Learning and Control for Complex Systems

Related lectures (31)

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Covers the design and analysis of multivariable control systems, focusing on stability and zero steady-state tracking error.

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

Covers compliant and force control for robots using Dynamical Systems.

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

Explores compliant control for robots through impedance and variable stiffness, enabling safe and adaptive interactions with the environment.

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

Covers the computation of tracking performance and transfer functions in digital control systems.

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

Explores obstacle avoidance using Dynamical Systems for robots, focusing on modulation, stability guarantees, and contraction theory.

Covers the structure theorem for state-space representations and companion forms.