scholarly journals Multiobjective Optimization Design of a Fractional Order PID Controller for a Gun Control System

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Qiang Gao ◽  
Jilin Chen ◽  
Li Wang ◽  
Shiqing Xu ◽  
Yuanlong Hou
Keyword(s):  
Control System ◽  
Multiobjective Optimization ◽  
Fractional Order ◽  
Optimization Design ◽  
Differential Evolution Algorithm ◽  
Optimal Solution ◽  
Parameter Tuning ◽  
Gun Control ◽  
Tuning Method ◽  
Fractional Order Pid

Motion control of gun barrels is an ongoing topic for the development of gun control equipments possessing excellent performances. In this paper, a typical fractional order PID control strategy is employed for the gun control system. To obtain optimal parameters of the controller, a multiobjective optimization scheme is developed from the loop-shaping perspective. To solve the specified nonlinear optimization problem, a novel Pareto optimal solution based multiobjective differential evolution algorithm is proposed. To enhance the convergent rate of the optimization process, an opposition based learning method is embedded in the chaotic population initialization process. To enhance the robustness of the algorithm for different problems, an adapting scheme of the mutation operation is further employed. With assistance of the evolutionary algorithm, the optimal solution for the specified problem is selected. The numerical simulation results show that the control system can rapidly follow the demand signal with high accuracy and high robustness, demonstrating the efficiency of the proposed controller parameter tuning method.

scholarly journals A Simplified Fractional Order PID Controller’s Optimal Tuning: A Case Study on a PMSM Speed Servo

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 130
Author(s):  
Weijia Zheng ◽  
Ying Luo ◽  
YangQuan Chen ◽  
Xiaohong Wang
Keyword(s):  
Control System ◽  
Fractional Order ◽  
Dynamic Performance ◽  
Permanent Magnet Synchronous Motor ◽  
Motor Speed ◽  
Estimation Model ◽  
Tuning Method ◽  
Suitable Definition ◽  
Fractional Order Pid

A simplified fractional order PID (FOPID) controller is proposed by the suitable definition of the parameter relation with the optimized changeable coefficient. The number of the pending controller parameters is reduced, but all the proportional, integral, and derivative components are kept. The estimation model of the optimal relation coefficient between the controller parameters is established, according to which the optimal FOPID controller parameters can be calculated analytically. A case study is provided, focusing on the practical application of the simplified FOPID controller to a permanent magnet synchronous motor (PMSM) speed servo. The dynamic performance of the simplified FOPID control system is tested by motor speed control simulation and experiments. Comparisons are performed between the control systems using the proposed method and those using some other existing methods. According to the simulation and experimental results, the simplified FOPID control system achieves the optimal dynamic performance. Therefore, the validity of the proposed controller structure and tuning method is demonstrated.

scholarly journals An MEA-Tuning Method for Design of the PID Controller

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Yongli Zhang ◽  
Lijun Zhang ◽  
Zhiliang Dong
Keyword(s):  
Pid Controller ◽  
Industrial Process ◽  
Optimal Solution ◽  
Design Feature ◽  
Parameter Tuning ◽  
Parallel Structure ◽  
Evolutionary Information ◽  
Tuning Method ◽  
Efficiency And Effectiveness ◽  
Global Optimal

The optimization and tuning of parameters is very important for the performance of the PID controller. In this paper, a novel parameter tuning method based on the mind evolutionary algorithm (MEA) was presented. The MEA firstly transformed the problem solutions into the population individuals embodied by code and then divided the population into superior subpopulations and temporary subpopulations and used the similar taxis and dissimilation operations for searching the global optimal solution. In order to verify the control performance of the MEA, three classical functions and five typical industrial process control models were adopted for testing experiments. Experimental results indicated that the proposed approach was feasible and valid: the MEA with the superior design feature and parallel structure could memorize more evolutionary information, generate superior genes, and enhance the efficiency and effectiveness for searching global optimal parameters. In addition, the MEA-tuning method can be easily applied to real industrial practices and provides a novel and convenient solution for the optimization and tuning of the PID controller.

Fuzzy Fractional Order PID Based Parallel Cascade Control System

2014 ◽  
pp. 293-302 ◽  
Author(s):  
Rangaswamy Karthikeyan ◽  
Sreekanth Pasam ◽  
Sandu Sudheer ◽  
Vallabhaneni Teja ◽  
Shikha Tripathi
Keyword(s):  
Control System ◽  
Fractional Order ◽  
Cascade Control ◽  
Fractional Order Pid ◽  
Cascade Control System

Fractional order PID Based Control Strategy for the Valve Plant of Hydraulic Transformer

2012 ◽  
Vol 203 ◽  
pp. 46-50
Author(s):  
Shu Nan Liu ◽  
Dan Tong Xie ◽  
Shu Qiang Jia ◽  
Tao Shang ◽  
Yong Ming Yao ◽  
...  
Keyword(s):  
Fractional Order ◽  
Control Strategy ◽  
Fuzzy Logic Controller ◽  
Differential Evolution Algorithm ◽  
Pressure Control ◽  
Step Response ◽  
Fuzzy Pid Control ◽  
Output Pressure ◽  
Hydraulic Transformer ◽  
Fractional Order Pid

Aiming at the pressure control of hydraulic transformer (HT), the fractional order PID (FOPID) controller is proposed for the control of the position of the valve plate. The assignment system of the HT is carefully modeled. To optimally determine the parameters of the FOPID controller, a self-adapting differential evolution algorithm is employed. Numerical simulation is conducted to investigate the proposed control strategy. Both step response and sinusoidal command signal tracking of the servo system is assessed, and the results demonstrate that the proposed control strategy is obviously superior to the conventional PID, Fuzzy Logic Controller (FLC) and fuzzy-PID control strategy, and can afford precise tracking performances. It is suitable for the precise adjustment of the output pressure of the HT.

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