Design And Research On A Hybrid Phase Control Based Lower Limb Exoskeleton

Human augmented exoskeleton is a wearable device which can enhance human muscle ability by actuated unit.These devices have been widely used in military battle,medical rehabilitation and industrial handling.However,the human intention acquirement and human-machine interactive motion are difficulties in the research of exoskeleton.This paper is focused on anthropomorphic design of the lower limb exoskeleton prototype,sensing system and human gait recognition,dynamic model and controller as well as prototype test setup.First,based on the human biomedical structure and the analysis of human motion characteristic,we obtain the design criterions of anthropomorphic lower limb exoskeleton.Then we visualize our mechanical design of each part of the robot.We select the flexion/extension of hip and knee joint in the sagittal plant as active DOF(Degree of Freedom)and install serial elastic actuator in the active DOFs to lower the stiffness of the joints.Gas springs are placed in the abduction/ adduction of hip joint to reduce the load implemented on the pilot.To avoid the singularity of Jacobian Matrix,the knee joint is designed to be angled.The ankle joint utilize the RCM(Remote Center Mechanism)to eliminate the misalignment of the human and robot.In order to satisfy the demand of the control algorithm,we design the sensing system of the exoskeleton,including the measurement of joint angle,torque and orientation,position of the links.Meanwhile,we use multi-axis force/ torque sensors to detect the human-machine interaction.We implement the Kalman filter to fuse the sensing information and reduce the noise.Moreover,by using Kalman filter,we can predict the human intention and compensate for the delay of the control strategy.This paper analyze human gait cycle and divide 5 specific phases of stance phase.To detect the phase of exoskeleton,we design a novel smart shoes with force sensor.Then a new phase detection algorithm is raised by applying COP(Center of Pressure)and it is validated by foot measurement tests.We use D-H coordinate to build the kinematic functions of the exoskeleton and obtain the work space of the simplified link model.Then we use Lagrange Equation to derive the dynamic model of different phase in the gait cycle.A new algorithm called Hybrid Phase Control is proposed based on the dynamic model.This algorithm utilize the interaction information of the end of the links.By using Jacobian Matrix we can obtain the torque in the joint space.Consequently,it forms a close control loop by torque feedback.For increasing the self-adaption of the control system,we introduce sliding mode controller(SMC)which is not sensitive to the parameter change.We further apply the fuzzy gain SMC to slove the chattering problem of the traditional SMC.The simulation of tracking a predefined trajectaory shows good result.Final,a sit-to-stand control based of COP is proposed.We build a lower limb exoskeleton prototype with 15 DOFs.Then we conduct several experiments to test the prototype,including no-load joint rotation test,predefined trajectory tracking test and human-machine interavtive motion test.All these tests shows the coincidence with the theoretical formulations.In conclusion,the proposed control alogrithm is fesible and the prototype performs great mobility.