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pid parameter tuning optimization based on multi-strategy fusion improved zebra optimization algorithm

JOURNAL OF SUPERCOMPUTING 2025年第1期81卷 1-39页

作者： Ren, Qingxin Feng, Feng Ningxia Univ Sch Informat Engn 217 Wencui North St Yinchuan 750021 Ningxia Peoples R China

The pid controller is one of the common control strategies in automatic control systems and is applied in various practical scenarios. Optimizing the design of pid controllers is an important topic at present. In this article, to solve the disadvantages of traditional pid parameter tuning methods such as time-consuming, prone to local search, complex calculation, and unclear termination criteria, a pid parameter tuning strategy based on multi-strategy fusion improved zebra optimization algorithm (MZOA) is proposed. For a series of problems such as the zebra optimization algorithm (ZOA) is prone to local optimization and slow convergence speed, the chaotic mapping and householder mirror reflection learning are combined to initialize the population, improve the distribution quality of the initial population in the search space, and introduce the tangent flight strategy based on the tangent search algorithm. The tangent flight strategy can stably produce a larger step length throughout the iteration, optimize the global search ability of the algorithm, and avoid falling into the local optimum. In the stage of resisting predator attacks, a sine-cosine optimization algorithm on hyperbolic cosine enhancement factor is introduced, using its oscillation to disturb the population and enhance the global search ability. Finally, the improved zebra optimization algorithm is used to optimize the parameters of the pid controller, and the MZOA-pid parameter tuning model and the ZOA-pid parameter tuning model are simulated. The simulation results show that compared with ZOA, MZOA has higher convergence accuracy and performance, can tune pid parameters faster, and makes the actual output curve of pid control parameters closest to the theoretical output curve.

关键词： Hippo optimization algorithm Tent chaotic mapping Householder mirror reverse learning Hyperbolic cosine enhancement factor Sine-cosine optimization algorithm Tangent flight pid parameter tuning

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New pid parameter tuning based on improved dung beetle optimization algorithm

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CANADIAN JOURNAL OF CHEMICAL ENGINEERING 2024年第12期102卷 4297-4316页

作者： Hu, Chonggao Wu, Feng Zou, Hongbo Hangzhou Dianzi Univ Informat & Control Inst Hangzhou Peoples R China

In this paper, a proportional-integral-derivative (pid) controller parameter optimization method based on the improved dung beetle optimization (IDBO) algorithm is proposed, which improves the balance between the global exploration and local exploitation capabilities of the dung beetle optimization (DBO) and significantly enhances the convergence speed and optimization accuracy. Initially, the dung beetle population is initialized using piecewise linear chaotic map (PWLCM) chaotic mapping in order to increase its variety and the DBO algorithm's capacity for global exploration. Furthermore, adaptive weighting in the DBO algorithm is now balanced between the capabilities of local exploitation and global exploration with the addition of adaptive weights. After that, in order to improve the DBO algorithm's capacity for local exploitation, a triangle wandering strategy is included during the dung beetle reproductive phase. Finally, using both L & eacute;vy flying wandering and greedy strategy (GS) together make it easier to take advantage of opportunities in both local and global areas. The outcomes of the traditional benchmark function test demonstrate a significant improvement in both convergence speed and optimization accuracy when the particle swarm optimization (PSO), DBO, grey wolf optimization (GWO), and sparrow search algorithm (SSA) algorithms are compared. The performance index function incorporates an overshooting penalty term to prevent the overshooting phenomenon in the control system. Simulation experiments are carried out for the DC motor control system, and the time domain performance, frequency domain performance, and robustness performance of the closed-loop control system with ZN-pid, Lambda-pid, PSO-pid, and IDBO-pid rectified pid controller parameters are comparatively analyzed, which verifies the validity and practicability of the IDBO algorithm.

关键词： DC motor dung beetle optimization algorithm greedy strategy L & eacute vy flying wandering pid parameter tuning PWLCM chaos mapping triangle wandering strategy

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Research on pid parameter tuning Based on Improved Artificial Bee Colony Algorithm 3

Research on PID Parameter Tuning Based on Improved Artificia...

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3rd International Conference on Applied Mathematics, Modeling and Simulation (AMMS)

作者： Li, Mingzhu Feng, Xi Haikou Univ Econ Haikou 571127 Hainan Peoples R China

Aiming at the difficulty of tuning industrial pid control parameters, an improved artificial bee colony pid tuning method is proposed. The improved artificial bee colony algorithm (IABC) uses Boltzmann selection mechanism to avoid premature convergence of roulette mechanism;at the same time, the global crossover mechanism is introduced in the domain search, which enhances the direction of the algorithm;and through chaotic avoiding search, the diversity of population is increased and the ability of global search is improved. Finally, the IABC algorithm is applied to pid parameter optimization of second order system. The simulation results show that the IABC algorithm obtains smaller ITAE and adjustment time than the basic artificial bee colony algorithm and Ziegler-Nichols engineering tuning method, and there is no overshoot. The performance of IABC algorithm is obviously improved.

关键词： Artificial Bee Colony Algorithm pid parameter tuning Boltzmann selection Global crossover Chaotic avoiding search

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Research on pid parameter tuning and Compound Control of precise XY Motion Platform 23

Research on PID Parameter Tuning and Compound Control of pre...

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23rd International Conference on Electronic Packaging Technology (ICEPT)

作者： He, Haiyuan He, Yunbo Liu, Huan Zhao, Jian Guangdong Univ Technol Sch Electromech Engn Guangzhou Peoples R China

ISBN: (数字)9781665499057

ISBN: (纸本)9781665499057

The precise XY motion platform is the key part of wire welding machine, and its performance determines the speed and quality of wire bonding. While pid controller is widely used as system control scheme for platform linear motor, pid parameter tuning is essential in this process. Aiming at the low parameter tuning efficiency of pid controller of precise XY motion platform of wire welding machine, a pid parameter tuning optimization algorithm based on hybrid particle swarm optimization algorithm(PSO) and genetic optimization algorithm(GA) is proposed in this paper. In this paper, the mathematical model of linear motor of motion platform is established and the simulation experiment is carried out in MATLAB. The experimental results show that compared with the conventional PSO algorithm and GA algorithm, this algorithm has better global search ability and faster convergence speed. Compared with manual tuning pid parameters, this algorithm has higher parameter tuning efficiency. In addition, in order to reduce the tracking error of the response output, a feedforward control structure is introduced to form a composite control with feedback control. The experimental results show that the composite control structure can greatly improve the tracking accuracy of response and ensure the positioning accuracy of the platform.

关键词： XY motion platform PSO-GA pid parameter tuning compound control

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Mathematical Modeling and pid Controller parameter tuning in a Didactic Thermal Plant

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IEEE LATIN AMERICA TRANSACTIONS 2017年第7期15卷 1250-1256页

作者： Torres, W. L. Araujo, I. B. Q. Menezes Filho, J. B. Costa Junior, A. G. Univ Fed Rio Grande Norte UFRN Dept Engn Comp & Automacao DCA Natal RN Brazil Inst Fed Educ Ciencia & Tecnol Paraiba IFPB Lab Instrumentacao Sistemas Controle & Automacao Joao Pessoa Paraiba Brazil

This paper involves an application of pid controllers topologies, deployed in an Arduino platform, applied to a didactic thermal plant. The tuning parameters of the controller are performed by experimental methods, in which have been chosen from the Ziegler-Nichols method (step response) and the CHR (Chien, Hrones and Reswick) method of tuning. Routines were created in Matlab and Arduino to provide the necessary interface and send the control parameters to the plant, in which is held signal acquisition and monitoring of the necessary variables. Therefore, it was found that different topologies have responded satisfactorily to the pid controller tuning methods used, standing out among them the CHR method. In addition, the teaching methodology PBL (Problem Based Learning) was successfully used as a way to increase interest in student learning in control systems.

关键词： Arduino Didactic thermal plant pid controller pid parameter tuning

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pid Controller parameter tuning Based on Improved Particle Swarm Optimization Algorithm

PID Controller Parameter Tuning Based on Improved Particle S...

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2015 International Conference on Electrical, Electronics and Mechatronics（ICEEM2015）

作者： Yanzi Miao Yang Liu Ying Chen Huijie Jin SIEE China University of Mining and Technology

ISBN: (纸本)9781510818019

Improved PSO algorithms combined with Simulated Annealing are proposed in this paper to solve the problems of the original PSO *** that three further improvements are proposed respectively from the parameters adjustment,the organization structure and evolution,and the topology *** common test functions are used to test the optimizing performances of the improved PSO algorithms in the *** test results indicate that all the improved PSO algorithms have better performances compared with former PSO ***,the improved PSO algorithm is applied to pid parameter tuning,and the simulation experiment results prove that the improved PSO algorithm proposed in this paper is more feasible than other intelligent algorithms.

关键词： particle swarm optimization(PSO) simulated annealing algorithm(SA) pid parameter tuning

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Based on the application of self-learning fuzzy pid control in tension control system

Based on the application of self-learning fuzzy PID control ...

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3rd International Conference on Advances in Materials Manufacturing (ICAMMP 2012)

作者： Mao Gangyuan Wu Mei Liu Huikang Huaiyin Inst Elect & Elect Engn Huaian 223003 Jiangsu Peoples R China Jiangsu Prov Huaihai Middle Sch Jiangsu Peoples R China Wuhan Univ Sci & technol Informat Coll Wuhan Hunan Peoples R China

ISBN: (纸本)9783037856482

Tension control system is one of the widely used systems in modern industrial control systems. In tension control system pid parameter setting is one of the main problems affecting the control system performance. However, conventional pid parameter is difficult to set. This article describes a pid fuzzy controller based on adaptive learning, which can change according to the deviation and deviation rate to adjust parameters in real time. Practice shows that such self-learning fuzzy pid controller has better control performance than conventional pid controller in tension control.

关键词： pid parameter tuning fuzzy control self-learn tension control

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A Novel Initial Method of Fuzzy Wavelet Network in Once-Through Steam Generator Control 33

A Novel Initial Method of Fuzzy Wavelet Network in Once-Thro...

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33rd Chinese Control Conference (CCC)

作者： Du Xue Zhao Yuxin Yuan Gannan Xia Genglei Chang Shuai Harbin Engn Univ Coll Automat Harbin 150001 Peoples R China Harbin Engn Univ Fundamental Sci Nucl Safety & Simulat Technol Lab Harbin 150001 Peoples R China

ISBN: (纸本)9781479947249

Since the outlet pressure of generator becomes a significant variable in the process of controlling to influence the efficiency of secondary loop directly, the pid control system of fuzzy wavelet network (FWN) is proposed to maintain the stabilization of pressure in this paper. By establishing FWN with MIMO structure, the network outputs provide parameters for enhance pid controller online. As the need of learning rate and control precision, a method of parameters initialization based on state estimation in wavelet neural network is presented connecting with system information such as the empirical initial values. In the process of associating with empirical values, state estimation is introduced into weights initialization, and finite element method is applied to obtain a priori probability density function of the state to calculate the initial parameters by Bayesian estimation. The FWN initial method proposed for enhance pid controller could effectively improve the accuracy of the controller parameters by more appropriate FWN initial weights, and thus the dynamic complex could be controlled more adaptively by the FWN enhance pid controller with parameters online.

关键词： Fuzzy Wavelet Neural Network parameters Initialization pid parameter tuning Once-Through Steam Generator

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Optimization of Power Plant DCS Control Based on Data Communication

Optimization of Power Plant DCS Control Based on Data Commun...

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10th World Congress on Intelligent Control and Automation (WCICA)

作者： Fu, Junjie Zhao, Zhigang Long, Junfeng Cai, Jun Li, Pingkang Datang Int Tuoketuo Power Tuoketuo 010206 Inner Mongolia Peoples R China Beijing Jiao Tong Univ Sch Mech Elect & Control Engn Beijing 100044 Peoples R China

ISBN: (纸本)9781467313988

A DCS (distributed control system) optimization approach introducing advanced algorithm realized in MATLAB into the control configuration was proposed. UDP and Modbus/TCP protocol communication program was written to establish two way data communication between the EDPF-NT plus DCS and MATLAB. Two timer objects in MATLAB were used to ensure real-time transmission of the data. Independence and reliability was guaranteed by using communication interface offered by DCS. An applying example of drum level fuzzy-pid control was given to prove the feasibility of this approach.

关键词： Communication interface DCS pid parameter tuning power plant control remote operation

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Expected Hypervolume Improvement Algorithm for pid Controller tuning and the Multiobjective Dynamical Control of a Biogas Plant

Expected Hypervolume Improvement Algorithm for PID Controlle...

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IEEE Congress on Evolutionary Computation (CEC)

作者： Yang, Kaifeng Gaida, Daniel Back, Thomas Emmerich, Michael Leiden Univ Leiden Inst Adv Comp Sci NL-2333 CA Leiden Netherlands Cologne Univ Appl Sci Inst Automat & Ind IT Gummersbach Germany

ISBN: (纸本)9781479974924

This paper presents and analyses an engineered expected hypervolume improvement (EHVI) algorithm for solving the problem of pid parameter tuning and the optimization problem of controlling the substrate feed of a biogas plant. The EHVI is the expected value of the increment of the hypervolume indicator given a Pareto front approximation and a predictive multivariate Gaussian distribution of a new point. To solve this problem, S-metric selection-based efficient global optimization (SMS-EGO), EHVI based efficient global optimization (EHVI-EGO) and SMS-EMOA are used and compared in both the pid parameter tuning problem and for biogas plant feed optimization. The results of the experiments show that surrogate model based algorithms perform better than SMS-EMOA, and the performance of EHVI-EGO is slightly better than SMS-EGO.

关键词： Expected Hypervolume Improvement Efficient Global Optimization Surrogate-Assisted Multiobjective Optimization Biogas Plant pid parameter tuning

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