Optimal hybrid scheme of dynamic neural network and PID controller based on harmony search algorithm to control a PWM-driven pneumatic actuator position

Mazare, Mahmood; Taghizadeh, Mohammad Javad; Kazemi, Mohammad Ghasem

doi:10.1177/1077546317707102

Cited by 29 publications

(21 citation statements)

References 32 publications

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“…This friction model is similar to those studied in [14][15][16]. It has the advantage of capturing more of the complex behavior of the actuator's friction than the ones used in [1][2][3][4][5][6][7][8][9][10][11][12].…”

Section: System Modelmentioning

confidence: 98%

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Position Control of Pneumatic Actuators Using Three-Mode Discrete-Valued Model Predictive Control

Bone

Zhang³

2019

Actuators

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A novel discrete-valued model-predictive control (DVMPC) algorithm termed DVMPC2 for the position control of pneumatic actuators using inexpensive on/off valves is presented. DVMPC2 includes a more flexible cost function, an improved prediction strategy, and other improvements. The actuator is a double-acting cylinder with two on/off solenoid poppet valves connected to each chamber. To reduce the switching frequency and prolong the valve life, DVMPC2 directly switches the valves when necessary, instead of using relatively high-frequency pulse-width modulation. Experimental comparisons are made with the state-of-the-art sliding-mode control (SMC) algorithm and the previous DVMPC algorithm. The comparisons are based on the five performance metrics: integral of time-weighted absolute error (ITAE), root mean square error (RMSE), overshoot (OS), steady-state error (SSE), and valve switches per second (SPS). The robustness is evaluated by increasing and decreasing the total mass of the moving components while keeping the controller parameters constant. The experimental results show that the proposed algorithm is superior to the previous DVMPC and outperformed SMC by a wide margin. Specifically, DVMPC2 reduced ITAE by 80%, RMSE by 52%, OS by 43%, and SPS by 20% relative to SMC. There was no clear winner in terms of SSE.

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Section: System Modelmentioning

confidence: 98%

“…On/off valves can be controlled using either pulse-width modulation (PWM), e.g., [1][2][3][4], or direct switching, e.g., [5][6][7][8][9][10][11][12]. PWM has the advantage of approximating the desirable flow behavior of a proportional valve.…”

Section: Introductionmentioning

confidence: 99%

Position Control of Pneumatic Actuators Using Three-Mode Discrete-Valued Model Predictive Control

Bone

Zhang³

2019

Actuators

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“…and compare with the ADRCS version, u bR control, given by equation (13). The controller parameters have the values k 1 = 28, k 2 = 1.8, and k 3 = 0.4.…”

Section: A Pd Controller With a Discontinuous Function Of The Positiomentioning

confidence: 99%

Application of the active disturbance rejection control structure to improve the controller performance of uncertain pneumatic actuators

Almeida¹,

Álvarez

Cárdenas³

2019

Asian Journal of Control

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In many robotic applications, pneumatic actuators are not adequate for tracking control tasks given the poor performance obtained with traditional control techniques like PID controllers. In this paper we show that the so-called Active Disturbance Rejection Control Structure (ADRCS), combined with a discontinuous observer and standard or robust algorithms in the controller block, provides a good solution to regulation and tracking control problems of pneumatic actuators. The discontinuous observer estimates the velocity, and whose discontinuous nature permits to estimate also the disturbances affecting the system, allowing to use a very simple model of the actuator and avoiding an off-line parameter identification. To analyze the observer ability to estimate the disturbances, we test three different algorithms in the controller block, the standard PD and two discontinuous controllers proposed elsewhere. The performance of the closed loop system is evaluated through experimental results using a performance index based on an  2 norm, for constants and sinusoidal references. Also, we compare the performance of the proposed algorithms with the controllers with those using the same control algorithm but not including the disturbance compensation, showing the important effect of the disturbance estimation included in the ADRCS on the overall controller performance.

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“…Otro importante grupo de trabajos está enfocado a proponer estrategias de control, con cierto grado de robustez, que resuelven el problema de control de fuerza o de posición, algunos ejemplos son (Song and Ishida (1997)), (Richer and Hurmuzlu (2000b)), (Rubio et al (2007)), (Mohd Fuaad et al (2012)), (Prieto et al (2015)), (Mazare et al (2017)), (Tuvayanond and Parnichkun (2017)) y (Zhao et al (2017)). También hay publicaciones que presentan estudios completamente experimentales sobre el desempeño de sistemas de posicionamiento neumático bajo diferentes acciones de control, un ejemplo destacado es (Rahman and Sepehri (2017)).…”

Section: Introductionunclassified

“…Sin embargo, como el control que se diseña es un controlador de fuerza, los errores de seguimiento no se pueden relacionar en forma directa con errores en la posición de la carga sujeta al cilindro neumático. En (Mazare et al (2017)) se propone un controlador basado redes neuronales dinámicas y un controlador PID para el control de un actuador neumático manejado por modulación por ancho de pulso (PWM). En este trabajo se considera un modelo no lineal que incluye la dinámica del mecanismo y de las presiones en la válvula; se utiliza el algoritmo de armonía para resolver el problema de optimozación.…”

Section: Introductionunclassified

Control Robusto de un Actuador Neumático Basado en la Estructura de Control con Compensación Activa de Perturbaciones para Seguimiento de Trayectorias

Almeida¹,

Cárdenas²,

Díaz³

et al. 2019

Rev. iberoam. autom. inform. ind.

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<p>Se propone una estrategia para resolver el problema de seguimiento de trayectorias en actuadores neumáticos inciertos y con medición parcial del vector de estado. La estrategia se basa en la estructura de control con compensación activa de perturbaciones (ADRC), que está formada por un observador de estado, un filtro pasa bajas y un controlador. En esta propuesta se utiliza un observador de estado discontinuo que estima el vector de estado completo y, utilizando el concepto del control equivalente, permite estimar los términos de perturbación presentes en la planta. El filtro pasa bajas se encarga de recuperar el control equivalente a partir de un término discontinuo del observador. Finalmente, el controlador tiene la estructura básica PD con un término adicional, que corresponde a las perturbaciones estimadas, y que tiene como fin compensar las perturbaciones reales en la planta. El rendimiento del sistema en lazo cerrado se evalúa mediante un índice de desempeño basado en la norma L2.</p>

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Optimal hybrid scheme of dynamic neural network and PID controller based on harmony search algorithm to control a PWM-driven pneumatic actuator position

Cited by 29 publications

References 32 publications

Position Control of Pneumatic Actuators Using Three-Mode Discrete-Valued Model Predictive Control

Position Control of Pneumatic Actuators Using Three-Mode Discrete-Valued Model Predictive Control

Application of the active disturbance rejection control structure to improve the controller performance of uncertain pneumatic actuators

Control Robusto de un Actuador Neumático Basado en la Estructura de Control con Compensación Activa de Perturbaciones para Seguimiento de Trayectorias

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