The proportional-integral-derivative (PID) controller is widely used in various industrial applications such as process control, motor drives, magnetic and optical memory, automotive, flight control and instrumentation. PID tuning refers to the generation of PID parameters (Kp, Ki, Kd) to obtain the optimum fitness value for any system. The determination of the PID parameters is essential for any system that relies on it to function in a stable mode. This paper proposes a method in designing a predictive PID controller system using particle swarm optimization (PSO) algorithm for direct current (DC) motor application. Extensive numerical simulations have been done using the Mathwork’s Matlab simulation environment. In order to gain full benefits from the PSO algorithm, the PSO parameters such as inertia weight, iteration number, acceleration constant and particle number need to be carefully adjusted and determined. Therefore, the first investigation of this study is to present a comparative analysis between two important PSO parameters; inertia weight and number of iteration, to assist the predictive PID controller design. Simulation results show that inertia weight of 0.9 and iteration number 100 provide a good fitness achievement with low overshoot and fast rise and settling time. Next, a comparison between the performance of the DC motor with PID-PSO, with PID of gain 1, and without PID were also discussed. From the analysis, it can be concluded that by tuning the PID parameters using PSO method, the best gain in performance may be found. Finally, when comparing between the PID-PSO and its counterpart, the PI-PSO, the PID-PSO controller gives better performance in terms of robustness, low overshoot (0.005%), low minimum rise time (0.2806 seconds) and low settling time (0.4326 seconds).

The seawater desalination process is emerging as a substantial source of fresh water by removing salt and minerals from an infinite supply of seawater effectively. The first stage in a desalination plant is the use of chlorine gas to sterilize the microorganisms in the water. During excess chlorine leakage, an alert is activated, employees are relocated away from the site for a specific period, and dampers will be manually opened. This will cause unsafe working conditions and a waste of time. To overcome this problem, this paper proposes a coefficient diagram method based proportional integral derivative (CDM-PID) control strategy for the tune the control parameter with the distributed control system (DCS) interfaced conical tank. During operation, a 10% NaOH solution is injected into the top of the scrubber column using an ethylene-ter-polymer (ETA) designed distributor to ensure that the solution is evenly distributed across the packing surface. The three control strategies are compared to tune the control parameter with the DCS interfaced conical tank. Instead of the sodium hydroxide tank in the chlorine scrubber system, this work presents the pilot plant of DCS interfaced with two conical tank interacting systems with different liquid level heights. Here, the proposed CDM-PID controller is compared with the standard Ziegler-Nichols (ZN)-ultimate cycling method, and the internal model control (IMC) method. The results demonstrated that the proposed CDM-PID approach is superior to existing approaches in terms of low oscillation, settling period, and high robustness.