A novel PID-like particle swarm optimizer: on terminal convergence analysis

Wang, Chuang; Wang, Zidong; Han, Fei; Dong, Hongli; Liu, Hongjian

doi:10.1007/s40747-021-00589-2

Cited by 4 publications

(2 citation statements)

References 55 publications

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“…e proportional-integralderivative (PID) control method is one of the most technical approaches in the control field, which has experienced remarkable development with regard to its use in mechanical systems [1][2][3][4][5]. In fact, this control approach is renowned for its simple structure.…”

Section: Background and Motivationmentioning

confidence: 99%

Optimal Fuzzy Proportional‐Integral‐Derivative Control for a Class of Fourth‐Order Nonlinear Systems using Imperialist Competitive Algorithms

et al. 2022

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The proportional integral derivative (PID) controller has gained wide acceptance and use as the most useful control approach in the industry. However, the PID controller lacks robustness to uncertainties and stability under disturbances. To address this problem, this paper proposes an optimal fuzzy-PID technique for a two-degree-of-freedom cart-pole system. Fuzzy rules can be combined with controllers such as PID to tune their coefficients and allow the controller to deliver substantially improved performance. To achieve this, the fuzzy logic method is applied in conjunction with the PID approach to provide essential control inputs and improve the control algorithm efficiency. The achieved control gains are then optimized via the imperialist competitive algorithm. Consequently, the objective function for the cart-pole system is regarded as the summation of the displacement error of the cart, the angular error of the pole, and the control force. This control concept has been tested via simulation and experimental validations. Obtained results are presented to confirm the accuracy and efficiency of the suggested method.

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Section: Background and Motivationmentioning

confidence: 99%

Optimal Fuzzy Proportional‐Integral‐Derivative Control for a Class of Fourth‐Order Nonlinear Systems using Imperialist Competitive Algorithms

et al. 2022

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“…PSO [14] is an optimization technique based on evolution and iteration, and the algorithm is used in various fields to solve real optimization problems, such as path planning problems [15], parameter identification problems [16], image processing problems [17], biomedical technologies problems [18], and other optimization problems. The advantages of PSO can be found mainly in the following four aspects.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Sine Cosine and Particle Swarm Optimization Algorithm for High-Dimensional Global Optimization Problem and Its Application

Wang,

Gao,

2024

Mathematics

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Particle Swarm Optimization (PSO) is facing more challenges in solving high-dimensional global optimization problems. In order to overcome this difficulty, this paper proposes a novel PSO variant of the hybrid Sine Cosine Algorithm (SCA) strategy, named Velocity Four Sine Cosine Particle Swarm Optimization (VFSCPSO). The introduction of the SCA strategy in the velocity formulation ensures that the global optimal solution is found accurately. It increases the flexibility of PSO. A series of experiments are conducted on the CEC2005 test suite with compositional algorithms, algorithmic variants, and good intelligent algorithms. The experimental results show that the algorithm effectively improves the overall performance of compositional algorithms; the Friedman test proves that the algorithm has good competitiveness. The algorithm also performs better in PID parameter tuning. Therefore, the VFSCPSO is able to solve the high-dimensional global optimization problems in a better way.

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Application of Novel SN-1DCNN-LSTM framework in small sample oil and gas pipeline leakage detection

Gao,

Hao,

Zhang

et al. 2024

Franklin Open

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A novel PID-like particle swarm optimizer: on terminal convergence analysis

Cited by 4 publications

References 55 publications

Optimal Fuzzy Proportional‐Integral‐Derivative Control for a Class of Fourth‐Order Nonlinear Systems using Imperialist Competitive Algorithms

Optimal Fuzzy Proportional‐Integral‐Derivative Control for a Class of Fourth‐Order Nonlinear Systems using Imperialist Competitive Algorithms

Hybrid Sine Cosine and Particle Swarm Optimization Algorithm for High-Dimensional Global Optimization Problem and Its Application

Application of Novel SN-1DCNN-LSTM framework in small sample oil and gas pipeline leakage detection

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