scholarly journals Model-Free Adaptive Control of Direct Drive Servo Valve of Electromagnetic Linear Actuator

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Jianhui Zhu ◽  
Jianguo Dai ◽  
Cheng Wang

An electromagnetic linear actuator (EMLA) has a promising application in direct motion control. However, ELMA will inevitably inherit uncertainties in the face of load changes, system parameter perturbation, and inherent system nonlinearities, all of which constitute disturbances adversely affecting the precision and adaptability of the control system. A model-free adaptive control (MFAC) strategy based on full form dynamic linearization (FFDL) was proposed to reduce the sensitivity of the control system to the disturbances. An adaptive control of direct drive servo valve was achieved based on the online interaction of characteristic parameters and control algorithms. The feasibility and precision of the proposed algorithm were verified through simulation and experimental results. The results show that the proposed algorithm could achieve adaptive adjustment of the servo valve response at different openings of 0-3 mm without changing control parameters, with the response time controlled within 10ms and steady state error less than 0.04mm. Furthermore, the proposed algorithm had better robustness and capacity of resisting disturbance.

2014 ◽  
Vol 596 ◽  
pp. 580-583
Author(s):  
Jian Chen ◽  
Xue Han

According to the analysis of furnace temperature control, a new control process which is based on the technique of model free adaptive control, is proposed against the defects of traditional control system. Through the analysis of the characters of MFAC and its utility for continuous and non-linear multivariable control system of glass furnace, a satisfied result indicates the good application of MFAC on temperature control of glass furnace.


2014 ◽  
Vol 608-609 ◽  
pp. 484-488
Author(s):  
Ze Min Liu

With the development of industry, the control system is more and more complex. For the nonlinear problems which can’t be solved by the traditional linear control system used now, it uses the model-free adaptive control system based on the neural network to effectively solve them. In this paper, it firstly makes a detailed analysis on the neural network, describing the neuron, the BP network and the training of neural network; then talks about the model-free adaptive control system, analyzing the structure, characteristics and algorithm of the system; and finally gives the core code of the model-free adaptive control system of the neural network. This paper provides positive effect to the industrial control staff and artificial intelligence researchers.


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