Performance Improvement of Vector Control Permanent Magnet Synchronous Motor Drive Using Genetic Algorithm-Based PI Controller Design Rajesh Kumar Mahto, Ambarisha Mishra, and Bharti Kumari Abstract The proposed work presents an improved performance of vector control PMSM drive using PI controllers, and each controller parameter is tuning with genetic algorithm-based optimization technique. The ability to work well of a drive system for variable speed and load in closed-loop system depends on controller’s perfor- mance. The working performance of controllers depends on its gain parameter; hence, the genetic algorithm-based optimization technique gives a unique value of each controller gain parameters for sudden change in speed and load. These properties of controllers improved the working performance of drive system. The proposed work had been developed in MATLAB/Simulink environment for variable speed and load, and it had been seen that from output response the proposed work greatly improved the settling time, THD in stator current, supply voltage profile and performance of overall drive system. Keywords Controller design · Optimization technique · Vector control 1 Introduction The genetic algorithm is an optimization technique work on the basis of search heuristic, and it is inspired by Charles Darwin’s theory of natural evolution. There are several methods of optimization technique, and these are used in various fields of engineering. These methods are used to improve the performance of a system like attribute reduction and methods of classifier and feature extraction [1–4]. These optimization techniques are also used in electric drive to improve controller’s performance and tuning approaches. In this work, PMSM motor is used in vector R. K. Mahto (B ) · A. Mishra National Institute of Technology Patna, Patna, India A. Mishra e-mail: ambrish.mishra@nitp.ac.in B. Kumari Nalanda College of Engineering, Chandi, Nalanda, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Khanna et al. (eds.), International Conference on Innovative Computing and Communications, Advances in Intelligent Systems and Computing 1394, https://doi.org/10.1007/978-981-16-3071-2_24 279