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rsys = reg(sys,K,L)
rsys = reg(sys,K,L,sensors,known,controls)
rsys = reg(sys,K,L) forms a dynamic regulator or compensator rsys given a state-space model sys of the plant, a state-feedback gain matrix K, and an estimator gain matrix L. The gains K and L are typically designed using pole placement or LQG techniques. The function reg handles both continuous- and discrete-time cases.
This syntax assumes that all inputs of sys are controls, and all outputs are measured. The regulator rsys is obtained by connecting the state-feedback law u = –Kx and the state estimator with gain matrix L (see estim). For a plant with equations
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this yields the regulator
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This regulator should be connected to the plant using positive feedback.

rsys = reg(sys,K,L,sensors,known,controls) handles more general regulation problems where:
The plant inputs consist of controls u, known inputs ud, and stochastic inputs w.
Only a subset y of the plant outputs is measured.
The index vectors sensors, known, and controls specify y, ud, and u as subsets of the outputs and inputs of sys. The resulting regulator uses [ud ; y] as inputs to generate the commands u (see next figure).

Given a continuous-time state-space model
sys = ss(A,B,C,D)
with seven outputs and four inputs, suppose you have designed:
A state-feedback controller gain K using inputs 1, 2, and 4 of the plant as control inputs
A state estimator with gain L using outputs 4, 7, and 1 of the plant as sensors, and input 3 of the plant as an additional known input
You can then connect the controller and estimator and form the complete regulation system by
controls = [1,2,4]; sensors = [4,7,1]; known = [3]; regulator = reg(sys,K,L,sensors,known,controls)
dlqr | estim | kalman | lqgreg | lqr | place

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