For and the constant matrices over the real numbers in the Kalman rank criterion, the finite-time Controllability Gramian accumulates the influence of all command times. Its column space equals that of the controllability matrix, and is a symmetric positive-definite matrix exactly when the controllability matrix has rank of a matrix . If so, put . Among square-integrable functions steering to at , the commandminimizes , with value . Here in a matrix superscript denotes transpose. This cost is a squared input norm, not necessarily physical energy, and the optimizing command need not satisfy an amplitude bound. [ref]
https://ee263.stanford.edu/archive/contr.pdf. Stephen Boyd, EE263: Controllability and state transfer, slides 18–29 to 18–30
For the double integrator, , so direct integration givesFor a rest-to-rest distance , and the minimum squared input norm is . Compare the two constant commands in the double integrator example, whose cost is : both attain the target, but the smooth command costs less. At , , however, peaks at , so it violates while the two constant commands remain admissible. Controllability, optimal control, and constrained reachability in control theory answer different questions.
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The Controllability Gramian is a mathematical construct used in control theory to assess the controllability of a linear time-invariant (LTI) system. Specifically, it provides a way to determine whether it is possible to drive the state of a dynamical system to any desired condition through appropriate control inputs.