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Accelerated Adaptive Backstepping Control of the Chaotic MEMS Gyroscope by Using the Type-2 Sequential FNN
Control acelerado del backstepping adaptativo del giroscopio caótico MEMS por medio de la FNN Secuencial de tipo 2
DOI:
https://doi.org/10.15446/ing.investig.v41n1.85825Keywords:
MEMS gyroscope, type-2 sequential fuzzy neural network, accelerated backstepping control, chaotic oscillation, speed function (en)giroscopio MEMS, red neuronal difusa secuencial de tipo 2, control acelerado de backstepping, oscilación caótica, función de velocidad (es)
In this paper, we propose an accelerated adaptive backstepping control algorithm based on the type2 sequential fuzzy neural network (T2SFNN) for the microelectromechanical system (MEMS) gyroscope with deadzone and constraints. Firstly, the mathematical model of the MEMS gyroscope is established to perform dynamical analyses and controller design. Then, the phase diagrams and Lyapunov exponents are presented to reveal its chaotic oscillation, which is harmful to system stability. In order to suppress oscillations derived from chaos and deadzone, an accelerated adaptive backstepping controller is proposed wherein an adaptive auxiliary is established to compensate the influence of nonsymmetric deadzone on stability performance, along with the T2SFNN designed to approximate unknown functions of dynamic systems. Furthermore, the speed function is introduced to accelerate convergence speed of the control system, and the problem of complex term explosion in traditional backstepping is successfully solved by a secondorder tracking differentiator. Finally, simulation results show that the proposed control scheme can guarantee asymptotic convergence of all signals in the closedloop system, as well as satisfying states constraints and fulfilling the purposes of chaos suppression and accelerated convergence.
En este artículo se propone un algoritmo de control acelerado y autoadaptado de backstepping basado en la red neural analgésica de tipo 2 (T2SFNN) para giroscopios del sistema microeléctrico (MEMS) con zona muerta y limitaciones. En primer lugar, se establece el modelo matemático del giroscopio MEMS para realizar análisis dinámicos y diseño de controladores. Luego, se presentan los diagramas de fase y los exponentes de Lyapunov para revelar su oscilación caótica, que es perjudicial para la estabilidad del sistema. Con el fin de suprimir las oscilaciones derivadas del caos y la zona muerta, se propone un controlador de backstepping adaptativo acelerado en el que se establece un auxiliar adaptativo para compensar la influencia de la zona muerta no simétrica en el rendimiento de estabilidad, junto con el T2SFNN diseñado para aproximar funciones desconocidas de sistema dinámico. Además, se introduce la función de velocidad para acelerar la velocidad de convergencia del sistema de control, y el problema de la explosión de términos complejos en el backstepping tradicional es resuelto exitosamente por un diferenciador de seguimiento de segundo orden. Finalmente, los resultados de la simulación muestran que el esquema de control propuesto puede garantizar la convergencia asintótica de todas las señales en el sistema de circuito cerrado, además de satisfacer las restricciones de los estados y lograr los propósitos de supresión del caos y convergencia acelerada.
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Copyright (c) 2021 Le Zhao, Shao hua Luo, Guan ci Yang, Jun yang Li
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