Presents a control strategy for underactuated mechanical system: the acrobot example, which combines fuzzy control and linear quadratic control. The fuzzy controller designed for the upswing ensures that the energy of...Presents a control strategy for underactuated mechanical system: the acrobot example, which combines fuzzy control and linear quadratic control. The fuzzy controller designed for the upswing ensures that the energy of the acrobot increases with each swing. After the acrobot enters a neighborhood of the unstable straight up equilibrium position, a linear quadratic regulator is designed to balance it.展开更多
A control strategy based on a combination of fuzzy control and linear quadratic control to control the acrobot is presented. The control torque to swing up is directly derived based on the energy of the acrobot. A fuz...A control strategy based on a combination of fuzzy control and linear quadratic control to control the acrobot is presented. The control torque to swing up is directly derived based on the energy of the acrobot. A fuzzy controller is designed to regulate the amplitude of the control torque from the energy during the upswing. After the acrobot enters a neighborhood of the straight up equilibrium position, a linear quadratic regulator is designed to balance it. The proposed control strategy simplifies the control of the acrobot and achieves better performance. The simulation results show the validity of the control strategy.展开更多
文摘Presents a control strategy for underactuated mechanical system: the acrobot example, which combines fuzzy control and linear quadratic control. The fuzzy controller designed for the upswing ensures that the energy of the acrobot increases with each swing. After the acrobot enters a neighborhood of the unstable straight up equilibrium position, a linear quadratic regulator is designed to balance it.
文摘A control strategy based on a combination of fuzzy control and linear quadratic control to control the acrobot is presented. The control torque to swing up is directly derived based on the energy of the acrobot. A fuzzy controller is designed to regulate the amplitude of the control torque from the energy during the upswing. After the acrobot enters a neighborhood of the straight up equilibrium position, a linear quadratic regulator is designed to balance it. The proposed control strategy simplifies the control of the acrobot and achieves better performance. The simulation results show the validity of the control strategy.