Self-Tuning and Adaptive Controllers

Author(s):  
Brian Roffel ◽  
Patrick Chin
1994 ◽  
pp. 27-42
Author(s):  
Rubiyah Yusof ◽  
Marzuki Khalid ◽  
Sigeru Omatu

One of the most recent development in the theories of adaptive methods in the form of self-tuning algorithms is in the area of self-tuning PID controllers (STPID). These controllers are a class of adaptive controllers but are essentially PID controllers with the capabilities of tuning their parameters automatically online. To this end, the theories of these types of controllers are still in the infancy stage. In this paper, we provide some interpretations of a STPID through some analytical and simulation results, thereby lending way for a better understanding of the algorithms and some insight into the usefullness of the algorithm. The interpretations also serve as an aid in the selection of the tuning parameters of this algorithm which can be a time consuming activity if done dilligently.


1999 ◽  
Vol 121 (3) ◽  
pp. 457-461 ◽  
Author(s):  
Thurai Vinay ◽  
Bradley Postma ◽  
Theo Kangsanant

Lagrange formalism is applied to derive a dynamic model, and design a nonlinear controller for two nonholonomic, differentially steered, wheeled mobile robots compliantly linked to a common payload. The resulting multivariable system model is of a large order and can be block decoupled by selective state feedback into five independent subsystems, two of which effectively represent the deviation dynamics of the individual robots from a prescribed path; two others represent their forward motion dynamics; while the fifth describes the payload dynamics. Controllers for each of the robot subsystems, including self-tuning adaptive controllers for the nonlinear deviation dynamics subsystems, are designed by the pole-placement technique. System performance is then evaluated via simulation for the case where each robot is undergoing curvilinear motion.


Technometrics ◽  
1980 ◽  
Vol 22 (2) ◽  
pp. 153-164 ◽  
Author(s):  
T. J. Harris ◽  
J. F. MacGregor ◽  
J. D. Wright

2003 ◽  
Vol 125 (1) ◽  
pp. 74-79 ◽  
Author(s):  
Xifan Yao

The use of fuzzy chip to implement the control of machining processes is investigated. The hardware solution can process rules in fuzzy controllers at high speed. In this paper, fuzzy-chip-based regular and self-tuning controllers are developed to maintain a constant cutting force during machining processes under time-varying cutting conditions. In the fuzzy-chip-based self-tuning controller, two knowledge bases are employed. One base is used to implement the inference of control rules and the other to execute tuning rules for adjusting the output scaling factor on line. The structure makes the proposed fuzzy-chip-based self-tuning controller different from those fuzzy adaptive controllers developed in machining. Those fuzzy-chip-based controllers are characterized by the simple structure and practical applicability for real-time implementation. Both simulation and experimental results on machining processes show that the fuzzy-chip-based controllers demonstrate feasibility, applicability, and adaptability.


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