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Lecture
Control Theory Fundamentals
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Related lectures (32)
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Learning and Control for Complex Systems
Explores learning and control for complex systems, addressing challenges and opportunities in technology and interdisciplinary research.
Nonlinear Model Predictive Control
Explores Nonlinear Model Predictive Control, covering stability, optimality, pitfalls, and examples.
Linear Quadratic (LQ) Optimal Control: Proof of Theorem
Covers the proof of the recursive formula for the optimal gains in LQ control over a finite horizon.
Linear Control Systems
Covers the reduction of complex systems to linear situations and controllability conditions.
SISO Polynomial Controllers: Sylvester Matrix, Internal Model Principle
Covers the design of SISO polynomial controllers using concepts such as the Sylvester matrix and model matching.
Networked Control Systems: Fundamentals and Stability Analysis
Covers the fundamentals and stability analysis of Networked Control Systems, including software installation, dynamical systems, equilibrium states, and stability testing.
Linear Quadratic Optimal Control: Theory and Applications
Explores Linear Quadratic optimal control theory, covering FH-LQ and IH-LQ problems and the importance of observability in control systems.
Controlled Stochastic Processes
Explores controlled stochastic processes, focusing on analysis, behavior, and optimization, using dynamic programming to solve real-world problems.
Stability: Poles, Zeros, and Control
Covers stability, poles, zeros, and control in dynamic systems, emphasizing the importance of observability.
Meromorphic Functions & Differentials
Explores meromorphic functions, poles, residues, orders, divisors, and the Riemann-Roch theorem.
