1 - 10 of 15 for LQRegulatorGainsSearch Results
LQRegulatorGains[ssm, {q, r}] gives the optimal state feedback gain matrix for the StateSpaceModel ssm and the quadratic cost function, with state and control weighting ...
Time delays are common in a variety of systems, often caused by communication lags, material transport, delayed sensing, etc. Time delays can cause instabilities and are ...
Descriptor state-space models can include both dynamic and algebraic equations, as is common in electrical circuits or constrained mechanical systems. This makes modeling ...
Mathematica provides powerful functions to compute state-feedback and estimator gains using pole-placement or optimal techniques. In addition, it has functions that directly ...
SystemsModelStateFeedbackConnect[ssm, controller] connects the states of StateSpaceModel ssm to controller and the outputs of controller to the inputs of ssm in feedback. ...
EstimatorRegulator[ssm, {l, \[Kappa]}] constructs the feedback regulator for the StateSpaceModel ssm with estimator and feedback gain matrices l and \[Kappa], respectively. ...
DiscreteLQRegulatorGains[ssm, {q, r}, \[Tau]] gives the optimal discrete-time state feedback gain matrix with sampling period \[Tau] for the continuous-time StateSpaceModel ...
RiccatiSolve[{a, b}, {q, r}] gives the matrix x that is the stabilizing solution of the continuous algebraic Riccati equation ConjugateTranspose[a].x + x.a - ...
LQGRegulator[{ssm, sensors, finputs}, {w, v, h}, {q, r, p}] constructs the optimal feedback regulator for the StateSpaceModel ssm using noisy measurements sensors and ...
DiscreteRiccatiSolve[{a, b}, {q, r}] gives the matrix x that is the stabilizing solution of the discrete algebraic Riccati equation ConjugateTranspose[a].x.a - x - ...
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