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A new adjusting technique for PID type fuzzy logic controller using PSOSCALF optimization algorithm

delete2019-12-01
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E
Elham Yazdani Bejarbaneh *
A
Ahmad Bagheri
B
Behnam Yazdani Bejarbaneh
S
Salinda Buyamin
DOI:10.1016/j.asoc.2019.105822delete
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Abstract

Abstract

En 中文
The main aim of this work consists of proposing a new three-step adjusting approach for an improved version of PID-type fuzzy structure in order to determine its design parameters based on a novel hybrid PSO search technique called PSOSCALF, combining Sine Cosine Algorithm (SCA) and Levy Flight (LF) distribution. In addition, conventional and self-tuning controllers are designed to get a better understanding of the performance and robustness of the proposed PID-type FLC approach. At first, the proposed PID-type FLC structure is defined as an optimization problem and then the PSOSCALF algorithm is applied to resolve it systematically. Evaluation of the performance quality of the proposed fuzzy structure is accomplished based on the stabilization and tracking control of a nonlinear Inverted Pendulum (IP) system. To make a complete comparison, the performance of three other optimization techniques namely simple PSO, Differential Evolution (DE) and Cuckoo Search (CS) are examined against the hybrid PSOSCALF algorithm. The simulation results demonstrate that the proposed PSOSCALF-tuned PID-type FLC structure is able to decrease the overshoot and integral square error amounts by about 25% and 10%, respectively compared to the self-tuning controllers. Finally, for more validation, all the controllers are tested under four different disturbance scenarios. Obtained results show that the proposed PID-type FLC can better stabilize the pendulum angle under all the scenarios compared to the PID and self-tuning controllers. (C) 2019 Elsevier B.V. All rights reserved.
Keywords:
PID-type fuzzy logic controller (PID-type FLC)
Particle swarm optimization (PSO)
Sine cosine algorithm (SCA)
Levy flight (LF)
Differential evolution (DE)
Cuckoo search (CS)
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Applied Soft Computing cover
Applied Soft Computing
IF:
6.6
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University of Guilan
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Islamic Azad University
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Universiti Teknologi Malaysia
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