jMPC Toolbox

The following methods are overloaded in the jSS class, although all require the Control Systems Toolbox.

ss

ltiobj = ss(jSSobj) converts the jSS model to a MATLAB lti State Space Model.

c2d

jSSobj = c2d(jSSobj,Ts) converts the continuous jSS model to discrete, using the sampling time Ts. If the model has been flagged to contain dead time (see Models with Dead Time), then this will be converted to state delay(s) at this point.

d2d

jSSobj = d2d(jSSobj,Ts) resamples the discrete jSS model to a new sampling period, using the sampling time Ts. Note this function will not work if the model has dead time which has been converted to state delays, in which case the correct sampling period must be used by c2d.

d2c

djSSobj = d2c(jSSobj) converts the discrete jSS model to continuous.

step

step(jSSobj) performs a step response simulation and plots the result.

[y,t] = step(jSSobj) performs a step response simulation and saves the result in the output vectors.

impulse

impulse(jSSobj) performs a impulse response simulation and plots the result.

[y,t] = impulse(jSSobj) performs a impulse response simulation and saves the result in the output vectors.

dlqe

K = dlqe(jSSobj) uses default Gain (G) & Covariance Matrices (Q,R) (all Identity) to calculate the steady state discrete time observer gain, K, from the supplied state space model.

K = dlqe(jSSobj,Q,R) identical to above but allows the user to specify the Q and R matrices manually.

ssdata

ssdata(jSSobj) displays the A, B, C and D state space matrices together with the sampling time and initial states in the command window.

[A,B,C,D,Ts,x0] = ssdata(jSSobj) returns the above data in the left hand variables.