Diego Oliva , Farhad Soleimanian Gharehchopogh, Vugar Hacimahmud Abdullayev, Widi aribowo, Asmunin Asmunin, Andi Iwan Nurhidayat

A Novel Modified Tornado optimizer with Coriolis force Based On Levy Flight to Optimize Proportional Integral Derivative Parameters of DC Motor

Introduction

A novel modified tornado optimizer with coriolis force based on levy flight to optimize proportional integral derivative parameters of dc motor. Optimize DC motor PID parameters using a novel Modified Tornado optimizer (LTOC) with Coriolis force & Levy Flight. Achieves optimal overshoot response, outperforming the TOC method.

Abstract

One kind of electric motor that runs on direct current (DC) is called a DC (Direct Current) motor. This motor uses the interaction of electric current and magnetic fields to transform electrical energy into mechanical energy, or motion. Applications requiring exact speed and torque control frequently use DC motors. By minimizing errors (differences between setpoints and actual values), proportional-integral-derivative (PID) control is a control technique used to govern dynamic systems to reach desired conditions (setpoints). PID creates an ideal control signal by combining three elements. The Modified Tornado optimizer-based Coriolis force (TOC) method for DC motor control is presented in this article. The paradigm for the TOC approach is the Tornado Optimizer-Based Coriolis Force Algorithm, a metaheuristic that leverages tornado dynamics and the effect of the Coriolis force to address difficult optimization problems. According to this study, the TOC method can be improved by implementing the Levy Flight methodology. According to the results of tests employing optimal functions, the LTOC technique may broaden exploration and exploitation. Meanwhile, when the LTOC technique is applied as a DC motor controller, the optimal overshoot response value is achieved. The LTOC approach outperforms the TOC method by 0.014% and 0.037%, respectively, in terms of ITSE and ITAE values.

Review

This paper presents a novel approach to optimize Proportional-Integral-Derivative (PID) controller parameters for DC motors, focusing on a modified metaheuristic called the Levy Flight-enhanced Tornado optimizer with Coriolis force (LTOC). The core idea revolves around leveraging tornado dynamics, the Coriolis effect, and Levy Flight's search capabilities to efficiently tune PID parameters. Given the widespread application of DC motors and the critical role of precise speed and torque control, the development of robust and effective PID tuning methods remains a highly relevant research area. The authors aim to improve upon existing optimization techniques by introducing this hybridized metaheuristic, promising enhanced performance in exploration and exploitation capabilities. The methodology proposed, LTOC, builds upon the Tornado Optimizer-Based Coriolis Force Algorithm (TOC) by integrating Levy Flight, a well-known strategy for improving global search in optimization algorithms. The abstract highlights that this integration broadens the algorithm's exploration and exploitation phases, which is a common and desirable outcome when applying Levy Flight. Furthermore, the paper claims that the LTOC technique, when applied as a DC motor controller, achieves an "optimal overshoot response value." Quantitatively, the LTOC method is reported to outperform its predecessor, TOC, with improvements of 0.014% in ITSE (Integral of Time-weighted Squared Error) and 0.037% in ITAE (Integral of Time-weighted Absolute Error) values, indicating a marginal but measurable enhancement in performance metrics. While the proposed LTOC method and its claimed improvements are interesting, the abstract leaves several critical questions unanswered that would be essential for a comprehensive evaluation. Firstly, the reported percentage improvements (0.014% and 0.037%) are extremely small; the practical significance of such marginal gains over the TOC method should be thoroughly discussed and justified. A crucial omission is a comparison of LTOC's performance against other well-established and state-of-the-art metaheuristic optimization techniques (e.g., PSO, GA, SCA, etc.) or traditional PID tuning methods for DC motors. Without this broader comparative analysis, it is challenging to ascertain the true novelty and competitive advantage of LTOC in the existing literature. Additionally, details regarding the experimental setup, simulation environment (e.g., type of DC motor, specific parameters, disturbance modeling), and the computational cost of the proposed algorithm would significantly strengthen the paper. Addressing these points in the full manuscript would provide a more robust and convincing argument for the superiority and utility of the LTOC approach.

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