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Robust optimal predictive control of heavy haul train under imperfect communication
- Source :
- ISA Transactions. 91:52-65
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- With the rapid developments in communication technology, the bidirectional wireless communication channel is widely used to exchange information between the train and wayside control center. As an emerging technology, the communication based heavy haul train control (CBHHTC) system is becoming a better alternative for administrative department to provide the greater transport capacity. In order to put the latest automatic control methods into the practice, this paper investigates the robust optimal control problem of heavy haul train under CBHHTC. By formulating the CBHHTC based real-time control procedure as a networked control system (NCS) model, the possible data loss phenomenon in the wireless communications is considered, and its impact on the stability and performances of the controller design is elaborated. On the basis of Lyapunov stability theory and model predictive control (MPC) approach, a set of linear matrix inequalities (LMIs) is given as sufficient conditions to ensure the velocity tracking ability, energy-efficiency and operational safety with a prescribed H∞ disturbance attenuation level under the control constraints. Case studies are conducted to illustrate the effectiveness of the proposed controller.
- Subjects :
- Lyapunov stability
0209 industrial biotechnology
Automatic control
business.industry
Computer science
Applied Mathematics
020208 electrical & electronic engineering
02 engineering and technology
Data loss
Networked control system
Optimal control
Computer Science Applications
Model predictive control
020901 industrial engineering & automation
Control and Systems Engineering
Control theory
0202 electrical engineering, electronic engineering, information engineering
Wireless
Electrical and Electronic Engineering
business
Instrumentation
Subjects
Details
- ISSN :
- 00190578
- Volume :
- 91
- Database :
- OpenAIRE
- Journal :
- ISA Transactions
- Accession number :
- edsair.doi.dedup.....1a8635b1cedf4506e913286c5f386213
- Full Text :
- https://doi.org/10.1016/j.isatra.2019.01.029