Abstract
An approach to the identification of the dissipativity properties of process systems from input-output data is presented, this approach lends itself to analysis and control design for multivariable process systems. In particular, the dissipativity based approach facilitates the design of decentralized or distributed control systems. The proposed approach has the intuitive advantage that only information that is used in the proceeding analysis and design steps is gathered in the system identification step, and not any extraneous information. Quadratic difference forms are used as supply rates and storage functions for the processes. Extensions, including applications to data driven control and thermodynamic properties of nonlinear systems are discussed.
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