Simulink Control Design™ - MathWorks

BlockSubs = struct('Name','rct_CSTR/CSTR','Value',Gd);

ST0 = slTuner('rct_CSTR',{'Kp','Ki'},BlockSubs);

Finally, use the tunable surfaces to parameterize the lookup tables.

ST0.setBlockParam('Kp',Kp);

ST0.setBlockParam('Ki',Ki);

When you tune STO, systune tunes the coefficients of the tunable surfaces Kp and Ki, so

that each tunable surface represents the tuned relationship between Cr and the gain.

When you write the tuned values back to the block for validation, setBlockParam

automatically generates tuned lookup-table data by evaluating the tunable surfaces at the

breakpoints you specify in the corresponding blocks.

For more details about this example, see “Gain-Scheduled Control of a Chemical Reactor”

(Control System Toolbox).

Tunable Surfaces in MATLAB

For a control system modeled in MATLAB, use tunable surfaces to construct more

complex gain-scheduled control elements, such as gain-scheduled PID controllers, filters,

or state-space controllers. For example, suppose that you create two gain surfaces Kp and

Ki using tunableSurface. The following command constructs a tunable gain-scheduled

PI controller.

C0 = pid(Kp,Ki);

Similarly, suppose that you create four matrix-valued gain surfaces A, B, C, D. The

following command constructs a tunable gain-scheduled state-space controller.

C1 = ss(A,B,C,D);

You then incorporate the gain-scheduled controller into a generalized model of your

entire control system. For example, suppose G is an array of models of your plant sampled

at the design points that are specified in Kp and Ki. Then, the following command builds

a tunable model of a gain-scheduled single-loop PID control system.

T0 = feedback(G*C0,1);

When you interconnect a tunable surface with other LTI models, the resulting model is an

array of tunable generalized genss models. The design points in the tunable surface

determine the dimensions of the array. Thus, each entry in the array represents the

11 Gain-Scheduled Controllers