Sliding mode control on receding horizon: Practical control design and application
| Autor: | Lianhao Yin, Per Tunestål, Gabriel Turesson, Rolf Johansson |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Optimization problem Computer science Noise (signal processing) Applied Mathematics 020208 electrical & electronic engineering SIGNAL (programming language) Linear system 02 engineering and technology Kalman filter Sliding mode control Computer Science Applications Model predictive control 020901 industrial engineering & automation Rate of convergence Control and Systems Engineering Control theory 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering |
| Zdroj: | Control Engineering Practice. 109:104724 |
| ISSN: | 0967-0661 |
| DOI: | 10.1016/j.conengprac.2021.104724 |
| Popis: | Sliding mode control (SMC) is to keep the system to a stable differential manifold. Model predictive control (MPC) calculates the control input by solving an optimization problem on receding horizon. The method of receding horizon sliding control (RHSC) includes the predicted information into the SMC design by combining SMC and MPC. Considering the modeling error and measurement noise, there are model-mismatch and disturbance problems in control practice. This paper combines the demonstrated method of RHSC with a state-augmented Kalman filter addressing the model mismatch and disturbance problem. The proposed scheme has been applied to the air system of an advanced heavy-duty engine. The results have shown the capability of tracking the reference signal during a step-response test and the convergence rate to the target signal is 10% faster than MPC. |
| Databáze: | OpenAIRE |
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