Fuzzy Self-Adaptive PID for Pneumatic Piston Rod Motion Control

Cascade Control Strategy on Servo Pneumatic System with Fuzzy Self-Adaptive System

“…The CFSAPID control system strategy was proposed to the targeted PPVDC model plant to produce high precision for the rod-piston position and inner system stability in the servo pneumatic system (Azahar et al 2019). The integration between FSA and PID was the first step of the strategy design, where the FLC algorithm acts as the dynamic tuner for the PID control system parameters (Fig.…”

“…According to Eq. (3), the FSA approach self-tuned the K p , K i , and K d by accumulating the changes in the PID parameter with the initial values, p initial , i initial , and d initial as follows (Azahar et al 2019):…”

“…In this progress, simulations were conducted, and the analyses were made on the comparison between the proposed CFSAPID, FSAPID (Azahar et al 2019), and a single PID controller on the dynamic model of PPVDC. MATLAB ® SIMULINK environment was used with a sampling time of 0.001 s, and the ordinary differential equation (ODE) 4 (Runge-Kutta) was used as the solver.…”

“…As shown in Table 2, optimized initial K p , K i , and K d parameters for PID controller were evaluated using the genetic algorithm (GA) method (Azahar et al 2019). Besides, this optimized PID parameter was also used on the FSAPID and outer-loop CFSAPID controller as the initial PID param- eter as shown in Table 3.…”

“…Fundamentally, this pneumatic system has complicated over some nonlinearity factors due to the inherent problems associated with its natural features. Recently, many studies in this area have been emphasizing on the development of various model-free control approaches to cope with precision in pneumatic positioning with minor computational effort in real-time implementation such as PID-based control (Lai et al 2012;Sy Salim 2012;Salim et al 2013;Syed Salim et al 2014;Saleem et al 2015;Ren et al 2019a), fuzzy logic control (FLC) (Najjari et al 2014; Soares dos Santos and Ferreira 2014; Azahar et al 2019), and even trained neural network (NN)-based control (Dehghan and Surgenor 2013;Abu Mallouh 2019). Model-free control system approach relies on the input-output behavior of the plant without any uncertain parameter as compared to the model-based control almost completely depending on overall plant information.…”