A comparative study of PID based temperature control of CSTR using Genetic Algorithm and Particle Swarm Optimization

Baruah, Swapnadeep; Dewan, Lillie

doi:10.1109/icetcct.2017.8280312

Cited by 14 publications

(10 citation statements)

References 9 publications

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“…Thus, several control strategies have been presented in the open literature, including linear and nonlinear backstepping control, mass concentration regulation controllers, etc. [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

“…The heuristic approach can search large spaces of candidate solutions to identify optimal or near-optimal solutions at a reasonable computational cost, but it is unable to guarantee either feasibility or optimization, and, in many cases, it does not indicate how close a certain feasible solution is to the optimum [33][34][35]. A wide range of direct search methods have been developed from heuristic optimization, such as genetic algorithms, evolutionary programming, differential evolution, genetic programming, evolutionary strategy, particle swarm optimization, and artificial bee colonies [36,37]; however, a theoretical analysis of convergence is not available, which is a major shortcoming [16,38]. A variety of approaches considering uncertainties in the optimization of chemical processes have been reported in the open literature [39,40].…”

Section: Introductionmentioning

confidence: 99%

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A TITO Control Strategy to Increase Productivity in Uncertain Exothermic Continuous Chemical Reactors

2021

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In this manuscript, a two-input two-output (TITO) control strategy for an exothermic continuous chemical reactor is presented. The control tasks of the continuous chemical reactor are related to temperature regulation by a standard proportional-integral (PI) controller. The selected set point increases reactor productivity due to the temperature effect and prevents potential thermal runaway, and the temperature increases until it reaches isothermal operating conditions. Then, an optimal controller is activated to increase the mass reactor productivity. The optimal control strategy is based on a Euler-Lagrange framework, in which the corresponding Lagrangian is based on the model equations of the reactor, and the optimal controller is coupled with an uncertainty estimator to infer the unknown terms required by the proposed controller. As a benchmark, a continuous stirred tank reactor (CSTR) with a Van de Vusse chemical reaction is considered as an application case study. Notably, the proposed methodology is generally applicable to any continuous stirred tank reactor. The results of numerical experiments verify the satisfactory performance of the proposed control strategy.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A TITO Control Strategy to Increase Productivity in Uncertain Exothermic Continuous Chemical Reactors

2021

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“…Sliding mode control also plays a critical role in suppressing the oscillation of the electric machine system [6]. In previous studies [7,8], particle swarm optimization technology was used to solve problems in complex linear processes, reduce overshoot percentage, and maintain CSTR temperature at steady-state operating points. Further, the PID controller with predictive components significantly improved the control quality and reduced the maximum deviation of process parameters from the specified value in [9].…”

Section: Introductionmentioning

confidence: 99%

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

Ouyang

Wang

2020

Complexity

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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.

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“…Conventional PID (proportional-integral-derivative) output feedback controllers have been traditionally applied to CSTR for temperature regulation due to their simplicity in terms of design and their robust performance to model uncertainties. Recent work on PID control for CSTR is presented in Banu and Uma (2008) and Baruah and Dewan (2017). Analytic studies on input-output linearizing control applied to continuous stirred tank reactors have been extensively carried out in Jouili et al (2008), Barkhordari Yazdi and Jahed-Motlagh (2009) and Tofighi et al (2017).…”

Section: Introductionmentioning

confidence: 99%

Temperature and concentration control of exothermic chemical processes in continuous stirred tank reactors

Vlahakis

Halikias

2019

Transactions of the Institute of Measurement and Control

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Exothermic chemical reaction taking place in continuous stirred tank reactor is considered. Heat release from the chemical reaction, non-linear dynamic behavior of the process and uncertainty in parameters are the main factors motivating the use of robust control design. Viewing temperature and molar concentration as variables both accessible in real time, PI and optimal state-feedback controllers driven by temperature and concentration error signals are proposed to regulate the system over reactor’s steady-state working points by counteracting undesired disturbances. Since access to concentration value has proved beneficial for the reactor’s performance, estimation techniques are examined to compensate for the problematic nature of the concentration’s measurement. A linear reduced-order observer is first proposed to estimate the concentration value using temperature measurements. In addition, assuming concentration measurement is available with a relatively short delay via sample analysis, a linear and non-linear discrete-time predictor is constructed to estimate the concentration’s real-time value. A linear combination of the two estimation schemes (observer, predictor) is proposed resulting in a combined estimator, in which the emphasis between the two individual schemes can be controlled via a scalar parameter. The work presented in this paper was supported by the GLOW project – New weather-stable low gloss powder coatings based on bifunctional acrylic solid resins and nanoadditives – as part of the development of novel and efficient processing technologies regarding the production of new families of powder coatings, responding to industrial requirements for quality improvement at lower cost and shorter development cycles.

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A comparative study of PID based temperature control of CSTR using Genetic Algorithm and Particle Swarm Optimization

Cited by 14 publications

References 9 publications

A TITO Control Strategy to Increase Productivity in Uncertain Exothermic Continuous Chemical Reactors

A TITO Control Strategy to Increase Productivity in Uncertain Exothermic Continuous Chemical Reactors

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

Temperature and concentration control of exothermic chemical processes in continuous stirred tank reactors

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