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This article presents a nonlinear model of the continuous weighing conveyor system as considering the delay time of material transport, and then given a novel two-loop control strategy based on PID combined with fuzzy logic: inner velocity control loop and outer mass flowrate control loop. Then, two designed controllers for the velocity and mass flowrate control loops are simulated and evaluated in MATLAB. After that, experimental setup of real-time weighing conveyor system is built in the UTC's laboratory. Finally, these controllers are installed into PLC to control the material mass flowrate following on the reference input. The simulation and experimental results show that the proposed fuzzy-PID algorithm is right and able to improve the material mass flowrate control quality in industrial continuous weighing conveyor system using PLC controller.

The paper presents a novel control strategy applying the particle swarm optimization (PSO) algorithm to optimize the scaling weights coefficients of the fuzzy-PID controller for the resistance furnace temperature control system, called PSO-based fuzzy-PID controller/ algorithm. The proposed PSO-based fuzzy-PID controller in this paper consist of the fuzzy-PID controller and the PSO algorithm. The proposed fuzzy-PID controller is combination of the advantage of PID control and fuzzy logic control. Firstly, the paper presents the mathematical model of the resistance furnace by identification method, based on the experimental data. Then, the design of the fuzzy-PID controller is given in this study. And then, the paper presents the design of the temperature control board using PIC16f with the installed PSO-based fuzzy-PID algorithm. Finally, the simulation and experimental results proved the stability of the proposed PSO-based fuzzy-PID controller with the disturbance, improved the furnace temperature control quality, through obtained major control criteria, such as overshoot, steady-state error, settling time, rising time.

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