Nonlinear Model Predictive Control

Related lectures (32)

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Covers the proof of the recursive formula for the optimal gains in LQ control over a finite horizon.

Covers the principles of feedback control systems and their applications in various fields.

Covers Nonlinear Model Predictive Control (NMPC) principles, including setpoint stabilization and Pontryagin's Maximum Principle.

Explores the Model Reference Method for designing PID regulators and cascade controllers for complex systems.

Explores Infinite-Horizon Linear Quadratic (LQ) optimal control, emphasizing solution methods and practical examples.

Explores Dynamic Programming for optimal control, focusing on stability, stationary policy, and recursive solutions.

Explores Linear Quadratic optimal control theory, covering FH-LQ and IH-LQ problems and the importance of observability in control systems.

Explores weight design and stability analysis in multivariable control systems, emphasizing Lyapunov theory and LQR stability.

Explores state-space representation, controllability, observability, and regulator calculation using the Ackermann method.

Covers state representation, controller design, LQR controllers, and optimal control criteria.