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Nested Sliding Surface in Robust Neuro Fuzzy Control for a Servomechanism System Regulation

Sep 2026 · International Journal of Combinatorial Optimization Problems and Informatics · Vol 18, pp. 401-417 · 0 citations · 19 references

Abstract

This paper describes the design of a robust neuro-fuzzy control system for regulating a servomechanism, it is based on the development of a nested sliding-mode approach to effectively regulate the system and reduce the chattering effect. The approach involves developing a nested sliding mode control with gain adjustment using adaptive Neuro-Fuzzy Inference. Furthermore, the servomechanism is driven by the voltage applied to a DC motor, and the controlled outputs are the angular position and velocity of the shaft. One key feature of this advanced intelligent control system is its capability to efficiently regulate the position and speed of the servomechanism in an exponential sense, even in the presence of dynamic uncertainties and external disturbances. To this end, in a first step, a conditional nested sliding mode control was developed to reduce the magnitude of chattering effect. However, the magnitude of this conditional controller produces chatering effects on the actuator. To reduce this issue, Adaptive Neuro-Fuzzy Inference System suggests adjusting the control gains of the sliding modes. So, the proposed control scheme helps reduce the magnitude of the chattering effect in the control signal. To validate the proposed control strategy’s effectiveness, a comparative study based on an error criterica study is presented, highlighting its potential on the control process.   AcknowledgmentsOmar Samperio Vázquez, CVU 551623. I would like to express my gratitude to the Autonomous University of the State of Hidalgo for the opportunity to pursue a Doctorate in Automation and Control, and to SECIHTI for the scholarship they awarded me for this program. Spanish-language metadata / Metadatos en españolTítulo en español:Superficie deslizante anidada en el control neurodifuso robusto para la regulación de un sistema servomecanismo Resumen:Este artículo describe el diseño de un sistema de control neurodifuso robusto para la regulación de un servomecanismo, basado en el desarrollo de un enfoque de modos deslizantes anidados para regular eficazmente el sistema y reducir el efecto de chattering. El enfoque consiste en desarrollar un control por modos deslizantes anidados con ajuste de ganancias mediante un sistema de inferencia neurodifuso adaptativo. Asimismo, el servomecanismo es accionado mediante el voltaje aplicado a un motor de corriente continua (DC), mientras que las salidas controladas corresponden a la posición angular y la velocidad del eje. Una característica fundamental de este avanzado sistema de control inteligente es su capacidad para regular eficientemente la posición y la velocidad del servomecanismo con convergencia exponencial, incluso en presencia de incertidumbres dinámicas y perturbaciones externas. Para ello, en una primera etapa se desarrolló un control condicional por modos deslizantes anidados con el propósito de reducir la magnitud del efecto de chattering. Sin embargo, la magnitud de la acción de este controlador condicional genera efectos de chattering en el actuador. Para mitigar este problema, se propone utilizar un Sistema de Inferencia Neurodifuso Adaptativo (ANFIS) para ajustar las ganancias de control de los modos deslizantes. De este modo, el esquema de control propuesto contribuye a reducir la magnitud del efecto de chattering en la señal de control. Para validar la eficacia de la estrategia de control propuesta, se presenta un estudio comparativo basado en criterios de error, destacando su potencial para el proceso de control. Palabras Claves:Control anidado, neurodifuso, servomecanismo. Smart citations:SciteAI. Dimensions.Open Alex.

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