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Optimal tuning of FOPID controller for higher order process using hybrid approach

APPLIED INTELLIGENCE 2022年第13期52卷 15345-15367页

作者： George, Thomas Ganesan, V Mt Zion Coll Engn Dept Appl Elect & Instrumentat Kadammanitta Kerala India Sathyabama Univ Dept Elect & Telecommun Engn Chennai Tamil Nadu India

This paper proposes an optimal tuning of fractional order proportional integral derivative (FOPID) controller for higher order process using hybrid approach. The proposed hybrid approach is the joint execution of Dynamic Differential Annealed Optimization (DDAO) and Feedback Artificial tree (FAT) algorithm, hence it is named D2AOFAT approach. The FOPID controller parameters like k(p), k(i), k(d), lambda and mu. The FOPID controller parameters errors are minimized and predict the optimal parameters by the FAT algorithm. Based on FOPID controller parameters using FAT algorithm, the DDAO optimizes the FOPID controller parameters. The FOPID controller advantage is adjusted to accomplish that needed responses that are resolute with FAT theory and RDF parameters are predictable using DDAO technique. The purpose of the proposed control system is selected in light of the achieved parameters of time delay system (TDS). The proposed technique is carried out in MATLAB / Simulink, its performance is compared to the existing techniques, like Ziegler-Nichols fit, Curve Fit, Wang method, and IWLQR method.

关键词： State feedback gain FOPID Time delay system three controller parameters Reliability constraints and small overruns

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Advanced cuttlefish optimizer-random decision forest (ACORDF) based design of fractional order PID controller for higher-order time-delay system

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JOURNAL OF ENGINEERING DESIGN AND TECHNOLOGY 2021年

作者： George, Thomas Ganesan, V. Mt Zion Coll Engn Kadammanitta India Sathyabama Univ Dept Elect & Telecommun Engn Chennai Tamil Nadu India

Purpose The purpose of this manuscript, a state feedback gain depends on the optimal design of fractional order PID controller to time-delay system is established. In established optimal design known as advanced cuttlefish optimizer and random decision forest that is combined performance of random decision forest algorithm (RDFA) and advanced cuttlefish optimizer (ACFO). Design/methodology/approach The proposed ACFO uses the concept of crossover and mutation operator depend on position upgrading to enhance its search behavior, calculational speed as well as convergence profile at basic cuttlefish optimizer. Findings Fractional order proportional-integrator-derivative (FOPID) controller, apart from as tuning parameters (kp, ki and kd) it consists of two extra tuning parameters lambda and mu. In established technology, the increase of FOPID controller is adjusted to reach needed responses that demonstrated using RDFA theory as well as RDF weight matrices is probable to the help of the ACFO method. The uniqueness of the established method is to decrease the failure of the FOPID controller at greater order time delay method with the help of controller maximize restrictions. The objective of the established method is selected to consider parameters set point as well as achieved parameters of time-delay system. Originality/value In the established technique used to evade large order delays as well as reliability restrictions such as small excesses, time resolution, as well as fixed condition defect. These methods is implemented at MATLAB/Simulink platform as well as outcomes compared to various existing methods such as Ziegler-Nichols fit, curve fit, Wang method, regression and invasive weed optimization and linear-quadratic regression method.

关键词： Control systems Optimization algorithms FOPID State feedback gain three controller parameters Time-delay system Reliability constraints and small overruns

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