04000nam a22005775i 4500 978-981-97-8167-6 DE-He213 20251030114552.0 cr nn 008mamaa 241129s2024 si | s |||| 0|eng d 9789819781676 978-981-97-8167-6 10.1007/978-981-97-8167-6 doi TJ212-225 TJ210.2-211.495 TJFM bicssc TEC007000 bisacsh TJFM thema Munasinghe, Sudath Rohan. author. aut http://id.loc.gov/vocabulary/relators/aut 88268 Optimization and Optimal Control in a Nutshell [electronic resource] / by Sudath Rohan Munasinghe. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. XVII, 127 p. 45 illus., 34 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Engineering Optimization: Methods and Applications, 2731-4057 1. Unconstrained Function Optimization -- 2. Constrained Function Optimization -- 3. Unconstrained Functional Optimization -- 4. Constrained Functional Optimization -- 5. Continuous Time Optimal Control -- 6. Linear Quadratic Regulator -- 7. Optimal Control with Pontryagin’s Maximum Principle -- 8. Discrete-time Optimal Control -- 9. Model Predictive Control. This book concisely presents the optimization process and optimal control process with examples and simulations to help self-learning and better comprehension. It starts with function optimization and constraint inclusion and then extends to functional optimization using the calculus of variations. The development of optimal controls for continuous-time, linear, open-loop systems is presented using Lagrangian and Pontryagin-Hamiltonian methods, showing how to introduce the end-point conditions in time and state. The closed-loop optimal control for linear systems with a quadratic cost function, well-known as the linear quadratic regulator (LQR) is developed for both time-bound and time-unbounded conditions. Some control systems need to maximize performance alongside cost minimization. The Pontryagin's maximum principle is presented in this regard with clear examples that show the practical implementation of it. It is shown through examples how the maximum principle leads to control switching and Bang-Bang control in certain types of systems. The application of optimal controls in discrete-time open-loop systems with the quadratic cost is presented and then extended to the closed-loop control, which results in the model predictive control (MPC). Throughout the book, examples and Matlab simulation codes are provided for the learner to practice the contents in each section. The aligned lineup of content helps the learner develop knowledge and skills in optimal control gradually and quickly. Control engineering. Robotics. 59148 Automation. 59149 Discrete mathematics. Mathematical optimization. 65522 Control, Robotics, Automation. Discrete Mathematics. Optimization. 65528 SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819781669 Printed edition: 9789819781683 Printed edition: 9789819781690 Engineering Optimization: Methods and Applications, 2731-4057 87009 https://doi.org/10.1007/978-981-97-8167-6 ZDB-2-INR ZDB-2-SXIT 65326 65326