An approach of dynamic sliding mode control for chemical processes

Herrera, Marco; Camacho, Oscar; Leiva, Hugo; Smith, Carlos A.

doi:10.1016/j.jprocont.2019.11.008

Cited by 58 publications

(31 citation statements)

References 26 publications

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“…En [7,17], se demuestra que TCLab es una plataforma excelente para que los alumnos en cursos introductorios de control puedan identificar modelos y ensayar controladores de tipo Proporcional, Integral y Derivativo (PID). Asimismo, se han publicado algunos trabajos en los que se ensayan técnicas avanzadas con TCLab, como, por ejemplo, control por prealimentación (feedforward ) o control en cascada [6], control predictivo basado en modelo [18] y control deslizante (sliding mode control, SMC) [11].…”

Section: Figura 2 Esquematización Del Modelo Físico Del Sistemaunclassified

Uso del paradigma Take-Home Labs para la enseñanza del control automático en estudios de ingeniería

Hoyo¹,

Mañas²,

Teodoro³

et al. 2021

Xlii Jornadas De Automática : Libro De Actas

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Como alternativa a los laboratorios tradicionales, en los que los estudiantes interactúan con un sistema real cuyo uso tiende a estar limitado por el tiempo y/o el espacio, existe la posibilidad de emplear laboratorios “para llevar a casa” que constituyen un recurso didáctico más flexible. El presente trabajo describe la experiencia en la Universidad de Almería con una plataforma de este tipo que se ha empleado en estudios de grado y postgrado para la enseñanza de técnicas de modelado y control sobre un sistema termodinámico. Su aplicabilidad en otras asignaturas junto a la opinión positiva que se ha percibido del alumnado sugieren que esta podría ser una metodología con un prometedor recorrido por delante.

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Section: Figura 2 Esquematización Del Modelo Físico Del Sistemaunclassified

Uso del paradigma Take-Home Labs para la enseñanza del control automático en estudios de ingeniería

Hoyo¹,

Mañas²,

Teodoro³

et al. 2021

Xlii Jornadas De Automática : Libro De Actas

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“…Therefore, designing an appropriate controller that recognizes and incorporates the extent of nonlinearities is desirable for chemical processes [8], which is the primary purpose of this work. The main difference between GPI control and state feedback control lies in the absence of asymptotic observers [9], that is why GPI Controller proposes a structural state reconstruction [10].…”

Section: Introductionmentioning

confidence: 99%

Regulation of Nonlinear Chemical Processes with Variable Dead Time: a Generalized Proportional Integral Controller Proposal

Chacón¹,

Vallejo²,

Herrera³

et al. 2021

International Journal on Advanced Science, Engineering and Information Technology

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This work shows the development and application of a Generalized Proportional Integral (GPI) Controller based on a FirstOrder Plus Dead Time (FOPDT) approximation for an industrial chemical process. GPI control is a relatively recent advancement in automatic control. Nowadays, several enhancements with the GPI technique come from integral reconstructions of the system states. Chemical engineering processes present numerous challenging control problems, including nonlinear dynamic behavior. GPI can become a new option to consider in industrial applications since, along with the arrival of Industry 4.0, there are many improvements in computers and automation architecture to implement controller algorithms. The new controller's functionality shows significant accessibility of mathematical and logical potential. A comparison between the GPI and a PID controller is made under the same conditions to evaluate their performance. After carrying out some tests, the GPI shows better performance and a smoother controller action when applied to the mixing tank with a variable delay than the PID. Performance indexes as Integral Square Error (ISE) for evaluating the Output Variable and Control Effort Total Variation (TVu) for evaluating the control action are used to measure performance. Finally, designing an appropriate controller like the GPI that recognizes and incorporates nonlinearities is required for chemical processes. Simulations were developed using Simulink-MATLAB.

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“…They approximated the higher order model into the stable FOPDT model to synthesize the SM controller. Recently, Herrera et al [13] used the FOPDT model-based dynamic sliding mode control procedure in a complex CI&A (compensator of Iinoya and Altpeter) structure to control higher-order processes with time delay and inverse response characteristic. Although complex schemes improved the closed loop performance, but for industrial implementation a simple control structure is much preferred.…”

Section: Introductionmentioning

confidence: 99%

“…The literature cited from [6][7][8][9][10][11][12][13] reveals that many researchers have addressed the design of the SM controller for stable processes. However, very few researchers have carried out research in the design of the SM controller for unstable processes.…”

Section: Introductionmentioning

confidence: 99%

Sliding mode controller design for second-order unstable processes with dead-time

Siddiqui

Anwar

Laskar

2020

Journal of Electrical Engineering

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A new approach is proposed to design the sliding mode (SM) controller for the unstable second-order plus dead-time (SOPDT) processes. The sliding mode control consists of two control laws ie continuous control law and discontinuous control law. The continuous control law parameters have been derived in terms of unstable SOPDT process parameters using the root locus technique. On the other hand, the parameters of discontinuous control law are tuned by optimizing a performance index using a recently developed metaheuristic search algorithm, namely the grasshopper optimization technique. The performance index is framed to achieve a good trade-off between performance and control efforts. Finally, simulations are conducted to validate the effectiveness of the proposed approach over the other existing techniques. It is observed that the proposed approach is able to deliver better disturbance rejection, minimal control efforts and good setpoint tracking.

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An approach of dynamic sliding mode control for chemical processes

Cited by 58 publications

References 26 publications

Uso del paradigma Take-Home Labs para la enseñanza del control automático en estudios de ingeniería

Uso del paradigma Take-Home Labs para la enseñanza del control automático en estudios de ingeniería

Regulation of Nonlinear Chemical Processes with Variable Dead Time: a Generalized Proportional Integral Controller Proposal

Sliding mode controller design for second-order unstable processes with dead-time

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