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Generalized Discrete-time nonlinear disturbance observer based fuzzy model predictive control for boiler–turbine systems
- Source :
- ISA Transactions. 90:89-106
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- The boiler-turbine system (BTS) is usually subject to the tight input constraint, the strong nonlinearity and the complex disturbance, which makes the control a challenging task To this end, a disturbance observer based fuzzy model predictive control (DOBFMPC) scheme is proposed for the BTS in this paper. The generalized discrete-time nonlinear disturbance observer (GDNDO) is first developed to estimate the higher-order disturbance by systematically extending the conventional nonlinear disturbance observer. The GDNDO exhibits a series structure of the internal states, and can precisely estimate the disturbance if its order is equal to or greater than that of the disturbance In addition, a baseline fuzzy model predictive control (FMPC) law is synthesized on the fuzzy model. With FMPC, the asymptotic stability is guaranteed, and meanwhile the input constraints are satisfied by both the free control variables and the future control inputs in the form of the state feedback law. At last, the disturbance estimate and the FMPC are applied to constitute the DOBFMPC law. With the proper design of the disturbance compensation gain, the disturbance influence is removed from the output channels by the composite DOBFMPC law at the steady state. Simulations for a 300 MW subcritical BTS well demonstrate the effectiveness of the proposed control scheme.
- Subjects :
- 0209 industrial biotechnology
Disturbance (geology)
Steady state (electronics)
Series (mathematics)
Computer science
Applied Mathematics
020208 electrical & electronic engineering
Control variable
02 engineering and technology
Computer Science Applications
Nonlinear system
Model predictive control
020901 industrial engineering & automation
Exponential stability
Discrete time and continuous time
Control and Systems Engineering
Control theory
0202 electrical engineering, electronic engineering, information engineering
Electrical and Electronic Engineering
Instrumentation
Subjects
Details
- ISSN :
- 00190578
- Volume :
- 90
- Database :
- OpenAIRE
- Journal :
- ISA Transactions
- Accession number :
- edsair.doi.dedup.....ca919063288f89a3ba8154ddc3c4aac2