Model Predictive Control: Mechatronic Applications

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Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Covers the fundamentals of rocket physics, including center of mass, momentum, and rocket speed.

Explores the design and optimization of car suspensions for improved performance.

Covers the Rocket Problem, exploring momentum diagrams, mass relations, rocket thrust, and providing a solution for no external forces.

Explores controlled stochastic processes, focusing on analysis, behavior, and optimization, using dynamic programming to solve real-world problems.

Covers the KKT conditions for optimization with constraints, essential for solving constrained optimization problems efficiently.

Explores variable mass systems, rocket thrust, takeoff conditions, and accelerated frames.

Covers the principles and applications of chemical propulsion systems in space missions.

Explores Nonlinear Model Predictive Control, covering stability, optimality, pitfalls, and examples.

Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.