This paper presents a gain-scheduling model predictive control(MPC) for linear parameter varying(LPV) systems subject to actuator saturation. The proposed gain-scheduling MPC algorithm is then applied to the lateral c...This paper presents a gain-scheduling model predictive control(MPC) for linear parameter varying(LPV) systems subject to actuator saturation. The proposed gain-scheduling MPC algorithm is then applied to the lateral control of unmanned airship.The unmanned airship is modeled by an LPV-type system and transformed into a polytopic uncertain description with actuator saturation. By introducing a parameter-dependent state feedback law, the set invariance condition of the polytopic uncertain system is identified. Based on the invariant set, the gain-scheduling MPC controller is presented by solving a linear matrix inequality(LMI) optimization problem. The proposed gain-scheduling MPC algorithm is demonstrated by simulating on the unmanned airship system.展开更多
基金supported by the National Natural Science Fundation of China(6117507411272205)
文摘This paper presents a gain-scheduling model predictive control(MPC) for linear parameter varying(LPV) systems subject to actuator saturation. The proposed gain-scheduling MPC algorithm is then applied to the lateral control of unmanned airship.The unmanned airship is modeled by an LPV-type system and transformed into a polytopic uncertain description with actuator saturation. By introducing a parameter-dependent state feedback law, the set invariance condition of the polytopic uncertain system is identified. Based on the invariant set, the gain-scheduling MPC controller is presented by solving a linear matrix inequality(LMI) optimization problem. The proposed gain-scheduling MPC algorithm is demonstrated by simulating on the unmanned airship system.
