PI Controller Tuning Based on Stochastic Optimization Technique for Performance Enhancement of DTC Induction Motor Drive
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ORIGINAL CONTRIBUTION
PI Controller Tuning Based on Stochastic Optimization Technique for Performance Enhancement of DTC Induction Motor Drives Naveen Goel1
•
Saji Chacko2 • R. N. Patel3
Received: 18 June 2019 / Accepted: 2 October 2020 The Institution of Engineers (India) 2020
Abstract Direct torque-controlled (DTC) induction motor (IM) drives over the years have been the work force of industries. The popularity of this motor drive is due to the low cost and low maintenance of induction motor coupled with the fast dynamic response and simple control structure of direct torque control method. The robust performance of the DTC induction motor drive depends on the proper tuning of its speed controller. The proposed paper makes use of the stochastic optimization technique, namely the popular harmony search algorithm, and is compared with the parameter-free Jaya algorithm for tuning the gains of the speed proportional integral controller. Simulation studies in MATLAB/Simulink show the success of the Jaya optimization for improving the performance of DTC drive with respect to speed and torque peak overshoot and steady-state error under different drive operating conditions. Keywords Variable speed drives Artificial intelligence Induction motors Optimization Cost function
& Naveen Goel [email protected] Saji Chacko [email protected] R. N. Patel [email protected] 1
Electrical and Electronics Engineering, Shri Shankaracharya Group of Institutions, Bhilai, CG 490020, India
2
Electrical Engineering, Government Polytechnic, Durg 490001, India
3
Electrical Engineering, National Institute of Technology, Raipur, Raipur, CG, India
Introduction For critical application in industries, an efficient controller for the DTC induction motor drive has to be designed. The IM being a highly cross-coupled machine, the complexity of an efficient PI controller for high performance increases substantially. Conventionally, the PI controllers are tuned by Ziegler Nichols tuning method. However, it is observed that the controller performance deteriorates under varied drive operating conditions. It has been found from literature studies that the use of the stochastic optimization techniques for obtaining the optimized values of PI controllers are finding increased importance [1–9]. All stochastic optimization algorithms invariably use common parameters like generations, population size, etc. The performance of the algorithm depends on these controlling parameters and has a direct bearing on its proper selection. Apart from this, different algorithms need their own specific control parameters like the weight factor and acceleration constants like in particle swarm optimization and similarly the pitch adjusting rate, harmony memory consideration rate, etc., in harmony search algorithm. The proposed study focuses on the Jaya optimization algorithm for finding the optimized values of speed PI controller. The main feature of this algorithm is that it does not require any parameters to be initialized as required for other pop
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