This work deals with the nonlinear control of a marine diesel engine by use of a robust intelligent control strategy based on cerebellar model articulation controller （CMAC）. A mathematical model of diesel engine pr...This work deals with the nonlinear control of a marine diesel engine by use of a robust intelligent control strategy based on cerebellar model articulation controller （CMAC）. A mathematical model of diesel engine propulsion system is presented. In order to increase the accuracy of dynamical speed, the mathematical model of engagement process based on the law of energy conservation is proposed. Then, a robust cerebellar model articulation controller is proposed for uncertain nonlinear systems. The concept of active disturbance rejection control （ADRC） is adopted so that the proposed controller has more robustness against uncertainties. Finally, the proposed controller is applied to engine speed control system. Both the model of the diesel engine propulsion system and of the control law are validated by a virtual detailed simulation environment. The prediction capability of the model and the control efficiency are clearly shown.展开更多
基金the National Natural Science Foundation of China(No.51179102)the China Postdoctoral Science Foundation(No.20110490716)
文摘This work deals with the nonlinear control of a marine diesel engine by use of a robust intelligent control strategy based on cerebellar model articulation controller （CMAC）. A mathematical model of diesel engine propulsion system is presented. In order to increase the accuracy of dynamical speed, the mathematical model of engagement process based on the law of energy conservation is proposed. Then, a robust cerebellar model articulation controller is proposed for uncertain nonlinear systems. The concept of active disturbance rejection control （ADRC） is adopted so that the proposed controller has more robustness against uncertainties. Finally, the proposed controller is applied to engine speed control system. Both the model of the diesel engine propulsion system and of the control law are validated by a virtual detailed simulation environment. The prediction capability of the model and the control efficiency are clearly shown.
