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  2. State-space representation - Wikipedia

    en.wikipedia.org/wiki/State-space_representation

    The state space or phase space is the geometric space in which the axes are the state variables. The system state can be represented as a vector, the state vector. If the dynamical system is linear, time-invariant, and finite-dimensional, then the differential and algebraic equations may be written in matrix form.

  3. Observability - Wikipedia

    en.wikipedia.org/wiki/Observability

    Consider a physical system modeled in state-space representation. A system is said to be observable if, for every possible evolution of state and control vectors, the current state can be estimated using only the information from outputs (physically, this generally corresponds to information obtained by sensors). In other words, one can ...

  4. Hautus lemma - Wikipedia

    en.wikipedia.org/wiki/Hautus_lemma

    In control theory and in particular when studying the properties of a linear time-invariant system in state space form, the Hautus lemma (after Malo L. J. Hautus), also commonly known as the Popov-Belevitch-Hautus test or PBH test, [1] [2] can prove to be a powerful tool.

  5. State-transition matrix - Wikipedia

    en.wikipedia.org/wiki/State-transition_matrix

    The state-transition matrix is used to find the solution to a general state-space representation of a linear system in the following form ˙ = () + (), =, where () are the states of the system, () is the input signal, () and () are matrix functions, and is the initial condition at .

  6. Distributed parameter system - Wikipedia

    en.wikipedia.org/wiki/Distributed_parameter_system

    In control theory, a distributed-parameter system (as opposed to a lumped-parameter system) is a system whose state space is infinite-dimensional. Such systems are therefore also known as infinite-dimensional systems. Typical examples are systems described by partial differential equations or by delay differential equations.

  7. Ackermann's formula - Wikipedia

    en.wikipedia.org/wiki/Ackermann's_Formula

    In control theory, Ackermann's formula is a control system design method for solving the pole allocation problem for invariant-time systems by Jürgen Ackermann. [1] One of the primary problems in control system design is the creation of controllers that will change the dynamics of a system by changing the eigenvalues of the matrix representing the dynamics of the closed-loop system. [2]

  8. Controllability - Wikipedia

    en.wikipedia.org/wiki/Controllability

    For the simplest example of a continuous, LTI system, the row dimension of the state space expression ˙ = + determines the interval; each row contributes a vector in the state space of the system. If there are not enough such vectors to span the state space of x {\displaystyle \mathbf {x} } , then the system cannot achieve controllability.

  9. Phase space - Wikipedia

    en.wikipedia.org/wiki/Phase_space

    The phase space of a physical system is the set of all possible physical states of the system when described by a given parameterization. Each possible state corresponds uniquely to a point in the phase space. For mechanical systems, the phase space usually consists of all possible values of the position and momentum parameters.