Networked Control Systems: Stability Analysis and Examples

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Networked Control Systems: Stability Analysis and Delay Compensation

Explores stability analysis and delay compensation in networked control systems, emphasizing the importance of compensating for known delays.

Sampling Theorem and Control Systems

Explores the Sampling Theorem, digital control, signal reconstruction, and anti-aliasing filters.

Quantiles, Sampling, Histogram Density

Explores quantiles, sampling, and histogram density for understanding distributions and constructing confidence intervals.

Basics of Linear Regression

Covers the basics of linear regression, including OLS estimators, hypothesis testing, and confidence intervals.

Stochastic Simulation: Computation and Estimation

Covers computation and estimation in stochastic simulation, focusing on generating iid replicas and optimal importance sampling.

Discrete-Time Systems Analysis

Explores Z-transform analysis for discrete-time systems and transfer functions in control systems.

Statistical Inference: Approximate Critical Values and Confidence Intervals

Covers the construction of confidence intervals and approximate critical values in statistical inference.

Stochastic Simulation: Latin Hypercube Sampling and Quasi Monte Carlo

Covers Latin Hypercube Sampling and Quasi Monte Carlo methods for stochastic simulation, explaining the goal of stratification and generating independent permutations.

Interval Estimation

Covers the construction of confidence intervals for a normal distribution with unknown mean and variance.

Networked Control Systems: Stability and Analysis

Explores the stability of networked control systems under packet loss and stochastic dropouts, emphasizing mean-square stability and robustness.