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Process Control: Modeling, Design, and Simulation by B. Wayne Bequette

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16.4. Constraints and Multivariable Systems

The dynamic matrix control technique presented in the previous section is based on an unconstrained optimization of current and future control moves. The combination of a linear model and a quadratic objective function lead to an analytical solution for the control moves. In practice, constraints on manipulated inputs (control moves) can be very important. If Equation (16.23), which is the analytical solution to Equation (16.22), results in an infeasible control action (e.g., a violation of constraints, such as a flow rate greater than the maximum possible flow), then obviously the control moves must be “truncated” at the maximum or minimum values. Since the resulting truncated solutions may not be ...

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