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Lecture
Approximate Linearization
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Related lectures (31)
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Convolution and Laplace Transform
Explores control of dynamic systems, impulse response, Laplace transform, and Fourier transform for solving differential equations.
Linear Systems in 2D: Stability
Explores stability in linear 2D systems, covering fixed points, vector fields, and phase portraits.
Introduction to Nonlinear Systems Control
Covers the analysis and control of nonlinear systems, including methods like phase plan and passivity.
Vectorization in Python: Efficient Computation with Numpy
Covers vectorization in Python using Numpy for efficient scientific computing, emphasizing the benefits of avoiding for loops and demonstrating practical applications.
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.
Dynamic Systems: Formalism and Bases
Covers the formalism and bases of dynamic systems, including differential equations and non-linear systems.
Multivariable Control: System Theory and Linear Systems
Introduces multivariable control, covering system theory, linear systems, and time discretization.
Kalman Filter: State Space Models
Introduces the Kalman Filter for estimating the state of a dynamic system from noisy measurements, covering prediction, updating, and filtering steps.
Phase Plan: Linear Order Systems
Discusses phase plans for linear order systems and characterizing trajectories through distinguishing eigenvalues and equilibrium points.
Stability Analysis: Linear Systems
Explores stability analysis in linear systems, emphasizing eigenvalues, eigenvectors, and stable manifolds.
