Adaptive neural dynamic surface sliding mode control for uncertain nonlinear systems with unknown input saturation

Abstract

In this article, an adaptive neural dynamic surface sliding mode control scheme is proposed for uncertain nonlinear systems with unknown input saturation. The non-smooth input saturation nonlinearity is firstly approximated by a smooth non-affine function, which can be further transformed into an affine form according to the mean value theorem. Then, one simple sigmoid neural network is employed to approximate the uncertain nonlinearity including the input saturation, and the approximation error is estimated using an adaptive learning law. Virtual controls are designed in each step by combing the dynamic surface control and integral sliding mode technique, and thus the problem of complexity explosion inherent in the conventional backstepping method is avoided. With the proposed control scheme, no prior knowledge is required on the bound of input saturation, and comparative simulations are given to illustrate the effectiveness and superior performance.

Mechanical design and robust tracking control of a class of antagonistic variable stiffness actuators based on the equivalent nonlinear torsion springs

“…The inequality 0 ≤ | η | − η tanh ( η false/ ε ) ≤ 0 . 2785 ε holds for any ε > 0 and for any η ∈ R . 41…”

“…The inequality 0 ł h j j À h tanh h=e ð Þł 0:2785e holds for any e . 0 and for any h 2 R. 41 Considering the state estimation errorsj qm (m = 1, 2, 3, 4, 5) andj kejn (n = 1, 2, 3), and invoking the system (33), the following descriptions can be obtained…”

Observer-based event-triggered adaptive neural control for time-delay nonlinear systems with input saturation and external disturbances

“…In Wang et al (2020), a novel auxiliary system was constructed to handle the adverse influence caused by input delay. In Chen et al (2016) and Wang et al (2019), an anti-saturation function was constructed to compensate for the magnitude and rate of saturation. However, the usage of network resources has not been considered in the above-mentioned references, which may increase the burden of communication bandwidth.…”

“…Due to the existence of input constraints, the actual controller cannot be obtained at the current time in the process of the controller design. In Chen et al (2016) and Wang et al (2020), an auxiliary system and an anti-saturation function were used to overcome the difficulties of input delay and saturation, respectively. However, to the authors' best knowledge, the problem of dealing with input delay and saturation simultaneously still needs to be further investigated.…”

Optimal dynamic output feedback control of Lipschitz nonlinear systems under input saturation

“…The input saturation is inevitable in many practical systems because of the safety constraints and physical limitations of actuators Sun and Zhang (2021). If the input saturation is neglected in control design, the designed controller may degrade the system performance or even lead to its instability Chen et al (2016). For this reason, significant attention has been paid to control systems with input saturation and various theoretical results have been proposed in the literature Rehan et al (2016); Alaviyan Shahri et al (2018); Rahimi and Binazadeh (2020); Shahri et al (2020); Yu et al (2018); Ma et al (2019); Yang and Li (2019); Mohammadi and Alfi (2019).…”