An enhanced fuzzy controller based on improved genetic algorithm for speed control of DC motors
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An enhanced fuzzy controller based on improved genetic algorithm for speed control of DC motors A. Lotfy1 • M. Kaveh1 • M. R. Mosavi1
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A. R. Rahmati1
Received: 28 July 2019 / Revised: 28 July 2019 / Accepted: 7 February 2020 Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Because of being imprecision and existence of uncertainty in input variables to fuzzy systems, and also their easy implementation, fuzzy controllers are introduced as one of useful optimization tools in industry especially in DC motors. Given to the growth of controller systems usages in industry, use of optimization methods has been noticed in the recent years; so that improve precision and performance of these systems. In addition to making improvement in their performance, real time implementation, less energy spending in comparison with other tools, having high speed in mathematical computation and decreasing hardware resources consumption are some serious challenges in this terrain. To optimize fuzzy controllers’ performance, various methods have been proposed by the researchers. This paper firstly focuses on applying improved Genetic Algorithm in regulating optimum parameters of fuzzy controller to rise convergence speed and accuracy. Secondly, a pipeline technique with specific strategies of diminishing required bit width for fuzzy controllers is provided to achieve maximum efficiency in fuzzy controller implementation. In general, it can be seen that optimized fuzzy controller in this paper has precise performance, high convergence speed and such advantages in efficient hardware implementation in comparison with other fuzzy controllers. Keywords Fuzzy controller Improved genetic algorithm Speed control DC motors FPGA
1 Introduction DC motors are one of useful electrical machines in industry. The relevant controllability and precise controlling and wide range of final speed of these machine are some factors which have introduced them popular electrical machine in industry. Given to the abundant uses of such machines, controller systems with high accuracy and application have to be developed. To control speed of electrical machine many controller systems have been & M. R. Mosavi [email protected] A. Lotfy [email protected] M. Kaveh [email protected] A. R. Rahmati [email protected] 1
Department of Electrical Engineering, Iran University of Science and Technology, Narmak, Tehran 13114-16846, Iran
proposed such as fuzzy controller systems [1], PID controller systems [2], adaptable PID controller systems [3], optimized systems by meta-heuristic algorithms [4], evolutionary algorithms [5–7], and neural network [8]. The training of neural network substantially has effect on performance precision [9–12]. One of the noticeable disadvantages of electrical DC machine is its non-linear characterizes which cause unsuitable performance and drop in precision. Fuzzy controllers are one of the systems which provide suitable performance in DC machines. Because of having proximate nature and less s
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