Lectures related to State Space Control: Discrete Systems

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

Explores signals, instruments, and systems, covering ADC, Fourier Transform, sampling, signal reconstruction, aliasing, and anti-alias filters.

Covers the state-space representation of systems and models in process control.

Covers the design of a regulator and state estimator for optimal control.

Explains Nyquist stability criteria and loop shaping for system performance and robustness.

Covers the concepts of analog, discrete, and digital signals, sampling times, frequencies, and pulses.

Explores the effects of poles and zeros on system response and the importance of system modeling and control strategies.

Explores the application of Laplace transform in state space modeling of linear systems and the control of dynamic systems.