2020
DOI: 10.1109/tvt.2020.2974979
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Robust Event-Triggered Model Predictive Control for Multiple High-Speed Trains With Switching Topologies

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Cited by 86 publications
(32 citation statements)
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“…Based on nonsingular terminal sliding mode technology and radial basis function neural network, two chatter-free control strategies are proposed to achieve stable tracking control [6]. An event-triggered model predictive control algorithm is designed to solve the tracking control problem with random switching topologies [7]. Energy consumption is also taken into consideration to achieve energy-efficient tracking operation [8][9][10].…”
Section: Introductionmentioning
confidence: 99%
“…Based on nonsingular terminal sliding mode technology and radial basis function neural network, two chatter-free control strategies are proposed to achieve stable tracking control [6]. An event-triggered model predictive control algorithm is designed to solve the tracking control problem with random switching topologies [7]. Energy consumption is also taken into consideration to achieve energy-efficient tracking operation [8][9][10].…”
Section: Introductionmentioning
confidence: 99%
“…However, because the nonlinear system is difficult to describe the internal structure and difficult to control, it is very necessary to simplify the nonlinear subsystems before analyzed. Recently, a piecewise‐affine (PWA) technique has been utilized to approximate the nonlinear systems, and some results have been frequently appeared, see References 12‐16 and the references therein. The main principle of PWA approximation is to decompose the nonlinear space into numerous tiny subspaces, where each subspace is approximated via a PWA region.…”
Section: Introductionmentioning
confidence: 99%
“…By reducing the transmission of the signal, the computation and communication resources can be reduced to guarantee the practicality of the controller [28,33,34,[42][43][44]. Due to the significance of event-triggering in multi-agent consensus systems, event-based control has been integrated into consensus control systems by means of sliding mode control (SMC) [45], a fuzzy logic and back stepping technique [46], model predictive control (MPC) [47], distributed control [20,37,[48][49][50][51][52] and dynamic role assignment [53]. Not only could this save communication resources, it could also save energy.…”
Section: Introductionmentioning
confidence: 99%