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In the context of control systems, they represent critical values that can determine the system stability and response characteristics.

A method for determining the stability of a system by constructing a Lyapunov function, which is a scalar function of the state that decreases along system trajectories.

A control strategy in which the poles of a closed-loop transfer function are assigned to specific locations in the complex plane to achieve desired response characteristics.

A mathematical framework used for modeling and analyzing dynamic systems, where state variables describe the system's status at any given time.

A function that describes the relationship between input and output in the Laplace domain, used to analyze the behavior of linear time-invariant systems.

An optimal control strategy that minimizes a cost function usually composed of state and control variables to achieve an optimal trajectory.

A vector of inputs into the system that can be manipulated to affect the state of the system.

A matrix that describes how the state of a system evolves from one state to the next in discrete or continuous time.

A property indicating whether it is possible to move the system from any initial state to any final state within a finite time span, using appropriate control inputs.

A graphical method for displaying the frequency response of a system, which can help in understanding the stability and the time domain behavior of the system.

The study of how system states evolve over time, which in state space representation is described by differential or difference equations.

A property that determines if the current state of a system can be determined over time by only looking at the outputs.

A vector consisting of state variables that represent the system at a given time. It is used in state space representation to describe the system's status.

A vector of outputs that the system produces, which are typically what we want to control or monitor.