NDLI: Parameter Tuning of Multi-Proportional-Integral-Derivative Controllers Based on Optimal Switching Algorithms

Content Provider	Springer Nature Link
Author	Wu, Xiang Zhang, Kanjian Sun, Changyin
Copyright Year	2013
Abstract	Under the framework of switched systems, this paper considers a multi-proportional-integral-derivative controller parameter tuning problem with terminal equality constraints and continuous-time inequality constraints. The switching time and controller parameters are decision variables to be chosen optimally. Firstly, we transform the optimal control problem into an equivalent problem with fixed switching instants by introducing an auxiliary function and a time-scaling transformation. Because of the complexity of constraints, it is difficult to solve the problem by conventional optimization techniques. To overcome this difficulty, a novel exact penalty function is introduced for these constraints. Furthermore, the penalty function is appended to the cost functional to form an augmented cost functional, giving rise to an approximate nonlinear parameter optimization problem that can be solved using any gradient-based method. Convergence results indicate that any local optimal solution of the approximate problem is also a local optimal solution of the original problem as long as the penalty parameter is sufficiently large. Finally, an example is provided to illustrate the effectiveness of the developed algorithm.
Starting Page	454
Ending Page	472
Page Count	19
File Format	PDF
ISSN	00223239
Journal	Journal of Optimization Theory and Applications
Volume Number	159
Issue Number	2
e-ISSN	15732878
Language	English
Publisher	Springer US
Publisher Date	2013-04-19
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Parameter tuning Multi-proportional-integral-derivative controllers Optimal control Switched systems Inequality constraints Calculus of Variations and Optimal Control; Optimization Optimization Theory of Computation Applications of Mathematics Engineering Operations Research/Decision Theory
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Control and Optimization Management Science and Operations Research

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