Motion Planning And Adaptive Control For Robotic Exoskeleton

With the rapid development of robotics,the auxiliary robot that realizes the motion assist for people has become an important frontier branch in robot research.As an auxiliary robot,robotic exoskeleton can achieve the rehabilitation treatment for the disabled and the motion assist for the normal person.The application of robotic exoskeleton has been gradually extended to medical,military,transportation and other fields.The research on the movement of robotic exoskeleton needs to focus on the problems of performance.Improving the performance of the robotic exoskeleton can meet the needs of the wearer to achieve the complex motion tasks.And establishing a reasonable and efficient motion planning and motion tracking control strategy are keys to the improvement of the performance of robotic exoskeleton.Due to the particularity of the structure and usage pattern of the robotic exoskeleton,there are some limitations in the direct application of the traditional motion planning and tracking control strategy to the robotic exoskeleton.For example,the traditional motion planning strategy does not consider the limitations of system dynamics and driving capability,so it can not improve the motion performance of the robotic exoskeleton.In addition,the traditional motion control strategy is not comprehensive in terms of system model,input saturation constraints,unknown disturbances and other aspects,which may lead to problems such as weak robustness and poor tracking performance.Based on the difficulties mentioned above,the thesis focuses on the research work on the motion planning and tracking control of the robotic exoskeleton.The main research contents can be summarized as follows:1.Aiming at the poor performance of traditional method of motion planning due to the neglect of the system dynamics and driving capability,a global motion planning scheme based on system dynamics is proposed in the thesis.The scheme we proposed considers the kinematics of the robot system,meanwhile,the system dynamics,joint drive capability and actual physical constraints of the robot system have been considered in this motion planning scheme.Then,the motion planning problem is transformed into a global optimization problem with nonlinear constraints.In order to solve such global optimization problem,the thesis utilizes a global optimization algorithm based on level set.The obtained motion trajectory satisfies the requirements of performance and lays the foundation for the subsequent motion control design.2.Aiming at the problem that the effect of control and robustness cannot be guaranteed due to the uncertainty of the system model,input saturation constraint and unknown disturbance in the robot system in the motion control of the robotic exoskeleton,an adaptive control strategy based on high dimensional vector integral Lyapunov function is proposed in the thesis.The closed-loop stability of the system can be ensured with the high-dimensional vector integral Lyapunov function-based control strategy.The asymmetry,nonlinearity and saturation constraints of the joint actuator have been considered in the control strategy.Meanwhile,combined with the disturbance observer and the adaptive neural network model approximation,the control scheme achieves effective tracking of the trajectory of the robotic exoskeleton.The motion planning and adaptive control scheme we proposed have been verified on the platforms of upper and lower robotic exoskeleton.Simulation and experimental results verified the effectiveness and practicability of the strategies proposed in this thesis.The motion planning strategy and adaptive control strategy proposed in the thesis provide an effective technical support for the robotic exoskeleton to gradually meet the various complex motion requirements of the wearer.