A Novel Quantum-Behaved Lightning Search Algorithm Approach to Improve the Fuzzy Logic Speed Controller for an Induction Motor Drive

Abstract

This paper presents a novel lightning search algorithm (LSA) using quantum mechanics theories to generate a quantum-inspired LSA (QLSA). The QLSA improves the searching of each step leader to obtain the best position for a projectile. To evaluate the reliability and efficiency of the proposed algorithm, the QLSA is tested using eighteen benchmark functions with various characteristics. The QLSA is applied to improve the design of the fuzzy logic controller (FLC) for controlling the speed response of the induction motor drive. The proposed algorithm avoids the exhaustive conventional trial-and-error procedure for obtaining membership functions (MFs). The generated adaptive input and output MFs are implemented in the fuzzy speed controller design to formulate the objective functions. Mean absolute error (MAE) of the rotor speed is the objective function of optimization controller. An optimal QLSA-based FLC (QLSAF) optimization controller is employed to tune and minimize the MAE, thereby improving the performance of the induction motor with the change in speed and mechanical load. To validate the performance of the developed controller, the results obtained with the QLSAF are compared to the results obtained with LSA, the backtracking search algorithm (BSA), the gravitational search algorithm (GSA), the particle swarm optimization (PSO) and the proportional integral derivative controllers (PID), respectively. Results show that the QLASF outperforms the other control methods in all of the tested cases in terms of damping capability and transient response under different mechanical loads and speeds.

Membrane‐hydration‐state detection in proton exchange membrane fuel cells using improved ambient‐condition‐based dynamic model

“…LSA was first introduced in 2015 86 followed by its subsequent expansion 87 to the Quantum LSA (QLSA), which demonstrated enhanced performance. LSA was first introduced in 2015 86 followed by its subsequent expansion 87 to the Quantum LSA (QLSA), which demonstrated enhanced performance.…”

“…The LSA is an optimisation technique inspired by the natural phenomenon of lightning caused by the propagation of negatively charged particles through space. LSA was first introduced in 2015 86 followed by its subsequent expansion 87 to the Quantum LSA (QLSA), which demonstrated enhanced performance. In this paper, 87 the operation of QLSA is described in detail, wherein it is revealed that the performance of QLSA is superior to that of algorithms based on the well-known particle swarm optimisation (PSO) approach and the backtracking search algorithm (BSA).…”

A Fuzzy-Rule-Based PV Inverter Controller to Enhance the Quality of Solar Power Supply: Experimental Test and Validation

“…A number of controllers are employed in the implementation of pulse width modulation (PWM) techniques, e.g., sine pulse width modulation (SPWM) and space vector pulse width modulation (SVPWM), for generating and regulating output of inverters. The SVPWM method is more complex compared to SPWM, especially for multilevel inverters [17,18]. Some of the controllers include analogue circuit controllers, microcomputers, digital circuit controllers, FPGA, and digital signal processors (DSPs) [19].…”

Optimal Capacitor Placement in Wind Farms by Considering Harmonics Using Discrete Lightning Search Algorithm

“…Proposed in 2015, the lightening search algorithm (LSA) is a powerful and flexible optimization technique [25] that was inspired by the natural phenomenon of lightning. Some engineering optimization problems related to the parameter extraction of solar cell models [26], as well as modelling wind power [27], controlling voltage and frequency in a solar thermal power plant [28], and designing a speed controller for an induction motor drive [29], have been recently and successfully solved by applying the LSA method. The results obtained by the DLSA for the optimal placement of capacitors were compared with the results obtained by the genetic algorithm (GA), and the discrete harmony search algorithm (DHSA) at different wind speeds considering or disregarding harmonics.…”