Journal
ASIAN JOURNAL OF CONTROL
Volume 18, Issue 1, Pages 122-132Publisher
WILEY
DOI: 10.1002/asjc.1180
Keywords
Active vehicle suspension; fuzzy models; model predictive control; linear matrix inequality; optimization
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This paper proposes a novel method for designing robust nonlinear multivariable predictive control for nonlinear active suspension systems via the Takagi-Sugeno fuzzy approach. The controller design is converted to a convex optimization problem with linear matrix inequality constraints. The stability of the control system is achieved by the use of terminal constraints, in particular the Constrained Receding-Horizon Predictive Control algorithm to maintain a robust performance of vehicle systems. A quarter-car model with active suspension system is considered in this paper and a numerical example is employed to illustrate the effectiveness of the proposed approach. The obtained results are compared with those achieved with model predictive control in terms of robustness and stability.
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