PD-RMPC for a flexible air-breathing hypersonic vehicle with input saturation and state constraints

This paper describes the design of parameter dependent robust model predictive controller (PD-RMPC) for a class of flexible air-breathing hypersonic vehicles. The strong system uncertainties, high nonlinearity, strong coupling, input saturation and flight state constraints are challenging problems in the design of control system. Therefore, a control method that can handle model uncertainties and perturbations while adhering to strict flight constraints is necessary. The nonlinear dynamic model with aerothermoelastic mode is transformed into linear parameter varying (LPV) model, and then Tensor-Product model transformation technology is applied to obtain the convex hull representations of LPV model. Based on linear matrix inequalities (LMIs), a novel parameter dependent robust model predictive control algorithm by are presented for the LPV model with input saturation and state constraints. The proposed control strategy not only addresses the issue of stability robustness with respect to parametric model uncertainty and aerothermoelastic mode, but also explicitly deals with system constraints and guarantees the control and state are within their limits. Finally, the numerical simulation results proved availability of the proposed method.