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Lecture

Networked Control Systems: Stability Analysis and Delay Compensation

In course

ME-427: Networked control systems

This course offers an introduction to control systems using communication networks for interfacing sensors, actuators, controllers, and processes. Challenges due to network non-idealities and opportunities offered by communication will be analyzed. ...

Description

This lecture covers stability analysis and delay compensation in networked control systems. The instructor discusses the sufficient stability conditions using Lyapunov functions, the estimation of Maximum Allowable Transmission Interval (MATI), and the impact of delays on system stability. Through examples and simulations, the lecture demonstrates the importance of compensating for known delays in remote control settings. The comparison between compensated and uncompensated controllers highlights the performance improvement achieved by delay compensation. The lecture concludes with key take-home messages emphasizing the challenges of analyzing time-varying delays and the benefits of delay compensation in networked control systems.

Instructor

Giancarlo Ferrari Trecate

Official source

Related concepts (32)

Lyapunov stability

Various types of stability may be discussed for the solutions of differential equations or difference equations describing dynamical systems. The most important type is that concerning the stability of solutions near to a point of equilibrium. This may be discussed by the theory of Aleksandr Lyapunov. In simple terms, if the solutions that start out near an equilibrium point stay near forever, then is Lyapunov stable. More strongly, if is Lyapunov stable and all solutions that start out near converge to , then is said to be asymptotically stable (see asymptotic analysis).

Stability theory

In mathematics, stability theory addresses the stability of solutions of differential equations and of trajectories of dynamical systems under small perturbations of initial conditions. The heat equation, for example, is a stable partial differential equation because small perturbations of initial data lead to small variations in temperature at a later time as a result of the maximum principle. In partial differential equations one may measure the distances between functions using Lp norms or the sup norm, while in differential geometry one may measure the distance between spaces using the Gromov–Hausdorff distance.

Industrial control system

An industrial control system (ICS) is an electronic control system and associated instrumentation used for industrial process control. Control systems can range in size from a few modular panel-mounted controllers to large interconnected and interactive distributed control systems (DCSs) with many thousands of field connections. Control systems receive data from remote sensors measuring process variables (PVs), compare the collected data with desired setpoints (SPs), and derive command functions that are used to control a process through the final control elements (FCEs), such as control valves.

Control system

A control system manages, commands, directs, or regulates the behavior of other devices or systems using control loops. It can range from a single home heating controller using a thermostat controlling a domestic boiler to large industrial control systems which are used for controlling processes or machines. The control systems are designed via control engineering process. For continuously modulated control, a feedback controller is used to automatically control a process or operation.

Distributed control system

A distributed control system (DCS) is a computerised control system for a process or plant usually with many control loops, in which autonomous controllers are distributed throughout the system, but there is no central operator supervisory control. This is in contrast to systems that use centralized controllers; either discrete controllers located at a central control room or within a central computer. The DCS concept increases reliability and reduces installation costs by localising control functions near the process plant, with remote monitoring and supervision.

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Compensation of Network-Induced Delays in Control Systems

Explores compensation of transmission delays in remote-control settings to ensure stability in networked control systems.

Networked Control Systems

Explores Networked Control Systems, addressing packet dropouts, network delays, stability, and control laws for system boundability.

Networked Control Systems: Stability Analysis and Estimation

Covers the analysis and estimation of stability in networked control systems, including the impact of sampling intervals and delays.

Networked Control Systems: Protocol-induced Delays and Time-varying Sampling

Explores protocol-induced delays, time-varying sampling, wireless control networks, and system stability.

Networked Control Systems: Dropout and Stability Analysis