An Auto-Adaptive GA-PID Control Method Based on CMAC Net

2011 ◽  
Vol 219-220 ◽  
pp. 1139-1144
Author(s):  
Wei Qiang Yue ◽  
Li Qiang Jin ◽  
Chuan Xue Song

This paper aimed at solving the difficulty of nonlinear process control by classical PID controller. The author structured a GA-PID controller taking advantage of the multipoint optimizing and fast compute speed of GA, which can get the optimal PID parameters by on-line turning. At the same time, the author introduced a CMAC feed-forward controller which make full use of the high precision to approach nonlinearly object of CMAC. Combine them, a concurrent pattern control method appear, which synthesize advantages of two controllers and is more fit for nonlinear process. The simulation result indicated that the method has high accuracy and good robustness.

2011 ◽  
Vol 62 (3) ◽  
pp. 147-152
Author(s):  
Albena Taneva ◽  
Michail Petrov ◽  
Ivan Ganchev

Hybrid PID Control Algorithms for Nonlinear Process ControlThis paper presents modifications of the classical PID control algorithm, implemented by an Adaptive Neuro-Fuzzy Architecture (ANFA). The main goal here is to design a fuzzy PID controller with a flexible structure, adaptive tuning of its parameters and algorithm modifications, which leads to improvement of the system performance. Thus the controlling process and system are prevented from the undesired and non expected changes of the system input signals. The antecedent part of the applied fuzzy rules contains a linear function, similar to the modified discrete equation of the corresponding conventional PID controller. The simulations demonstrate satisfactory results of these performances and implementations applied to a nonlinear plant.


2012 ◽  
Vol 220-223 ◽  
pp. 1258-1261
Author(s):  
Li Hong Wang

PID control is adopted in traditional DC speed regulating system. In start process the current super adjustment value is big. When adding load perturbation and voltage perturbation suddenly, its dynamic state function will be decended. Aimming at this problem, a kind of improved system was put forward. The speed modulator used fuzzy PID controller, according to e and ec, the parameters of the modulator can be modified on line. The current modulator adopted integral separable PID control method. The simulation results indicated that the improved system has better dynamic state function and anti- Rao function. Particularly the start current wave closes to the ideal rectangle wave more. So the responding speed of the system can be sped.


2014 ◽  
Vol 602-605 ◽  
pp. 1186-1189
Author(s):  
Dong Sheng Wu ◽  
Qing Yang

Aiming at the phenomena of big time delay are normally existing in industry control, this paper proposes an intelligent GA-Smith-PID control method based on genetic algorithm and Smith predictive compensation algorithm and traditional PID controller. This method uses the ability of on line-study, a self-turning control strategy of GA, and better control of Smith predictive compensation to deal with the big time delay. This method overcomes the limitation of traditional PID control effectively, and improves the system’s robustness and self-adaptability, and gets satisfactory control to deal with the big time delay system.


2011 ◽  
Vol 128-129 ◽  
pp. 890-893
Author(s):  
De Quan Zhu ◽  
Wen Hua Xie ◽  
Lei Sun

To improve the control precision of six degree-of-freedom parallel platform, a fuzzy immune PID control method was presented based on the immune feedback mechanism and fuzzy control theory, and the parameters of PID controller was optimized with hybrid algorithm. First, least square algorithm was used for off-line optimization to form immune feedback control system. Then, genetic algorithm was used for on-line optimization to get the optimal performance parameters of immune PID control system and the optimal fuzzy proportional parameters. Simulation results demonstrated that the control method designed gets tracking effect with high precision and speed.


2011 ◽  
Vol 58-60 ◽  
pp. 1914-1919
Author(s):  
De Quan Zhu ◽  
Cheng Mao Cao ◽  
Lei Sun ◽  
Mei Zhu

To improve the control precision of multi-joint robots, a adaptive fuzzy immune PID control method for multi-joint robots was presented based on the immune feedback mechanism and fuzzy control theory, and the parameters of PID controller was optimized with hybrid algorithm. First, least square algorithm was used for off-line optimization to form immune feedback control system. Then, genetic algorithm was used for on-line optimization to get the optimal performance parameters of immune PID control system and the optimal fuzzy proportional parameters. Simulation results of a 2-joint robot manipulator demonstrated that the control method designed gets tracking effect with high precision and speed.


2021 ◽  
Vol 11 (6) ◽  
pp. 2685
Author(s):  
Guojin Pei ◽  
Ming Yu ◽  
Yaohui Xu ◽  
Cui Ma ◽  
Houhu Lai ◽  
...  

A compliant constant-force actuator based on the cylinder is an important tool for the contact operation of robots. Due to the nonlinearity and time delay of the pneumatic system, the traditional proportional–integral–derivative (PID) method for constant force control does not work so well. In this paper, an improved PID control method combining a backpropagation (BP) neural network and the Smith predictor is proposed. Through MATLAB simulation and experimental validation, the results show that the proposed method can shorten the maximum overshoot and the adjustment time compared with traditional the PID method.


2014 ◽  
Vol 685 ◽  
pp. 368-372 ◽  
Author(s):  
Hao Zhang ◽  
Ya Jie Zhang ◽  
Yan Gu Zhang

In this study, we presented a boiler combustion robust control method under load changes based on the least squares support vector machine, PID parameters are on-line adjusted and identified by LSSVM, optimum control output is obtained. The simulation result shows control performance of the intelligent control algorithm is superior to traditional control algorithm and fuzzy PID control algorithm, the study provides a new control method for strong non-linear boiler combustion control system.


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