Control System Of Parallel Robot Research Articles

A trajectory planning algorithm for a multi-degree-of-freedom parallel robot based on NURBS research and simulation

Parallel robots are small in size and high in accuracy, so they are widely used in processing and production industries. In order to give full play to the characteristics of high-speed motion of parallel robots, trajectory planning has become a hot spot in the industry. This paper proposes a trajectory planning algorithm based on NURBS. Firstly, the algorithm uses the characteristics of NURBS continuous and derivable to fit interpolation points, and then we obtain a smooth and continuous robot motion trajectory. Secondly, It uses interpolation algorithm to discretize the curve to get the robot motion sequence. Finally, It completes the entire motion process of the robot in three-dimensional space. Experiments show that the algorithm can be applied to the parallel robot control system, which can give full play to the performance of the parallel robot and ensure the stable and high-speed operation of the robot.

Design of A Three-DOF Redundantly Driven Parallel Robot Control System

Parallel robot has advantages of no friction and clearance, fast response, compact structure, good rigidity, and low error accumulation, but they also have many shortcomings in geometric characteristics, such as small range of motion, poor flexibility, and singularity in the workspace. Adding redundancy can improve its geometric characteristics. Parallel robots are usually controlled by dedicated controllers, without openness, high development costs, and long cycles. This paper introduces the design of an open control system for a three-DOF redundant drive robot based on PC bus, and with "PC + motion control card" as the core.

Adaptive PID control of multi-DOF industrial robot based on neural network

The control system of parallel robot, especially industrial robot, is a very complex multi-modal nonlinear system, which has the characteristics of time-varying, strong coupling and strong nonlinearity. Trajectory tracking control algorithm is a very important part of industrial robot control system. It is required that the algorithm can realize the continuous tracking of each joint of the robot and the processing and tracking of the desired trajectory. However, due to the strong influence of acceleration and speed on the trajectory tracking of industrial robots, the corresponding control difficulty and control accuracy are seriously affected. Based on the core idea of fuzzy neural network algorithm, the functional relationship between control error and arrival degree is established to improve the control quality of industrial robots. At the same time, combining with the PID feedforward control algorithm, the self-adaptive adjustment of PID parameters is realized, and the accuracy of the tracking algorithm is improved. In order to verify the superiority of the proposed trajectory tracking control algorithm over the traditional PID algorithm, the model of industrial robot is established by using the virtual simulation system Adams. At the same time, the model is simulated by joint experiment. Experimental results show that the trajectory control algorithm based on the proposed trajectory control algorithm is effective. This method has good control accuracy and stability.

Adaptive Fuzzy Sliding Mode Control for Hydraulic Servo System of Parallel Robot

The hydraulic servo control system, which is the important component of parallel robot, is a high order, nonlinear, dynamic asymmetry, parameter uncertain system, which seriously affect dynamic performance of robot, so it is very difficult to gain good performance with traditional control. Based on sliding mode variable structure control method combined with fuzzy control and adaptive control, an adaptive fuzzy sliding mode control algorithm was presented by taking the Stewart platform servo control system of parallel robot as the research object, and the uncertain term of the sliding mode controller was approximated with adaptive fuzzy control method. The simulation results showed that compared with the conventional PID control applied to the same hydraulic control system, the new controller has a strong robustness, good traceability with regard to model uncertainties, unknown external disturbances and changes in the operation conditions, as well as much better adaptive characteristics. The simulation results also showed that the adaptive fuzzy sliding mode control system can solve the dynamic asymmetrical performance and poor stability of parallel robot, and can greatly improve the robot control precision. DOI : http://dx.doi.org/10.11591/telkomnika.v12i6.5087