Research On The Design Method Of Self-aligning Artificial Knee Joint And Validation Of The Digital Virtual Prototype

Due to the needs of industrial production and the aging of society,research on rehabilitation robots and lower limb exoskeleton technology has remained a focus in recent years.Still,the problem of misalignment between the robot and the human body due to misalignment has not been well addressed.The misalignment of the human-machine system at the knee joint is discussed in this article through an analysis and summary of the top exoskeleton and knee rehabilitation technologies available domestically and internationally,as well as the motions of the human knee joint.A two-degree-of-freedom self-aligning artificial knee joint mechanism and a method of designing for human-machine coordination are proposed to lessen the adverse effects of human-machine misalignment.A control method is created for this system,which is the artificial knee joint with good motion control characteristics and offers an idea for further investigation.The remainder of this essay’s primary work is as follows.A kinematic and mechanical analysis of the human knee joint served as the foundation for the research of the self-aligning prosthetic knee joint.The design of the drive and Human-Robot connecting mechanisms are based on information about human gait and body measurements,while the design of the primary transmission mechanism requires the knowledge of the biological characteristics of the human knee joint’s motion.Using 3D modeling software,the mechanical model of the self-aligning artificial knee joint is created.a kinematic model of the human-Robot coupling is created,by combining the movement characteristics of the human knee joint and kinematic analysis of the self-aligning artificial knee joint,and the misalignment between the Human-Robot is discussed quantitatively.Then the motion trajectory data of the human knee joint is captured through a motion capture test.A particle swarm optimization-based motio N·matching method for human-machine systems is provided to decrease the misalignment.It is based on the real trajectory data together with the kinematic model of the Human-Robot system.The human-Robot matching method is then used to optimize the parameters of key transmission components so that the self-aligning artificial knee joint can exhibit the same motion characteristics as the lower leg during motion to achieve self-alignment.Next,the Lagrange method is used to model the dynamics of the self-aligning artificial knee joint.The parameters of the digital virtual prototype of the artificial knee joint are identified using the kinetic parameter identificatio N·method and the minimum inertia parameter method to get unknown kinetic parameters,and build a nominal model for self-aligning artificial knee joint’s dynamic.A sliding-mode controller is designed for the tracking control of the trajectory based on the dynamic characteristics of the self-aligning knee joint,a multi-input and multioutput mechatronic system,and an RBF neural network is used to approximate the uncertainty of the dynamic parameters.To test the efficacy of the motion trajectory tracking control,a digital virtual prototype of the self-aligned artificial knee joint is constructed in collaboration with Adams & Simulink.The simulation experiment of tracking human trajectory by the digital virtual prototype is then carried out using the human trajectory data as the desired trajectory input.The outcomes demonstrate that the artificial knee joint completes the human-machine matching task,including trajectory tracking and angle self-alignment.