 |
BUILT-IN MATHEMATICA SYMBOL
DiscreteLQRegulatorGains[ssm, {q, r}, 
]
gives the optimal discrete-time state feedback gain matrix with sampling period for the continuous-time StateSpaceModel ssm and the quadratic cost function, with state and control weighting matrices q and r.
DiscreteLQRegulatorGains[ssm, {q, r, p}, ]
includes the state-control cross-coupling matrix p in the cost function.
DiscreteLQRegulatorGains[{ssm, finputs}, {...}, ]
specifies the feedback inputs of ssm.
Details and Options
- The standard state-space model ssm can be given as StateSpaceModel[{a, b, ...}], where a and b represent the state and input matrices in the continuous-time system
. - The descriptor continuous-time state-space model ssm defined by
can be given as StateSpaceModel[{a, b, c, d, e}]. - The argument finputs is a list of integers specifying the positions of the feedback inputs
in 
. - DiscreteLQRegulatorGains[ssm, {...}, ] is equivalent to DiscreteLQRegulatorGains[{ssm, All}, {...}, ].
- The cost function is given by
. - In DiscreteLQRegulatorGains[ssm, {q, r}, ], the cross-coupling matrix
is assumed to be zero. - DiscreteLQRegulatorGains computes the regulator gains based on the emulated system
with cost function 
. - The matrix
is the submatrix of 
associated with the feedback inputs 
. - The emulated closed-loop system with the computed feedback gain matrix k can be obtained from SystemsModelStateFeedbackConnect[ToDiscreteTimeModel[ssm, , Method->"ZeroOrderHold"], k]
Examplesopen all
Basic Examples (1)
Compute a set of discrete-time regulator gains for a continuous-time system:
| In[1]:= |
| Out[1]= |  |
New in 8 | Last modified in 9
