Abstract
This paper presents a new control strategy for a class of non-Gaussian stochastic systems so that the output probability density function (PDF) of the system can be made to follow a desired PDF. The system considered is represented by an Nonlinear AutoRegressive and Moving Average with eXogenous (NARMAX) inputs with input channel time-delay and non-Gaussian noise. A multi-step-ahead nonlinear cumulative cost function is used to improve tracking performance. For this purpose, a relationship between the PDFs of all the inputs and the PDFs of multiple-step-ahead output is formulated by constructing an auxiliary multivariate mapping. By minimizing this performance function, a new explicit predictive controller design algorithm is established with less conservatism than some previous results. Furthermore, an improved approach is developed to guarantee the local stability of the closed-loop system by tuning the weighting parameters recursively. Simulations are given to demonstrate the effectiveness of the proposed control algorithm and desired results have been obtained.
Original language | English |
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Pages (from-to) | 1904-1911 |
Number of pages | 8 |
Journal | Automatica |
Volume | 44 |
Issue number | 7 |
DOIs | |
State | Published - Jul 2008 |
Externally published | Yes |
Keywords
- Non-Gaussian systems
- Nonlinear systems
- Optimal control
- Probability density functions
- Stability analysis
- Stochastic control
- Time-delay systems