Control Algorithm Study for some Optical Tracking Measurement System with Low Mechanical Resonance Frequency

2011 ◽  
Vol 188 ◽  
pp. 241-245
Author(s):  
Yong Li Bi ◽  
Zhong Xian Wang

For some optical tracking measurement systems, because their size, weight and space structure are very strict restrictions, DC servo motors have to drive the loads through the several stages of gear transmission. For such a nonlinear controlled object, it is difficult to obtain acceptable control performance applying the traditional controller design method. In the paper, firstly, establish such a non-linear system dynamic model, and consider intelligent control algorithm to inhibit mechanical resonance effect for the control system performance. In order to achieve real-time control easily, the paper suggests a fuzzy numeric model with the self-regulating factor based on analytic expression for such a non-linear system. The result demonstrates that the fuzzy controller is very effective in applications. This work provides a new thought for a controller design to inhibit the low mechanical resonance frequency.

2012 ◽  
Vol 562-564 ◽  
pp. 1712-1719
Author(s):  
Wei Wei Pan ◽  
Jia Xin Chen

The design methods of a kind of three-dimensional fuzzy controller and reasoning rules of its control algorithm, and the relevant simplification technology of three-dimensional table have been advanced in this paper. Self-optimized algorithm of the fuzzy controller has also been presented. The simulation results of high-order non-linear system and test of its practical applications have shown its good control effect.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Akshaykumar Naregalkar ◽  
Subbulekshmi Durairaj

Abstract A continuous stirred tank reactor (CSTR) servo and the regulatory control problem are challenging because of their highly non-linear nature, frequent changes in operating points, and frequent disturbances. System identification is one of the important steps in the CSTR model-based control design. In earlier work, a non-linear system model comprises a linear subsystem followed by static nonlinearities and represented with Laguerre filters followed by the LSSVM (least squares support vector machines). This model structure solves linear dynamics first and then associated nonlinearities. Unlike earlier works, the proposed LSSVM-L (least squares support vector machines and Laguerre filters) Hammerstein model structure solves the nonlinearities associated with the non-linear system first and then linear dynamics. Thus, the proposed Hammerstein’s model structure deals with the nonlinearities before affecting the entire system, decreasing the model complexity and providing a simple model structure. This new Hammerstein model is stable, precise, and simple to implement and provides the CSTR model with a good model fit%. Simulation studies illustrate the benefit and effectiveness of the proposed LSSVM-L Hammerstein model and its efficacy as a non-linear model predictive controller for the servo and regulatory control problem.


1990 ◽  
Vol 2 (1) ◽  
pp. 65-76 ◽  
Author(s):  
Ph. B�nilan ◽  
D. Blanchard ◽  
H. Ghidouche

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