the system. The disturbances, parametric uncertainties associated with the processes are treated as an extended state variable to be estimated in real-time using ESO. With the implementation of a predictive algorithm with an ESO, the proposed control structure extends its applicability to time-delayed higher-order processes. The proposed control technique utilizes the simple first-order modified predictive ESO even in the case of higher-order processes. The novel predictive ESO is able to obtain a delay less estimation of total disturbance as compared with existing normal ESO. Also, novel predictive ESO maintains its stability margin in presence of time delay as well provides better response as compared with normal ESO. Numerical simulations show that the proposed scheme provides a significant improvement in transient response as compared with internal model control-based proportional-integral-derivative (IMC-PID) control. The proposed scheme requires less knowledge of the process as compared with the IMC-PID structure. The implementation of the proposed control is tested on a real-life single tank level control system. Because of its merit, the suggested technique can be used as automatic for online tuning, as it is less reliant on the process model.