Iterative Data-Driven Controller Tuning with Actuator Constraints and Reduced Sensitivity
- 1 September 2014
- journal article
- research article
- Published by American Institute of Aeronautics and Astronautics (AIAA) in Journal of Aerospace Information Systems
- Vol. 11 (9), 551-564
- https://doi.org/10.2514/1.i010154
Abstract
This paper proposes a novel iterative data-driven algorithm for the data-driven tuning of controllers for nonlinear systems. The iterative data-driven algorithm uses an experiment-based solving of the optimization problems for nonlinear processes, with linear controllers accounting for actuator constraints in terms of a quadratic penalty function approach. A neural network-based identification provides the gradient information used in the search algorithm for controller tuning and ensures a reduced sensitivity with respect to the controller parameters. A case study dealing with the data-driven controller tuning for the angular position control of a nonlinear aerodynamic system is included to validate the new iterative data-driven algorithm.Keywords
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