Multiple model adaptive control for a class of nonlinear systems with unknown control directions

ABSTRACT

This study introduces an improved multiple model adaptive control (MMAC) algorithm for a class of nonlinear discrete-time systems. The controller consists of a linear direct adaptive controller, a neural network-based nonlinear direct adaptive controller and a switching mechanism. The assumption of the nonlinear term is relaxed by incorporating a parameter estimator with an augmented error. The control direction of the system is not required to be known by employing a linear direct adaptive controller with the discrete Nussbaum gain and future output predictions. The stability of the closed-loop systems applying the proposed MMAC method is proved and the improved transient performance of the system is illustrated by the simulation results.

KEYWORDS:

• Unknown control directions
• discrete-time nonlinear systems
• multiple models
• adaptive controller

Acknowledgments

This work is supported by the National Nature Science Foundation of China (No. 61633019, 61272020, 61673268]; Zhejiang Provincial Natural Science Foundation of China (No. LZ15F030004); Ningbo Science and Technology Plan Project (No. 2014B82015); Research Programs of Educational Commission Foundation of Zhejiang Province of China (No. Y201636903); Open problem project of State Key Laboratory of Industrial Control Technology (No. ICT170285); Shanghai Sailing Program (No. 17YF1413100).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work is supported by the National Nature Science Foundation of China (No. 61633019, 61272020, 61673268]; Zhejiang Provincial Natural Science Foundation of China (No. LZ15F030004); Ningbo Science and Technology Plan Project (No. 2014B82015); Research Programs of Educational Commission Foundation of Zhejiang Province of China (No. Y201636903); Open problem project of State Key Laboratory of Industrial Control Technology (No. ICT170285); Shanghai Sailing Program (No. 17YF1413100).