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The control of a pH process is complex because of severe nonlinearities in its behavior. A continuous pH neutralization process is usually represented as a first-order plus dead time system, but its gain varies for different operating points. Therefore, a conventional linear controller cannot be used, and the pH system was thus represented as a linear state-space model around an equilibrium point. This linear model was then used to compute the PID controller gains using robust and optimization techniques like quantitative feedback theory, bacterial foraging technique-based particle swarm optimization algorithm, and genetic algorithm. The corresponding controller gains resulting from the three algorithms were used to control the pH using a reconfigurable I/O device, NI myRIO-1900. Finally, the output time domain specifications and the servo and regulatory responses, resulting from the three algorithms, were compared in simulation and in real-time to deduce the appropriate tuning algorithm for this system.
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