scholarly journals Optimal Operation of High-Speed Trains Using Hybrid Model Predictive Control

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Yingze Yang ◽  
Zheng Xu ◽  
Weirong Liu ◽  
Heng Li ◽  
Rui Zhang ◽  
...  
Keyword(s):  
Linear System ◽  
Model Predictive Control ◽  
Hybrid Model ◽  
Predictive Control ◽  
High Speed ◽  
Piecewise Linear ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Piecewise Linear System ◽  
Train Operation

The high-speed train operation process is highly nonlinear and has multiple constraints and objectives, which lead to a requirement for the automatic train operation (ATO) system. In this paper, a hybrid model predictive control (MPC) framework is proposed for the controller design of the ATO system. Firstly, a piecewise linear system with state and input constraints is constructed through piecewise linearization of the high-speed train’s nonlinear dynamics. Secondly, the piecewise linear system is transformed into a mixed logical dynamical (MLD) system by introducing the auxiliary binary variables. For the transformed MLD system, a hybrid MPC controller is designed to realize the precise control under hard constraints. To reduce the online computation complexity, the explicit control law is computed offline by employing the mixed-integer linear programming (MILP) technique. Simulation results validate the effectiveness of the proposed method.

Derivation and Simulation Results of a Hybrid Model Predictive Control for Water Purge Scheduling in a Fuel Cell

2009 ◽  
Author(s):  
Giulio Ripaccioli ◽  
Jason B. Siegel ◽  
Anna G. Stefanopoulou ◽  
Stefano Di Cairano
Keyword(s):  
Fuel Cell ◽  
Model Predictive Control ◽  
Hybrid Model ◽  
Predictive Control ◽  
Optimization Procedure ◽  
Gas Diffusion ◽  
Lookup Table ◽  
Mixed Integer ◽  
Multiparametric Optimization ◽  
Embedded Controller

This paper illustrates the application of hybrid modeling and model predictive control techniques to the water purge management in a fuel cell with dead-end anode. The anode water flow dynamics are approximated as a two-mode discrete-time switched affine system that describes the propagation of water inside the gas diffusion layer, the spilling into the channel and consequent filling and plugging the channel. Using this dynamical approximation, a hybrid model predictive controller based on on-line mixed-integer quadratic optimization is tuned, and the effectiveness of the approach is shown through simulations with a high-fidelity model. Then, using an off-line multiparametric optimization procedure, the controller is converted into an equivalent piecewise affine form which is easily implementable even in an embedded controller through a lookup table of affine gains.

scholarly journals Data-Driven Koopman Model Predictive Control for Optimal Operation of High-speed Trains

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Bin Chen ◽  
Zhiwu Huang ◽  
Rui Zhang ◽  
Weirong Liu ◽  
Heng Li ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
High Speed ◽  
Optimal Operation ◽  
Data Driven ◽  
High Speed Trains

Chaos in a manifold piecewise linear system

1981 ◽  
Vol 64 (10) ◽  
pp. 9-17 ◽  
Author(s):  
Toshimichi Saito ◽  
Hiroichi Fujita
Keyword(s):  
Linear System ◽  
Piecewise Linear ◽  
Piecewise Linear System

scholarly journals Hybrid Model Predictive Control of a Variable Displacement Engine Mode Management

2020 ◽  
Vol 53 (2) ◽  
pp. 14047-14054
Author(s):  
Pawel Majecki ◽  
Michael J. Grimble ◽  
Ibrahim Haskara ◽  
Chen-Fang Chang
Keyword(s):  
Model Predictive Control ◽  
Hybrid Model ◽  
Predictive Control ◽  
Variable Displacement
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