Diversity Controlled Self Adaptive Differential Evolution based design of non-fragile multivariable PI controller. (November 2015)

• Record Type: Journal Article
• Authors: Kadhar, K. Mohaideen Abdul; Baskar, S.; Amali, S. Miruna Joe
• Is Part Of: Engineering applications of artificial intelligence. Volume 46:Part A(2015:Oct.)
• Page Start: 209
• Page End: 222
• Publication Date: 2015-11
• Subjects: Non-fragile controller -- PI controller -- Differential evolution -- Monte carlo simulation -- Decoupling control -- Multivariable PI controller.; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2015.09.015
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: This paper proposes the design of non-fragile multivariable PI controller for industrial Multi Input Multi Output (MIMO) processes using Diversity Controlled Self-Adaptive Differential Evolution with Local Search (DCSaDE-LS) algorithm. The proposed non-fragile multivariable PI controller design is formulated as a single objective optimization problem with the objective of robustness subject to non-fragileness constraint. Monte Carlo Simulation is used to evaluate the non-fragileness constraint against stochastic uncertainty of controller parameters. Wood and Berry Distillation process and a real time Level-Temperature reactor process model with simple de-coupler are considered as a test systems. For constraint handling, Constraint Domination Principle (CDP) and Penalty Parameter Less (PPL) methods are incorporated in DCSaDE-LS, seperately. Also, the performance of DCSaDE-LS is compared with the recent adaptive DE algorithms namely Ensemble of mutation strategies and control parameters in Differential Evolution (EPSDE), Composite Differential Evolution (CoDE) and SaDE. The robustness and non-fragileness of the controller is analyzed under +40% and −40% variations in nominal process and controller parameters. The results demonstrated that the DCSaDE-LS designed non-fragile multivariable PI controller has good time domain performance, better robustness and non-fragileness than the reported multivariable PI controllers namely Maghade-PI, IMC-PI and NDT-PI.