scholarly journals A PID Tuning Strategy Based on a Variable Weight Beetle Antennae Search Algorithm for Hydraulic Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Yujing Qiao ◽  
Yuqi Fan
Keyword(s):  
Hydraulic System ◽  
Pid Controller ◽  
Search Algorithm ◽  
Parameter Tuning ◽  
Hydraulic Systems ◽  
Basic Algorithm ◽  
Response Characteristics ◽  
Pid Tuning ◽  
Variable Weight ◽  
Tuning Process

To select reasonable PID controller parameters and improve control performances of hydraulic systems, a variable weight beetle antenna search algorithm is proposed for PID tuning in the hydraulic system. The beetle antennae search algorithm is inspired by the beetle preying habit depending on symmetry antennae on the head. The proposed algorithm added the exponential equation mechanism strategy in the basic algorithm to further improve the searching performance, the convergence speed, and the optimization accuracy and obtain new iteration and an updating method in the global searching and local searching stages. In the PID tuning process, advantages of less parameters and fast iteration are realized in the PID tuning process. In this paper, different dimension functions were tested, and results calculated by the proposed algorithm were compared with other famous algorithms, and the numerical analysis was carried out, including the iteration, the box-plot, and the searching path, which comprehensively showed the searching balance in the proposed algorithm. Finally, the reasonable PID controller parameters are found by using the proposed method, and the tuned PID controller is introduced into the hydraulic system for control, and the time-domain response characteristics and frequency response characteristics are given. The results show that the proposed PID tuning method has good PID parameter tuning ability, and the tuned PID has a good control ability, which makes the hydraulic system achieve the desired effect.

scholarly journals Optimized PID Controller Based on Beetle Antennae Search Algorithm for Electro-Hydraulic Position Servo Control System

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2727 ◽  
Author(s):  
Yuqi Fan ◽  
Junpeng Shao ◽  
Guitao Sun
Keyword(s):  
Control System ◽  
Pid Controller ◽  
Search Algorithm ◽  
Three Dimensional ◽  
Parameter Tuning ◽  
Servo Control ◽  
Dimensional Parameter ◽  
Servo Control System ◽  
Position Servo Control ◽  
Position Servo

To improve the controllability of an electro-hydraulic position servo control system while simultaneously enhancing the anti-jamming ability of a PID controller, a compound PID controller that combines the beetle antennae search algorithm with PID strategy was proposed, and used to drive the position servo control system of the electro-hydraulic servo system. A BAS-PID controller was designed, and the beetle antennae search algorithm was used to tune PID parameters so that the disturbance signal of the system was effectively restrained. Initially, the basic mathematical model of the electro-hydraulic position servo control system was established through theoretical analysis. The transfer function model was obtained by identifying system parameters. Then, the PID parameter-tuning problem was converted into a class of three-dimensional parameter optimization problem, and gains of PID controllers were adjusted using the beetle antennae search algorithm. Finally, by comparing the effectiveness of different algorithms, simulation and experimental results revealed that the BAS-PID controller can greatly enhance the performance of the electro-hydraulic position servo control system and inhibit external disturbances when different interference signals are used to test the system’s robustness.

scholarly journals Parameter effect analysis of particle swarm optimization algorithm in PID controller design

2019 ◽  
Vol 9 (2) ◽  
pp. 165-175
Author(s):  
Mustafa Şinasi Ayas ◽  
Erdinc Sahin
Keyword(s):  
Particle Swarm Optimization ◽  
Steady State ◽  
Pid Controller ◽  
Parameter Tuning ◽  
Pso Algorithm ◽  
System Response ◽  
Industrial Control ◽  
Swarm Optimization ◽  
Control Applications ◽  
Tuning Process

PID controller has still been widely-used in industrial control applications because of its advantages such as functionality, simplicity, applicability, and easy of use. To obtain desired system response in these industrial control applications, parameters of the PID  controller should be well tuned by using conventional tuning methods such as Ziegler-Nichols, Cohen-Coon, and Astrom-Hagglund or by means of meta-heuristic optimization algorithms which consider a fitness function including various parameters such as overshoot, settling time, or steady-state error during the optimization process. Particle swarm optimization (PSO) algorithm is often used to tune parameters of PID controller, and studies explaining the parameter tuning process of the PID controller are available in the literature. In this study, effects of PSO algorithm parameters, i.e. inertia weight, acceleration factors, and population size, on parameter tuning process of a PID controller for a second-order process plus delay-time (SOPDT) model are analyzed. To demonstrate these effects, control of a SOPDT model is performed by the tuned controller and system response, transient response characteristics, steady-state error, and error-based performance metrics obtained from system response are provided.

Parameter Identification of Hydraulic Systems Using Modified Coyote Optimization Algorithm

2020 ◽  
Author(s):  
Reza Mohammadi Asl ◽  
Heikki Handroos
Keyword(s):  
Artificial Intelligence ◽  
Parameter Identification ◽  
Optimization Algorithm ◽  
Traditional Method ◽  
Hydraulic System ◽  
Hydraulic Systems ◽  
Basic Algorithm ◽  
Control Engineering ◽  
Identification Method ◽  
Previous Condition

Abstract Parameter identification is one of most interesting fields for researchers in control engineering field. Different methods have been investigated in recent years. Methods can be divided into two main categories: mathematical based methods and artificial intelligence approaches. Mathematical approaches also known as traditional method which uses different formula to have an estimation of some missed parameters in practical systems, and on the other hand artificial intelligence methods uses different approaches for this purpose. This paper presents a new parameter identification method. A new modified evolutionary algorithm, which can be sorted as a approach of artificial intelligence, is presented and applied to a servo-hydraulic system as a parameter identification method. Coyote Optimization algorithm is chosen for this purpose. The presented modified algorithm is changed in a way that in each iteration, uses details from previous steps and have a better performance in comparison with the basic algorithm. The proposed algorithm tries to update each candidate based on its previous condition which has been missed in basic algorithm. The proposed intelligent method is used as parameter identification method and applied to servo-hydraulic system. The results for simulation are given. Results show the efficiency of the presented method. Based on results, it can be drawn that the proposed method can be supposed as reliable method for nonlinear systems.

Research and Simulation of Fuzzy PID Controller

2015 ◽  
Vol 779 ◽  
pp. 233-238
Author(s):  
Lu Ding ◽  
Wang Cheng
Keyword(s):  
Hydraulic System ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Parameter Tuning ◽  
Fuzzy Pid ◽  
Parallel Connection ◽  
Fuzzy Pid Controller ◽  
Controlling System ◽  
Static Performance ◽  
Hydraulic Cylinders

In light of the difficulty for the multi-variable fuzzy controller to formulate a sophisticated set of rules concerning multi-dimensional controlling, this project proposes a parallel connection fuzzy PID controller, each PID employing two fuzzy controllers to carry out parameter tuning. This project applies the parallel connection PID fuzzy controller in controlling the jacking system of the multi-hydraulic cylinders. Through the AMESim/Simulink connector, joint simulation is achieved for the hydraulic system and the controlling system. The result of the simulation reveals that this application effectively improves the dynamic and static performance of the system, as well as synchronization precision in the jacking of the hydraulic cylinders.

scholarly journals Tuning and Retuning of PID Controller for Unstable Systems Using Evolutionary Algorithm

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
V. Rajinikanth ◽  
K. Latha
Keyword(s):  
Cost Function ◽  
Pid Controller ◽  
Parameter Tuning ◽  
Pso Algorithm ◽  
Industrial Applications ◽  
Unstable Systems ◽  
Pid Tuning ◽  
Improved Performance ◽  
Tuning Methods ◽  
The Cost

Proportional + integral + derivative (PID) controllers are widely used in industrial applications to provide optimal and robust performance for stable, unstable, and nonlinear processes. In this paper, particle swarm optimization (PSO) algorithm is proposed to tune and retune the PID controller parameter for a class of time-delayed unstable systems. The proposal is to search the optimal controller parameters like , , and by minimising the cost function. The integral of squared error (ISE) criterion is considered as the cost function, which guides the PSO algorithm to get the optimised controller parameters. The procedure for PID parameter tuning and retuning is presented in detail. A comparative study is done with the conventional PID tuning methods proposed in the literature. The simulation results show that the PSO-based PID controller tuning approach provides improved performance for the setpoint tracking, load disturbance rejection, error minimization, and measurement noise attenuation for a class of unstable systems.

A Variable Speed Control Hydraulic System Based on BP Neural Network PID Controller

2011 ◽  
Vol 101-102 ◽  
pp. 439-442
Author(s):  
Fang Ping Huang ◽  
Tian Hao Peng
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Hydraulic System ◽  
Pid Controller ◽  
Good Control ◽  
Hydraulic Systems ◽  
Variable Speed ◽  
Control Effect ◽  
Research Results ◽  
Neural Network Pid

The variable speed hydraulic systems have many advantages, and research about this field in recent years has developed rapidly. In this paper, a variable speed hydraulic system is studied using BP Neural Network PID controller. The research results show that using BP Neural Network PID controller can achieve good control effect.

PID CONTROLLER TUNING USING ANT COLONY METHOD FOR SERVO HYDRAULIC SYSTEM

2019 ◽  
Vol 42 (4) ◽  
pp. 148-152
Author(s):  
Shaymaa Mahmood Mahdi ◽  
Karam Samir Khalid ◽  
Shakir Mahmood Mahdi
Keyword(s):  
Hydraulic System ◽  
Pid Controller ◽  
Ant Colony ◽  
Controller Tuning ◽  
Pid Controller Tuning

Application of improved PSO for parameter tuning of PID controller

2010 ◽  
Vol 24 (2) ◽  
pp. 141-146 ◽  
Author(s):  
Cuiyun Jin ◽  
Jianlin Wang ◽  
Jiangning Ma ◽  
Ying Wang
Keyword(s):  
Pid Controller ◽  
Parameter Tuning ◽  
Improved Pso

Design and application of an optimally tuned PID controller for DC motor speed regulation via a novel hybrid Lévy flight distribution and Nelder–Mead algorithm

2021 ◽  
pp. 014233122110196
Author(s):  
Davut Izci
Keyword(s):  
Pid Controller ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Absolute Error ◽  
Dc Motor ◽  
Cuckoo Search Algorithm ◽  
Lévy Flight ◽  
Motor Speed ◽  
Levy Flight ◽  
Speed Regulation

This paper deals with the design of an optimally performed proportional–integral–derivative (PID) controller utilized for speed control of a direct current (DC) motor. To do so, a novel hybrid algorithm was proposed which employs a recent metaheuristic approach, named Lévy flight distribution (LFD) algorithm, and a simplex search method known as Nelder–Mead (NM) algorithm. The proposed algorithm (LFDNM) combines both LFD and NM algorithms in such a way that the good explorative behaviour of LFD and excellent local search capability of NM help to form a novel hybridized version that is well balanced in terms of exploration and exploitation. The promise of the proposed structure was observed through employment of a DC motor with PID controller. Optimum values for PID gains were obtained with the aid of an integral of time multiplied absolute error objective function. To verify the effectiveness of the proposed algorithm, comparative simulations were carried out using cuckoo search algorithm, genetic algorithm and original LFD algorithm. The system behaviour was assessed through analysing the results for statistical and non-parametric tests, transient and frequency responses, robustness, load disturbance, energy and maximum control signals. The respective evaluations showed better performance of the proposed approach. In addition, the better performance of the proposed approach was also demonstrated through experimental verification. Further evaluation to demonstrate better capability was performed by comparing the LFDNM-based PID controller with other state-of-the-art algorithms-based PID controllers with the same system parameters, which have also confirmed the superiority of the proposed approach.

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