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

Abstract

Servo pneumatic position control has gained considerable attention due to its superiority in improving the precision of automation and mechatronic systems. This paper presents the proposed cascaded fuzzy self-adaptive with proportional, integral, and derivative (CFSAPID) control strategy in providing an accurate rod-piston displacement as desired input with stable pressure in chambers. Unlike the conventional cascade strategy, the control law of proposed CFSAPID was designed based on the Mamdani-type fuzzy approach as a dynamic tuner to each stage in the proportional, integral, and derivative (PID) controller that deals with the nonlinearity of servo pneumatics adequately. The bounder sector zone of Mamdani-type fuzzy was determined based on position and velocity states on servo pneumatic rod-piston, and the parameter was constructed to obtain the optimum gain parameters of PID in each stage. The proposed CFSAPID was verified using a pneumatic proportional valve with a double-acting cylinder dynamic model plant. Simulation and analyses were emphasized on steady-state error, difference in pressures of pneumatic cylinder's chambers, hysteresis effect, tuning parameters convergence, performance criteria, and performance indices. The results show that the proposed CFSAPID controller was able to withstand the load disturbances, at variable input trajectory with a stable pressure in chambers at almost minimum hysteresis effect compared to the FSAPID and single PID controllers.

A Review of Fuzzy Logic Method Development in Hydraulic and Pneumatic Systems

“…The second group includes fuzzy-PD and fuzzy-PID systems, where the fuzzy controller is used to modify the coefficients of the primary PID controller, which controls the position of the actuator via electromagnetic valves. Proposals for such systems were presented by Azahar et al [81,82], Tagosoglu et al [83,84], Gao et al [85], as well as Irawan and Azahar [86]. Furthermore, Hassan et al [87] designed a similar system except using type-2 membership functions in the fuzzy controller.…”

Optimal Pneumatic Actuator Positioning and Dynamic Stability using Prescribed Performance Control with Particle Swarm Optimization: A Simulation Study

“…where 𝜆 𝑛 with 𝑛 = 1, 2, 3. are the coefficients of the friction's dynamics where 𝑛 = 1 denotes the spring bristle factor, 𝑛 = 2 denotes damping bristle factor and viscous friction factor with 𝑛 = 3, further detail regarding this function can be find in [14]. Since the temperature is negligible, the differential equation for both pressure chambers is computed as follows under the adiabatic assumption [12].…”

“…where the 𝜏 is a valve spool time constant and 𝜔 is the valve orifice area gradient. Moreover, the valve orifice effective area are denoted as 𝐴 𝑝𝑣 [14]. The standard length of the connecting tube in the model was assumed to be short enough to be neglected as a significant contributor to the time delay in the PPVDC system.…”

“…Function in (13) will continuously update the current agent's velocity with reference to those reward values. The updating function can be expressed in (14).…”

“…Moreover, some control strategy approaches have been done by engineers and researchers to cater to the PSS issues, such as integration controllers' methods or hybrid techniques, as done in [12], [13]. The other integration methods include cascading control, adaptive control, intelligent control, and optimal control using computational methods [14]- [17]. The Proportional, Integral, and Derivative (PID) control system is a classical control system that is commonly deployed and becomes standard in most systems.…”