a PD-like self-tuning fuzzy controller based on tuning of scaling factors (STFC) by gradient descent method is presented. The tuning scheme allows the tuning of the scaling factors to be on-line. Tuning scaling factors is more effective and simpler than tuning all the parameters of standard fuzzy logic controller (FLC). The aim is to obtain good performance parameters, such as the rise time, the overshoot, the steady-state error. Experimental results of an inverted pendulum system with STFC controller show a better performance in the transient and steady state phases than other classical controllers like PD, PID, auto-tuned PID controller (PID-AT), and linear quadratic regulator (LQR).

a PD-like self-tuning fuzzy controller based on tuning of scaling factors (STFC) by gradient descent method is presented. The tuning scheme allows the tuning of the scaling factors to be on-line. Tuning scaling factors is more effective and simpler than tuning all the parameters of standard fuzzy logic controller (FLC). The aim is to obtain good performance parameters, such as the rise time, the overshoot, the steady-state error. Experimental results of an inverted pendulum system with STFC controller show a better performance in the transient and steady state phases than other classical controllers like PD, PID, auto-tuned PID controller (PID-AT), and linear quadratic regulator (LQR).

a PD-like self-tuning fuzzy controller based on tuning of scaling factors (STFC) by gradient descent method is presented. The tuning scheme allows the tuning of the scaling factors to be on-line. Tuning scaling factors is more effective and simpler than tuning all the parameters of standard fuzzy logic controller (FLC). The aim is to obtain good performance parameters, such as the rise time, the overshoot, the steady-state error. Experimental results of an inverted pendulum system with STFC controller show a better performance in the transient and steady state phases than other classical controllers like PD, PID, auto-tuned PID controller (PID-AT), and linear quadratic regulator (LQR).

ABSTRACT Flow field design in PEM fuel cells has an important influence on both the power density and efficiency of fuel cell systems. In order to effectively utilize the active area, flow distribution and current density should be as homogenous as possible. In addition, pressure losses should be minimized. The main objective of this work is to provide a comprehensive study of the flow field characteristics for different parallel flow channel configurations. The investigated channel configurations are parallel with various cross-sectional configurations. For each channel configuration pressure drop, species mass fraction, velocity, and current distributions are numerically predicted. In addition, performance curves are presented and discussed. The predicted performance parameters are compared with the corresponding available experimental data. Based on the computed results the optimum channel design is selected. Detailed results are presented and discussed. The present work would help PEM fuel cell manufacturers, companies and researchers to choose the optimum configuration for their applications and products to achieve the best possible performance.