Abstract
In this paper, a novel optimal control method with the analytical solution strategy is developed for a wide class of nonlinear systems with input constraints. First, an equivalent constrained optimisation problem is formulated by performing a quadratic performance index including the control inputs and the predicted tracking errors. Then, the problem is analytically solved by using the Kerush-Kuhn-Tucker (KKT) theorem to find the optimal control law. For comparison, a computational technique based on calling the genetic algorithm (GA) is also provided to online solving the developed optimisation problem. The proposed control method with two solutions is applied on a mathematical example and a chemical reactor which is a multi-input multi-output (MIMO) system. The results show that the proposed KKT-based predictive controller is effective from different aspects. Importantly, it is very fast, easy to solve and suitable for online implementation compared with the conventional nonlinear model predictive control (NMPC) method.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
