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  2. Controllability Gramian - Wikipedia

    en.wikipedia.org/wiki/Controllability_Gramian

    In control theory, we may need to find out whether or not a system such as ˙ = + () = + is controllable, where , , and are, respectively, , , and matrices for a system with inputs, state variables and outputs.

  3. Controllability - Wikipedia

    en.wikipedia.org/wiki/Controllability

    For example, if matrix D = 0 and matrix C does not have full row rank, then some positions of the output are masked by the limiting structure of the output matrix, and therefore unachievable. Moreover, even though the system can be moved to any state in finite time, there may be some outputs that are inaccessible by all states.

  4. Kalman decomposition - Wikipedia

    en.wikipedia.org/wiki/Kalman_decomposition

    In control theory, a Kalman decomposition provides a mathematical means to convert a representation of any linear time-invariant (LTI) control system to a form in which the system can be decomposed into a standard form which makes clear the observable and controllable components of the system.

  5. Observability - Wikipedia

    en.wikipedia.org/wiki/Observability

    Observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs. In control theory, the observability and controllability of a linear system are mathematical duals.

  6. Gram matrix - Wikipedia

    en.wikipedia.org/wiki/Gram_matrix

    That is, a real or complex Gram matrix is also a normal matrix. The Gram matrix of any orthonormal basis is the identity matrix. Equivalently, the Gram matrix of the rows or the columns of a real rotation matrix is the identity matrix. Likewise, the Gram matrix of the rows or columns of a unitary matrix is the identity matrix.

  7. Observability Gramian - Wikipedia

    en.wikipedia.org/wiki/Observability_Gramian

    The Observability Gramian can be found as the solution of the Lyapunov equation given by + = In fact, we can see that if we take = as a solution, we are going to find that: + = + = = | = = =

  8. Hankel singular value - Wikipedia

    en.wikipedia.org/wiki/Hankel_singular_value

    In control theory, Hankel singular values, named after Hermann Hankel, provide a measure of energy for each state in a system. They are the basis for balanced model reduction, in which high energy states are retained while low energy states are discarded. The reduced model retains the important features of the original model.

  9. Control-Lyapunov function - Wikipedia

    en.wikipedia.org/wiki/Control-Lyapunov_function

    It is often difficult to find a control-Lyapunov function for a given system, but if one is found, then the feedback stabilization problem simplifies considerably. For the control affine system ( 2 ), Sontag's formula (or Sontag's universal formula ) gives the feedback law k : R n → R m {\displaystyle k:\mathbb {R} ^{n}\to \mathbb {R} ^{m ...