This paper outlines an algorithm for controller reconfiguration for non-linear systems, based on a combination of a multiple model estimator and a generalized predictive controller. A set of models is constructed, each corresponding to a different operating condition of the system. The interacting multiple model estimator, extended for systems with offset, is utilized to yield a reconstruction of the state of the non-linear system and mode probabilities of the different models in the model set. Based on this information, a standard cost function in predictive control is optimized under the assumption that the mode probabilities are constant over the maximum costing horizon. The algorithm is illustrated for two different case studies — one with a linear model of one joint of a space robot manipulator, subjected to failures, and one with a non-linear model of the inverted pendulum on a cart.
- Generalized predictive control
- Fault detection
- Nonlinear Systems
- Fault-tolerant systems