A robust predictive control design for nonlinear active suspension systems. (English) Zbl 1338.93147
Summary: 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.
MSC:
| 93B40 | Computational methods in systems theory (MSC2010) |
| 93B35 | Sensitivity (robustness) |
| 93C95 | Application models in control theory |
| 93C15 | Control/observation systems governed by ordinary differential equations |
Keywords:
active vehicle suspension; fuzzy models; model predictive control; linear matrix inequality; optimizationReferences:
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