The effects of active control on the vehicle roll were studied. Based on the theory that distributing the greater roll stiffness to the rear axle can improve tracking trajectory capacity and increase maneuver stabilit...The effects of active control on the vehicle roll were studied. Based on the theory that distributing the greater roll stiffness to the rear axle can improve tracking trajectory capacity and increase maneuver stability, an eight degrees of freedom vehicle model was established and feedforward feedback control strategy was devised to control distribution of lateral load transfer on the front axle and the rear one. Simulation results showed that the proposed control strategy can improve comfort, maneuver stability and safety effectively.展开更多
The hysteresis characteristic is the major deficiency in the positioning control of magnetic shape memory alloy actuator. A Prandtl-Ishlinskii model was developed to characterize the hysteresis of magnetic shape memor...The hysteresis characteristic is the major deficiency in the positioning control of magnetic shape memory alloy actuator. A Prandtl-Ishlinskii model was developed to characterize the hysteresis of magnetic shape memory alloy actuator. Based on the proposed Prandtl-Ishlinskii model, the inverse Prandtl-Ishlinskii model was established as a feedforward controller to compensate the hysteresis of the magnetic shape memory alloy actuator. For further improving of the positioning precision of the magnetic shape memory alloy actuator, a hybrid control method with hysteresis nonlinear model in feedforward loop was proposed. The control method is separated into two parts: a feedforward loop with inverse Prandtl-Ishlinskii model and a feedback loop with neural network controller. To validate the validity of the proposed control method, a series of simulations and experiments were researched. The simulation and experimental results demonstrate that the maximum error rate of open loop controller based on inverse PI model is 1.72%, the maximum error rate of the hybrid controller based on inverse PI model is 1.37%.展开更多
Using linear state feedback and linear feedforward control of the disturbances, the problem of achieving the distrubance rejection in a linear time invariant singular system is treated and a constructive solvability c...Using linear state feedback and linear feedforward control of the disturbances, the problem of achieving the distrubance rejection in a linear time invariant singular system is treated and a constructive solvability condition is presented.展开更多
This paper investigates adaptive state feedback stabilization for a class of feedforward nonlinear systems with zero-dynamics, unknown linear growth rate and control coefficient. For design convenience, the state tran...This paper investigates adaptive state feedback stabilization for a class of feedforward nonlinear systems with zero-dynamics, unknown linear growth rate and control coefficient. For design convenience, the state transformation is first introduced and the new system is obtained. Then, the estimation law is constructed for the unknown control coefficient, and the state feedback controller is proposed with a gain updated on-line. By appropriate choice of the estimation law for the control coefficient and the dynamic gain, the states of the closed-loop system are globally bounded, and the state of the original system converges to zero. Finally, a simulation example is given to illustrate the correctness of the theoretical results.展开更多
文摘The effects of active control on the vehicle roll were studied. Based on the theory that distributing the greater roll stiffness to the rear axle can improve tracking trajectory capacity and increase maneuver stability, an eight degrees of freedom vehicle model was established and feedforward feedback control strategy was devised to control distribution of lateral load transfer on the front axle and the rear one. Simulation results showed that the proposed control strategy can improve comfort, maneuver stability and safety effectively.
基金Project(51105170) supported by the National Natural Science Foundation of ChinaProject supported by the Scientific Research Foundation for the Returned Overseas Chinese Scholars,Ministry of Education,China
文摘The hysteresis characteristic is the major deficiency in the positioning control of magnetic shape memory alloy actuator. A Prandtl-Ishlinskii model was developed to characterize the hysteresis of magnetic shape memory alloy actuator. Based on the proposed Prandtl-Ishlinskii model, the inverse Prandtl-Ishlinskii model was established as a feedforward controller to compensate the hysteresis of the magnetic shape memory alloy actuator. For further improving of the positioning precision of the magnetic shape memory alloy actuator, a hybrid control method with hysteresis nonlinear model in feedforward loop was proposed. The control method is separated into two parts: a feedforward loop with inverse Prandtl-Ishlinskii model and a feedback loop with neural network controller. To validate the validity of the proposed control method, a series of simulations and experiments were researched. The simulation and experimental results demonstrate that the maximum error rate of open loop controller based on inverse PI model is 1.72%, the maximum error rate of the hybrid controller based on inverse PI model is 1.37%.
文摘Using linear state feedback and linear feedforward control of the disturbances, the problem of achieving the distrubance rejection in a linear time invariant singular system is treated and a constructive solvability condition is presented.
基金supported by the National Natural Science Foundations of China under Grant Nos.61104069,61325016,61273084,61374187 and 61473176Independent Innovation Foundation of Shandong University under Grant No.2012JC014
文摘This paper investigates adaptive state feedback stabilization for a class of feedforward nonlinear systems with zero-dynamics, unknown linear growth rate and control coefficient. For design convenience, the state transformation is first introduced and the new system is obtained. Then, the estimation law is constructed for the unknown control coefficient, and the state feedback controller is proposed with a gain updated on-line. By appropriate choice of the estimation law for the control coefficient and the dynamic gain, the states of the closed-loop system are globally bounded, and the state of the original system converges to zero. Finally, a simulation example is given to illustrate the correctness of the theoretical results.
