A Computer Aided Design Tool for Control Design, in the Framework of Machine Learning

摘要

The paper proposes an alternative for designing control systems for nonlinear, uncertain plants. The proposed solution requires intensive computer computation, but in the same time it allows a big degree of autonomy to the design algorithm. The controller structure is estimated by an off-line stage. During the on-line operating the controller adapts itself due to its time-varying coefficients.