IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING

This paper proposes an off-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. The aim of this research is to obtain the best hydrogen partial pressure (PH2) value using FPGA emulator to design and implement a digital PID controller that track the fuel cell output voltage during a variable load current applied. The off-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID controller parameters that improve the dynamic behavior of the closed loop digital control fuel cell system and to achieve the stability of the desired output voltage of fuel cell. The numerical simulation results (MATLAB) package and FPGA emulator experimental work show the performance of the proposed FPGA-PID controller in terms of voltage error reduction and generating optimal value of the (PH2) control action without oscillation in the output and no saturation state when these results are compared with other control methodology.

The network congestion is an essential problem that leads to packets
losing and performance degradation. Thus, preventing congestion in the
network is very important to enhance and improve the quality of service. Active
queue management (AQM) is the solution to control congestion in TCP network
middle nodes to improve theire performance. We design a linear quadratic
(LQ)-servo controller as an AQM applied to TCP network to control congestion
and attempt to achieve high quality of service under dynamic network
environments. The LQ-servo controller is proposed to provide queue length
stabilization with a small delay and faster settling time. The designed controller
parameters are tuned by using the particle swarm optimization (PSO) method.
The PSO algorithm was fundamentally applied to find the optimal controller
parameters Q and R, such that a good output response could be obtained. The PI
controller is examined for comparison reasons. The MATLAB simulation result
shows that the controller is more effective than the PI in reaching zero steadystate
error with better congestion avoidance under the dynamic network
environment. Moreover, the proposed controller achieves a smaller delay and
faster settling time.

Abstract –This paper presents an on-line nonlinear trajectory tracking control algorithm for differential wheeled mobile robot using optimal back-stepping technique based particle swarm optimization while following a pre-defined continuous path. The aim of the proposed feedback nonlinear kinematic controller is to find the optimal velocity control action for the real mobile robot. The particle swarm optimization algorithm is used to find the on-line optimal parameters for the proposed controller based on the Lyapunov criterion in order to check the stability of the control system. Simulation results (Matlab) and experimental work (LabVIEW) show the effectiveness and robustness of the proposed on-line nonlinear kinematic control algorithm. This is demonstrated by minimizing tracking error and obtaining smoothness of the optimal velocity control signal, especially with regards to the external disturbance attenuation problem.


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Keywords:- Mobile Robots, Nonlinear Kinematic Controller, Back-Stepping Technique, Particle Swarm Optimization, Trajectory Tracking, Matlab package, LabVIEW package.