- Performance weight Qz
Performance weights, specified as a scalar or a matrix. Use a scalar value to specify a
multiple of the identity matrix. Otherwise specify a symmetric nonnegative definite
matrix. Use a diagonal matrix to independently scale or penalize the contribution of
each variable in z.The performance weights contribute to the cost function according to:J = E(z(t)′ Qz z(t)).When you use the LQG goal as a hard goal, the software tries to drive the cost function
J < 1. When you use it as a soft goal, the cost function J is minimized subject to any
hard goals and its value is contributed to the overall objective function. Therefore,
select Qz values to properly scale the cost function so that driving it below 1 or
minimizing it yields the performance you require.- Noise Covariance Qw
Covariance of the white noise input vector w(t), specified as a scalar or a matrix. Use a
scalar value to specify a multiple of the identity matrix. Otherwise specify a symmetric
nonnegative definite matrix with as many rows as there are entries in the vector w(t).
A diagonal matrix means the entries of w(t) are uncorrelated.The covariance of w(t is given by:E(w(t)w(t)′) = QW.When you are tuning a control system in discrete time, the LQG goal assumes:E(w[k]w[k]′) = QW/Ts.Ts is the model sample time. This assumption ensures consistent results with tuning in
the continuous-time domain. In this assumption, w[k] is discrete-time noise obtained
by sampling continuous white noise w(t) with covariance QW. If in your system w[k] is
a truly discrete process with known covariance QWd, use the value Ts*QWd for the
QW value.Options
Use this section of the dialog box to specify additional characteristics of the LQG goal.10 Control System Tuning