Optimal parameter tuning of Modified Active Disturbance Rejection Control for unstable time-delay systems using an AHP combined Multi-Objective Quasi-Oppositional Jaya Algorithm

Active Disturbance Rejection Control (ADRC) is an innovative control paradigm which emerged as a viable alternative to the traditional control design methods. However, the applicability of ADRC is limited to stable minimum phase systems. This paper investigates the problem of handling unstable time-delay systems under ADRC framework. To this end, an optimally tuned modified Active Disturbance Rejection Control (MADRC) scheme is proposed. The scheme consists of a model-assisted extended state observer designed using the known model information and a state feedback control law. The tuning of MADRC scheme is formulated as a multi-objective optimization problem with tracking and disturbance rejection performances as the objectives to be met simultaneously. Solution for this multi-objective optimization problem is carried out in two stages. The first stage is meant for generating a set of Pareto-optimal solutions with the help of Multi-Objective Quasi Oppositional Jaya Algorithm (MOQO-Jaya), while the second stage is for selection of the best among the available alternatives using Analytical Hierarchy Process (AHP). Simulation studies conducted on different unstable systems with time-delay illustrates the efficacy of the proposed scheme. Further, tracking and disturbance rejection performances are also assessed in the presence of nominal and perturbed conditions. Finally, the proposed method is extended to a Two-Input and Two-Output (TITO) process. Stability study is carried out by translating the proposed structure into a standard two degree of freedom framework. (C) 2019 Elsevier B.V. All rights reserved.