Controlling the temperature reactor based on Raspberry Pi system control

Ate, Abdelrahim; Abdelrahim, Mohamed

doi:10.1109/iceee2.2018.8391333

Cited by 2 publications

(1 citation statement)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many advanced control strategies have been proposed to control the process. In previous studies [1][2][3][4], evolutionary algorithms were used to effectively suppress interference, adjust the temperature of the CSTR, and improve the robustness of the raspberry PI control, event-driven sliding mode control, and fuzzy control. Fuzzy logic plays a key role in diagnosing induction motor faults [5].…”

Section: Introductionmentioning

confidence: 99%

Optimization and Realization of the Continuous Reactor with Improved Automatic Disturbance Rejection Control

Ouyang

Wang

2020

Complexity

View full text Add to dashboard Cite

In the chemical production process, the temperature of the continuous reactor has nonlinear characteristics such as large inertia. An improved autodisturbance control method is proposed. By improving the tracking differentiator with adjustable parameters, the expanded state observer and the control structure obtained an improved automatic disturbance rejection control model and realized the optimal control of the nonlinear and large-delay systems. On the process control training system, the experiment of the continuous system process flow is compared with the anti-interference of the Smith predictive compensation system, which uses an optimal set of data. The reactor temperature fluctuates, but the self-resistance is improved. The optimal overshoot of the disturbance is close to 0. Compared with the original antidisturbance controller, the antidisturbance time is not affected by the number of iterations, which reduces the high requirements on the accuracy of the parameters. Therefore, the improved automatic disturbance rejection control improves the operation and enhances the ability to resist external disturbance that changes the controlled object.

show abstract

Section: Introductionmentioning

confidence: 99%