Multi-model prediction control method based on gap metric weighting function
A weighting function and predictive control technology, which is applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve the problem of increasing the number, etc., and achieve the effect of improving control performance, reducing the amount of online calculation, and setting convenient and fast
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[0034] In Example 1, a continuous stirred reactor system (CSTR) is simulated and analyzed.
[0035] CSTR system:
[0036]
[0037] where x 1 and x 2 is the dimensionless reaction rate and the temperature in the reactor, and the input variable u is the dimensionless coolant temperature. The constant D in the equation a =0.072, γ=20, B=8 and β=0.3. This system is highly nonlinear, and a single linear controller cannot meet the requirements.
[0038] Utilize the multi-model predictive control method based on the gap metric weighting function provided by the present invention to control the CSTR system, the steps are as follows:
[0039] S1. The change of the output y of the CSTR system directly reflects the degree of nonlinearity of the system, so y is selected as the scheduling variable; the operating space of the system is {y|y∈[0,6]}.
[0040] S2. Choose 3 linear models to approximate the CSTR system, respectively
[0041] S3. Based on submodel P 1 , P 2 , P 3...
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