Study On Dynamics And Control Of 2-DOF Parallel Mechanisms With Hybrid Actuation

Hybrid actuation machine systems have two types of motors: constant velocity motor (CV) and servo regulated velocity motor. The hybrid actuation machine combines the power of the traditional motors with the programming and real time controllability of modern servo motors. Hybrid actuation systems provide a middle ground between the traditional inflexible machines and the modern flexible robots. Study on the hybrid actuation machine will be extremely promising.In the paper, the features and development of hybrid actuation machine system were presented, the control system design of the hybrid machine and the use of intelligent control technology in parallel mechanism were analyzed. The study contents mostly included forward kinematics and inverse kinematics, electromechanical coupling dynamic model, control system design, intelligent control technology in parallel mechanism and tracking experiments of the 2-DOF redundant parallel mechanism.Forward kinematics analysis and inverse kinematics analysis provide a theory basis for the study on dynamic model and the control system design. In order to study the interaction between the geometry of a hybrid machine and the motions of that system, a kinematics model is modeled. At the same time, the Jacobian matrix was calculated and the velocity characteristic of the end-effector was analyzed. Comparing the influence parameters including structure parameters, adjustable parameters and controlled parameters, the trend of different parameters influence on the velocity characteristic of hybrid actuation machine was obtained and the sensitive parameters were found. The blindness of optimal design can be reduced and the efficiency of the optimization can be raised. The objective of the inverse kinematics is to determine the motion in the joints to achieve a desired trajectory at the end-effector. In the case of a hybrid actuation mechanism, the process of the inverse kinematics is to determine the corresponding angular motion of the servo motor, such as the angle, angular velocity and angular acceleration, given the trajectory of the end-effector and the angular velocity of the CV motor. The velocity on the constant velocity motor is constant, so it is must be considering the characteristic when modeling the inverse kinematics model. In this paper, the inverse kinematics model including the time is different from the path generation in the mechanism design. Simulation results showed the motion trajectory on the servo motor could be obtained through the solution to the inverse kinematics model.Dynamic deals with the relationship between the input torque of motors and the displacements, velocities, and accelerations of the parts of the system. Dynamic model is the basis of the dynamic analysis and synthesis. In order to develop an effective controller for optimal trajectory tracking performance, the dynamics of a mechanism must be thoroughly analyzed. Both the dynamic model of the mechanical system and that of the motors were established and then integrated into an electromechanical coupling dynamic model. By means of the Lagrange method one can obtain the dynamic model of the mechanical system. Using the Newtonian kinematics law the torque equation for the motor dynamics can be expressed. Two dynamic models are integrated via torque pass. Simulation study showed that the dynamic model was accurate which was necessary for the development of suitable control strategies.Due to the complexity of the dynamic model of a hybrid actuation mechanism and the uncontrollable nature of the CV motor, the control of this structure is a challenging and difficult task. As a result, developing a special control strategy for the hybrid machine is necessary. We presented a new iterative controller which was based on a new concept to "inform" velocity fluctuation in the CV motor to the controller of the servo motor. This study differed from those existing ones in that a CV motor (not any substituted one by the servo motor) was used in the hybrid actuation mechanism system. The general strategy for controlling the hybrid actuation mechanism is therefore to model the propagated speed fluctuation in the CV motor and incorporate it into a controller designed for the servomotor. The CV motor is not real-time programmable. Such fluctuation which can not be attenuated by the CV motor itself due to the lack of a control system in the CV motor will be propagate to the end-effector. Since the dynamic model is a high coupled system, the actual trajectory of the end-effector may offset the desired trajectory due to the speed fluctuation in the CV motor. Using the proposed controller, the angular velocity fluctuation in the CV motor can be calculated and be feedback to the desired angular displacement of the servo motor. This is a way to "pass" the velocity fluctuation on the CV motor to the servo motor. In this case, the fluctuation is "gradually" mapped to the fluctuation on the servo motor. The trajectory can be adjusted over again and can be controlled. By the way the controller for servo motor can compensate the disturbance propagated from the CV motor due to its speed fluctuation. The disadvantage effect with the speed fluctuation of the CV motor can be further reduced. Simulation results showed that this new controller is much better than the one previously developed.In comparison to their serial counterparts, parallel structures have high stiffness, high motion accuracy and high load-structure ratio. Due to their advantages over serial structure mechanisms, parallel structure mechanisms have been receiving increasing interest from both academia and industries in recent years. In order to obtain optimal trajectory tracking performance, more advanced control theory are required. Compound intelligent control method is advanced to overcome the nonlinear of system. Intelligent control is a new automation technique which uses various intelligent strategies to realize the control of complicated system. Accurate trajectory control of a robot is essential in practical use of robot. The paper presented an adaptive PID control algorithm based on radial basis function (RBF) neural network and neural network sliding mode control algorithm with adjustable parameter for trajectory tracking of a 2-DOF parallel mechanism. Simulation results showed that the control algorithms can accurately track given trajectories of a 2-DOF parallel mechanism. The results also indicated that the system robustness and tracking performance are superior to the classic PID method and the classic sliding mode control. Comparison illustrated that the neural network control techniques can be used to improve the trajectory tracing performance.The dynamic characteristic analysis and the tracking experiment of the 2-DOF redundant parallel mechanism were discussed. The high precision trajectory tracking of the redundant parallel mechanism was realized by adjusting the control parameters.