You can now use systune to tune the controller coefficients against the requirements
R1-R4. Make the stability margin requirement a hard constraints and optimize the
remaining requirements.
ST = systune(ST0,[R1 R2 R3],R4);
Final: Soft = 1.21, Hard = 0.99913, Iterations = 207
The resulting design satisfies the hard constraint (Hard<1) and nearly satisfies the
remaining requirements (Soft close to 1). To validate this design, simulate the responses
to a ramp in concentration with the same slope as Cref. Each plot shows the linear
responses at the five design points CrEQ.
t = 0:Ts:20;
uC = interp1([0 2 5 20],(-0.25)*[0 0 3 3],t);
subplot(211), lsim(getIOTransfer(ST,'Cref','Cr'),uC)
grid, set(gca,'ylim',[-1.5 0.5]), title('Residual concentration')
subplot(212), lsim(getIOTransfer(ST,'Cref','Tc'),uC)
grid, title('Coolant temperature variation')
Gain-Scheduled Control of a Chemical Reactor