Abstract
This paper presents an efficient covid-19 optimization algorithm to find the optimal values of the PD/PID cascaded controller. The purpose of the control algorithm is to force the link shaft to follow the desired reference position with good accuracy all time. This objective should be achieved for different position/time tracks regardless of load disturbance and parameter variations. This work, simulating how the covid-19 spreads and infects to optimize the parameters of the PD/ PID control. The initial values of PD/PID controller parameters consider the zero patient, which infects new patients (other values of PD/PID controller parameters). The optimization model simulates as accurately as possible the covid-19 activity. The covid-19 has two major advantages compared to other similar strategies. First, the covid-19 parameters are already adjusted according to disease statistics to prevent designers from initializing them with arbitrary values. Second, the approach has the ability to finish after several iterations where the infected population initially grows at an exponential rate. However, after some iterations. The proposed covid-19 was investigated with well-known optimization techniques such as the genetic algorithm (GA) and Harmony Search (HS) optimization. A multi-objective function is used to allow the designer to select the desired rise time, the desired settling time, the desired overshoot, and the desired steady-state error. Several tests have been performed to investigate the obtained proper values of PD/PID controller parameters. In the first test, a step position reference had been applied. In the second test, the continuous change in position reference had been subjected to the robot arm. The results provide that the covid-19 based PD/PID controller has the best performance among other techniques. In addition, the covid-19 based PID controller can track accurately the position command compared to other techniques.
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