Search

PID controller has still been widely-used in industrial control applications because of its advantages such as functionality, simplicity, applicability, and easy of use. To obtain desired system response in these industrial control appli- cations, parameters of the PID controller should be well tuned by using con- ventional tuning methods such as Ziegler-Nichols, Cohen-Coon, and Astrom- Hagglund or by means of meta-heuristic optimization algorithms which con- sider a fitness function including various parameters such as overshoot, settling time, or steady-state error during the optimization process. Particle swarm op- timization (PSO) algorithm is often used to tune parameters of PID controller, and studies explaining the parameter tuning process of the PID controller are available in the literature. In this study, effects of PSO algorithm parame- ters, i.e. inertia weight, acceleration factors, and population size, on param- eter tuning process of a PID controller for a second-order process plus delay- time (SOPDT) model are analyzed. To demonstrate these effects, control of a SOPDT model is performed by the tuned controller and system response, tran- sient response characteristics, steady-state error, and error-based performance metrics obtained from system response are provided. [ABSTRACT FROM AUTHOR]

Human-robot interaction is inherently available and used actively in ankle rehabilitation robots. This interaction causes disturbances to be counteracted on the rehabilitation robots in order to reduce the side effects. This paper presents a fractional order proportional-integral-derivative controller to improve the trajectory tracking ability of a developed 2-degree of freedom parallel ankle rehabilitation robot subject to external disturbances. The parameters of the controller are optimally tuned by using both the cuckoo search algorithm and the particle swarm optimization algorithm. A traditional proportional-integral-derivative controller, which is also tuned using both of the algorithms, is designed to test the performance of the fractional order proportional-integral-derivative controller. The experimental results show that the optimally tuned FOPID controller improves the tracking performance of the ankle rehabilitation robot subject to external disturbances significantly and decreases the steady-state tracking errors compared to the optimally tuned PID controller. [ABSTRACT FROM AUTHOR]