In this article,a nonlinear optimal control approach is proposed for the dynamic model of 3-DOF four-cable driven parallel robots(CDPR).To solve the associated nonlinear optimal control problem,the dynamic model of th...In this article,a nonlinear optimal control approach is proposed for the dynamic model of 3-DOF four-cable driven parallel robots(CDPR).To solve the associated nonlinear optimal control problem,the dynamic model of the 3-DOF cable-driven parallel robot undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method.The linearization relies on Taylor series expansion and on the associated Jacobian matrices.For the linearized state-space model of the 3-DOF cable-driven parallel robot a stabilizing optimal(H-infinity)feedback controller is designed.To compute the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm.The stability properties of the control method are proven through Lyapunov analysis.The proposed nonlinear optimal control approach achieves fast and accurate tracking of reference setpoints under moderate variations of the control inputs and a minimum dispersion of energy.展开更多
基金supported by Grant Ref.“Ref 301022”-“Nonlinear optimal and flatness-based control methods for complex dynamical systems”of the Unit of Industrial Automation of the Industrial Systems Institute。
文摘In this article,a nonlinear optimal control approach is proposed for the dynamic model of 3-DOF four-cable driven parallel robots(CDPR).To solve the associated nonlinear optimal control problem,the dynamic model of the 3-DOF cable-driven parallel robot undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method.The linearization relies on Taylor series expansion and on the associated Jacobian matrices.For the linearized state-space model of the 3-DOF cable-driven parallel robot a stabilizing optimal(H-infinity)feedback controller is designed.To compute the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm.The stability properties of the control method are proven through Lyapunov analysis.The proposed nonlinear optimal control approach achieves fast and accurate tracking of reference setpoints under moderate variations of the control inputs and a minimum dispersion of energy.
