Internal model control (IMC), which explicitly incorporates a plant model and a plant inverse as its components, has an intuitive control structure and simple tuning philosophy, making it appealing to industrial applications. Combining the IMC structure with adaptation through the certainty equivalence principle leads to adaptive IMC (AIMC), where the plant model is identified and the plant inverse is derived by inverting the estimated model. In [1], [2], we proposed the composite adaptive IMC (CAIMC) for a first-order plant and successfully applied it to the boost-pressure control problem of a turbocharged gasoline engine system. Within the IMC control structure, the plant model and the plant inverse are simultaneously identified to minimize modeling errors and further reduce the tracking error. Through theoretical analysis, simulations, and experimental validation, CAIMC was shown to demonstrate better performance compared to AIMC. In this paper the design procedure of CAIMC is generalized to a n-th order plant, and stability and asymptotic performance are established and analyzed under proper conditions.
['Zeng Qiu', 'Jing Sun', 'Mrdjan Jankovic', 'Mario Santillo']
Generalized composite adaptive IMC: Design and analysis