Minimum entropy control for non-linear and non-Gaussian two-input and two-output dynamic stochastic systems

Author(s): J. Zhang ; M. Ren ; H. Wang
DOI: 10.1049/iet-cta.2011.0791

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Author(s): J. Zhang ¹ ; M. Ren ² ; H. Wang ³
- Affiliations: 1: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, People’s Republic of China
  2: School of Control and Computer Engineering, North China Electric Power University, Beijing, People’s Republic of China
  3: Control System Centre, School of Electrical Engineering and Electronics, The University of Manchester, UK
Source: Volume 6, Issue 15, 11 October 2012, p. 2434 – 2441
DOI: 10.1049/iet-cta.2011.0791 , Print ISSN 1751-8644, Online ISSN 1751-8652

In this study, the problem of control algorithm design for a class of nonlinear two-input and two-output systems with non-Gaussian disturbances is investigated, where a general non-linear auto-regressive moving average with exogenous model is used to describe the system. Based on the deduced probability density functions of tracking errors, a new performance index is established using the entropy and joint entropy so as to characterise the uncertainty of the tracking errors of the closed-loop system. This performance also includes the expectations of tracking errors and the constrains of control energy. A recursive optimisation control algorithm is obtained by minimising the performance index. Moreover, the local stability condition of the closed-loop systems is established after some formulations. Finally, the comparative simulation results are presented to show that the performance of the proposed algorithm is superior to that of proportional–integral–derivative controller.

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Minimum entropy control for non-linear and non-Gaussian two-input and two-output dynamic stochastic systems

Minimum entropy control for non-linear and non-Gaussian two-input and two-output dynamic stochastic systems

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