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Robust Interactive PID Controller Design for Medical Robot System

Shaymaa M. Mahdi, Safanah M. Raafat

发表年份
2021
引用次数
6
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摘要

In this paper, the design and application of robust interactive PID control for a medical robot system is presented. The aim is to solve the problem of precise position tracking required for human walking, using a simple type of control while taking into account the interactions of the systems' input and outputs. The medical robot system can be interpreted as pendulum links to obtain a complete motion of all muscles. Two control actions are required to be applied for the two joints. The interactions of this multivariable system have been examined using the relative gain array (RGA). In this work, PID and Fuzzy PID controllers are implemented with interactions effects. In addition, two other non-conventional types of PID control structures have been considered for comparison, where the RGA cannot be applied. These are the two-degree PID (2DoFPID) and nonlinear PID (NPID) controllers. Simulation results show that in the case of not considering the interaction effects, the Fuzzy PID controller can provide an improvement of 44% as compared with conventional PID controller. While this improvement has been increased to 70% with the consideration of interaction effects. Meanwhile, NPID controller shows higher rise and settling times (almost more than 2 seconds for the settling time). While 2DoFPID controller shows difficulty in implementation due to its highly chattered control signals with higher overshoots in the transient response as compared with the results of the interactive Fuzzy PID controller. Finally, robustness against disturbances and system uncertainties has been tested with all the developed controllers. It has been concluded that the interactive Fuzzy PID controller achieves better performance in terms of less ISE, settling time, rise time, and overshoot.

关键词

Computer sciencePID controllerControl engineeringController (irrigation)RobotControl theory (sociology)Control (management)Artificial intelligenceTemperature control

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