A novel adaptive-gain supertwisting sliding mode controller: Methodology and application

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Adaptive sensor and actuator fault estimation for a class of uncertain Lipschitz nonlinear systems (2016, methodology): “NA4 L2 NC/ ONx C L2 NC Nx C NB1y1 C NB2 C 111 y1; Ox2; u k NB2M NC Ne C N 1 C L1 NC PNx From Equation (9), adding L1 NC PNx to both sides, one gets S PNx D NA4 Nx C NB1y1 C NB2 C 111 y1; x2; u C N N C L1 NC PNx The dynamic behavior of the error trajectories is PNe D S 1 NA4 L2 NC Ne C NB2 C 111 y1; ”
Disturbance-Observer-Based Control for Air Management of PEM Fuel Cell Systems via Sliding Mode Technique (2019, background): “and φ20 is assumed to be bounded and with first derivative bounded [37].”
Adaptive continuous higher order sliding mode control (2016, background): “…rejuvenated interest in this area (Moreno & Osorio (2008)) and the literature expanding these Lyapunov ideas into the realm of adaptive sliding mode control is developing rapidly (Plestan et al. (2010); Alwi & Edwards (2013); Shtessel et al. (2012); Bartolini et al. (2103); Taleb et al. (2013)).”
A novel adaptive high-order sliding mode control based on integral sliding mode (2014, background): “In [29], the gain adaptation problem concerning the over-estimation was investigated in the super-twisting sliding mode control framework, where the gain adaptation algorithm was similar to that in [28].”