As an innovative concept,an optimal predictive impedance controlle is introduced here to control a lower limb rehabilitation robo in the presence of uncertainty.The desired impedance law is considered to propose a con...As an innovative concept,an optimal predictive impedance controlle is introduced here to control a lower limb rehabilitation robo in the presence of uncertainty.The desired impedance law is considered to propose a conventional model-based impedance controller for the LLRR.However,external disturbances,model imperfection,and parameters uncertainties reduce the performance of the controller in practice.In order to cope with these uncertainties,an optimal predictive compensator is introduced as a solution for a proposed convex optimization problem,which is performed on a forward finite-length horizon.As a result,the LLRR has the desired behavior even in an uncertain environment.The performance and efficiency of the proposed controller are verified by the simulation results.展开更多
In this paper,an adaptive observer for robust control of robotic manipulators is proposed.The lumped uncertainty is estimated using Chebyshev polynomials.Usually,the uncertainty upper bound is required in designing ob...In this paper,an adaptive observer for robust control of robotic manipulators is proposed.The lumped uncertainty is estimated using Chebyshev polynomials.Usually,the uncertainty upper bound is required in designing observer-controller structures.However,obtaining this bound is a challenging task.To solve this problem,many uncertainty estimation techniques have been proposed in the literature based on neuro-fuzzy systems.As an alternative,in this paper,Chebyshev polynomials have been applied to uncertainty estimation due to their simpler structure and less computational load.Based on strictly-positive-rea Lyapunov theory,the stability of the closed-loop system can be verified.The Chebyshev coefficients are tuned based on the adaptation rules obtained in the stability analysis.Also,to compensate the truncation error of the Chebyshev polynomials,a continuous robust control term is designed while in previous related works,usually a discontinuous term is used.An SCARA manipulator actuated by permanent magnet DC motors is used for computer simulations.Simulation results reveal the superiority of the designed method.展开更多
文摘As an innovative concept,an optimal predictive impedance controlle is introduced here to control a lower limb rehabilitation robo in the presence of uncertainty.The desired impedance law is considered to propose a conventional model-based impedance controller for the LLRR.However,external disturbances,model imperfection,and parameters uncertainties reduce the performance of the controller in practice.In order to cope with these uncertainties,an optimal predictive compensator is introduced as a solution for a proposed convex optimization problem,which is performed on a forward finite-length horizon.As a result,the LLRR has the desired behavior even in an uncertain environment.The performance and efficiency of the proposed controller are verified by the simulation results.
文摘In this paper,an adaptive observer for robust control of robotic manipulators is proposed.The lumped uncertainty is estimated using Chebyshev polynomials.Usually,the uncertainty upper bound is required in designing observer-controller structures.However,obtaining this bound is a challenging task.To solve this problem,many uncertainty estimation techniques have been proposed in the literature based on neuro-fuzzy systems.As an alternative,in this paper,Chebyshev polynomials have been applied to uncertainty estimation due to their simpler structure and less computational load.Based on strictly-positive-rea Lyapunov theory,the stability of the closed-loop system can be verified.The Chebyshev coefficients are tuned based on the adaptation rules obtained in the stability analysis.Also,to compensate the truncation error of the Chebyshev polynomials,a continuous robust control term is designed while in previous related works,usually a discontinuous term is used.An SCARA manipulator actuated by permanent magnet DC motors is used for computer simulations.Simulation results reveal the superiority of the designed method.
