Parameters optimization of PID controller based on Kalman filter and ant colony algorithm

2011 ◽  
Author(s):  
Li Shelei ◽  
Li Haitao
Keyword(s):  
Kalman Filter ◽  
Pid Controller ◽  
Ant Colony Algorithm ◽  
Parameters Optimization ◽  
Ant Colony

Ant Colony Algorithm Application In Glass Fiber Textile Machine Parameter Tuning

2012 ◽  
Vol 462 ◽  
pp. 71-76 ◽  
Author(s):  
Li Hong Zhang ◽  
Shu Qian Chen ◽  
Gui Zhi Bai
Keyword(s):  
Glass Fiber ◽  
Pid Control ◽  
Ant Colony Algorithm ◽  
Control Process ◽  
Parameter Tuning ◽  
Integral Function ◽  
Parameters Optimization ◽  
Ant Colony ◽  
Control Parameters ◽  
Optimization Strategy

In glass fiber textile process, non-axis volume cloth drive motor with glass fabric volume increases, increasing the pressure on the drive shaft, moreover, because of cloth non-axis volume makes the pressure in the process of change is evident, that causes the motor load changing constantly, the traditional PID control system controller cannot timely tracking response. In order to solve the problem which the control parameters optimizes, improves the system performance, proposed a new Ant colony algorithm PID parameters optimization strategy, this solution can combine characteristics that Ant colony algorithm can fast find the most superior parameter solution stably and PID can precise adjustment. In the control process, taken the PID parameters as a colony of ants, used to control the absolute error integral function as the optimization objective, dynamically adjust the PID control parameters in the control process, so as to realize the PID parameters on-line tuning.

Ant Colony Algorithm and its Applications to Optimization of PID Parameters

2010 ◽  
Vol 431-432 ◽  
pp. 568-571 ◽  
Author(s):  
Sheng Li Song ◽  
Jian Zhao Zhou ◽  
Hai Tao Wang ◽  
Hu Sheng Feng ◽  
Ren He
Keyword(s):  
Computer Simulation ◽  
Genetic Algorithms ◽  
Pid Controller ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Mathematical Representation ◽  
Digital Pid ◽  
Tuning Pid Parameters

In this paper, an improved ACA (IACA) is used for tuning PID parameters. Firstly, the mathematical representation of conventional digital PID controller is deduced. Then genetic algorithms (GAs) and ACA are described. Thirdly, a PID controller based on IACA is designed. Computer simulation is performed for the proposed IACA-based PID controller finally. The results show that the proposed method could search the optimization PID parameters efficiently. The tryout of the designed controller in a paver walk system driven by valve-controlled motor runs well up to present.

Regulation of PID Controller Parameters Based on Ant Colony Optimization Algorithm in Bending Control System

2011 ◽  
Vol 128-129 ◽  
pp. 205-210 ◽  
Author(s):  
Yu Zhen Yu ◽  
Xin Yi Ren ◽  
Chun Yan Deng ◽  
Jing Jing Yu ◽  
Shu Zhen Li ◽  
...  
Keyword(s):  
Control System ◽  
Pid Controller ◽  
Ant Colony Algorithm ◽  
Control Method ◽  
External Disturbance ◽  
Good Control ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Control Effect ◽  
Dynamic Quality

The bending-roll control system has characteristics of time-varying, time-delay, nonlinearity and serious external disturbance, so it is hard to establish precise math model that be applied to control. In view of the problems above, ant colony algorithm is used to tuning parameters of PID controller and concrete step of PID parameters tuning based on ant colony algorithm is given. The simulation results indicate that the method not only improves control performance and dynamic quality, but also has strong self-adapting ability and robustness. It achieved a very good control effect when used in bending control system that proved the correctness and effectiveness of the control method.

The Main Steam Temperature Cascade PID Controller Parameters Tuning Optimization Based on Ant Colony Algorithm

2012 ◽  
Vol 239-240 ◽  
pp. 1442-1447
Author(s):  
Ji Ming Hu ◽  
Qing Shan Ji
Keyword(s):  
Pid Controller ◽  
Ant Colony Algorithm ◽  
Good Control ◽  
Absolute Error ◽  
Ant Colony ◽  
Steam Temperature ◽  
Control Effect ◽  
Tuning Method ◽  
Multiple Parameters ◽  
Main Steam

The main steam temperature of the boiler adopted usually a cascade PID control. Traditional PID parameter engineering tuning method has a very high demand for the control personnel. And the control loop of inner and outer ring interacted. Adjusting wasted the time and labor, and the control effects were difficult to achieve the optimal. Adopting the ant colony algorithm can optimize Cascade PID controller parameters. A combination of multiple parameters was the ant colony's foraging path, and the moment integral of absolute error was the optimization objective function, through the simulation for an ant foraging process, the optimal combination of parameters was identified. The simulation results showed that the main steam temperature cascade PID controller based on ant colony algorithm has good control effect.

Ant Colony Algorithm Application in Water Treatment Control System Parameter Tuning

2012 ◽  
Vol 433-440 ◽  
pp. 4354-4360
Author(s):  
Shu Qian Chen ◽  
Li Hong Zhang
Keyword(s):  
Control System ◽  
Water Treatment ◽  
Pid Control ◽  
Ant Colony Algorithm ◽  
Thermal Power ◽  
Control Process ◽  
Parameters Optimization ◽  
Ant Colony ◽  
Control Parameters ◽  
Treatment Control

In Thermal Power Generation and heating Water Treatment process, duo to the water supply pipeline pressure and flow changes, the traditional PID control system controller cannot the prompt track response, PH value of water changes in a larger range, increased damage to the boiler pipes. In order to solve the problem which the control parameters optimizes, improves the system performance, proposed a new Ant colony algorithm PID parameters optimization strategy, this solution can combine characteristics that Ant colony algorithm can fast find the most superior parameter solution stably and PID can precise adjustment. In the control process, taken the PID parameters as a colony of ants, used to control the absolute error integral function as the optimization objective, dynamically adjust the PID control parameters in the control process, so as to realize the PID parameters on-line tuning, to improve real-time of the water treatment control system, improved the stability of the system, and achieve a better control effect.

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