State-estimation-based adaptive sliding mode control of uncertain switched systems: A novel linear sliding manifold approach

Lin, Luxin; Liu, Zhen

doi:10.1016/j.isatra.2020.11.004

Cited by 7 publications

(1 citation statement)

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“…Although, in the recent decades issues concerning switched systems such as sliding mode control (SMC) in the assessment of stability and stabilization (Jing et al, 2011), robust H∞ sliding mode control (Lian et al, 2009), SMC of switched systems with faults in actuator (Liu et al, 2014), SMC of time-delayed switched systems (Wu and Lam, 2008), integral SMC of non-linear switched systems (Lian et al, 2010), SMC of discrete switched systems (Yu et al, 2013), intelligent fuzzy and neural networks control (Faria et al, 2014; Singh and Sukavanam, 2012), State-estimation-based ASMC (Lin and Zhen, 2020), the SMC of switched systems with signal quantization and actuator nonlinearity (Cheng et al, 2020), have been the focus of many researchers. But the topic of model reference ASMC using RBFNN is still an open and wide discussion.…”

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confidence: 99%

Adaptive sliding mode control of switched linear systems using disturbance observer based on the RBF neural network

Hosseini

Noei

2022

Journal of Vibration and Control

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This study deals with analyze of an adaptive sliding model controller for a class of switched linear systems in the context of model reference adaptive control (MRAC) using RBF neural network (RBFNN) with the aid of disturbance observer (DO). For this purpose, adaptive laws and switching rules are designed. These are constructed based on tracking error and sliding mode control, together with using time-dependent switching conceptualizations. A DO is used to estimate the external disturbance with an adaptive RBFNN which is applied to obtain the external disturbance upper bound estimation, combined with an adaptive sliding mode control (ASMC) under the identic Lyapunov stability framework. The switching rules are based on dwell time (DT) and average dwell time (ADT) switching. The ASMC updates the system dynamics so that it assures the proposed closed-loop switched linear system stability via fast switching, resulting in the form of globally uniformly ultimately bounded (GUUB) stability. The convergence of the process of updating the weights in the adaptive RBFNN and the boundedness of updated estimates of weights are satisfied. Achieving the state tracking, robustness, reducing the chattering problem and anti-disturbance performance are the main objectives. Moreover, switching rules based on the mode-dependent approaches have been developed, which can allow faster switching as compared to switching rules based on the DT and ADT. Finally, to evaluate the efficiency of the obtained theoretical results, the controller and the proposed method have been tested on the electro-hydraulic system (EHS).

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