Minimal control synthesis adaptive control of nonlinear systems: utilizing the properties of chaos

Author(s):  
M di Bernardo ◽  
D.P Stoten

This paper discusses a novel approach to the control of chaos based on the use of the adaptive minimal control synthesis algorithm. The strategies presented are based on the explicit exploitation of different properties of chaotic systems including the boundedness of the chaotic attractors and their topological transitivity (or ergodicity). It is shown that chaos can be exploited to synthesize more efficient control techniques for nonlinear systems. For instance, by using the ergodicity of the chaotic trajectory, we show that a local adaptive control strategy can be used to synthesize a global controller. An application is to the swing-up control of a double inverted pendulum.

Author(s):  
D P Stoten ◽  
M G Dye ◽  
M Webb

The minimal control synthesis (MCS) algorithm is an adaptive control strategy that requires no prior knowledge of plant dynamic parameters, and yet is guaranteed to provide global asymptotic stability of the closed-loop system. The purpose of this paper is to present MCS as applied to web tension und transport control a class of plant that has highly non-linear dynamics and time-varying parameters. The plant is difficult to control by conventional methods over its full operating range. A typical example and model of such a plant is presented along with the implementation of MCS. Experimental comparisons of MCS with conventional control benchmarks are provided. It will be seen that MCS significantly outperforms the conventional controller.


2003 ◽  
Vol 13 (03) ◽  
pp. 677-684 ◽  
Author(s):  
XIAO FAN WANG ◽  
M. DI BERNARDO ◽  
D. P. STOTEN ◽  
M. H. LOWENBERG ◽  
G. CHARLES

The aim of bifurcation tailoring is to design an appropriate control law such that the controlled system has a desired bifurcation diagram. After describing two open-loop bifurcation tailoring techniques, this paper proposes a new open-loop plus close-loop bifurcation tailoring method based on a combination of the Newton-flow algorithm and the minimal control synthesis (MCS) adaptive control strategy. This method is applied to the Duffing system as an illustrative example.


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