Adaptive model‐based event‐triggered sliding mode control

Abstract

This paper addresses the design of a model-based event-triggered sliding mode control strategy of adaptive type. The overall proposal can be regarded as a networked control scheme, because one of the design objectives is to reduce the number of transmissions of the plant state over the network used to construct the control loop. The key idea consists in using the actual plant state or the state of a suitably updated nominal model of the plant to generate the control variable, depending on the magnitude of the sliding variable. The proposed adaptive control scheme proves to be capable of steering the sliding variable to a boundary layer of the sliding manifold in finite time, in spite of the presence of bounded uncertainties with unknown bounds. When the sliding variable is confined within the boundary layer, the nominal model state is used to compute the control variable. Then, a continuous control can be analytically determined and applied, which provides a beneficial chattering alleviation effect. The proposed networked control scheme is theoretically analyzed and assessed in simulation with satisfactory results.

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Event-Triggered Sliding Mode Control algorithms for a class of uncertain nonlinear systems: experimental assessment

“…The control law (10), and the triggering condition (7) give rise to the Event-Triggered SMC (ET-SMC) strategy (Strategy 1). Its aim is to steer the sliding variable σ (x(t)) to a boundary layer B λ 1 , defined as a vicinity of the sliding manifold, i.e.,…”

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