Imperialist competitive algorithm–based adaptive fuzzy control of a pneumatic actuator

Abstract

This article presents an investigation into the application of a constrained imperialist competitive algorithm with a new penalty function to optimize an adaptive fuzzy proportional–integral–derivative controller for a pneumatic actuator. The integral absolute error and the maximum overshoot of the control system are considered as the cost functions. The constrained imperialist competitive algorithm–based optimization scheme is thus conducted to obtain the best structure of the fuzzy proportional–integral–derivative controller involving optimum shape and location of membership functions and suitable value of scale factors. Then, a simulation study based on the identified model of the pneumatic actuator and three control approaches namely conventional proportional–integral–derivative control, genetic algorithm–based adaptive fuzzy proportional–integral–derivative control and the proposed constrained imperialist competitive algorithm–based adaptive fuzzy proportional–integral–derivative control is carried out to evaluate the performance of the proposed controllers. Finally, an experimental rig is developed to verify the simulation outcomes. It is found that the constrained imperialist competitive algorithm–based fuzzy controller converges faster to an optimum solution compared to the genetic algorithm method. Besides, the superiority of the proposed constrained imperialist competitive algorithm–based design over other controllers is demonstrated.

Structural dynamic modification of an active suspended handle with a parallel coupled piezo stack actuator

“…Meanwhile, the NI 9263 module delivers the voltage signal from the controller to the high-voltage piezo amplifier (E-508.00) and a display module (E-517.i3) is used to monitor the voltage of the piezo stack actuator. The LabVIEW (2012) software is used to develop real-time PID 37 controller programming for the active suspended handle. The I and the D parameters are fixed to unity, and the P parameter is tuned using the proportional feedback gain (P) step-up method 38,39 to generate the voltage for the piezo stack actuator.…”

Identification of nonlinear actuators with time delay and rate saturation using meta-heuristic optimization algorithms

“…It has obtained considerable position in engineering problems. 32,40 Similar to other evolutionary algorithms, it starts with a random population called countries. Some of the best elements are selected as imperialists and the remainder would be colonies.…”

“…Lari et al and Maruta et al 29,30 have utilized meta-heuristic optimization techniques for designing robust controllers. Moreover, in Coelho et al 31 and Ahmadi et al, 32 respectively, cuckoo search algorithm (CSA) and imperialist competitive algorithm (ICA) are exploited to estimate parameters and adaptive controller design. Nowadays, application of these methods is highly noticed by researchers and numerous examples can be found in the literature.…”