  This paper develops a new model reference adaptive control (MRAC) framework
using partial-state feedback for solving a multivariable adaptive output
tracking problem. The developed MRAC scheme has full capability to deal with
plant uncertainties for output tracking and has desired flexibility to combine
the advantages of full-state feedback MRAC and output feedback MRAC. With such
a new control scheme, the plant-model matching condition is achievable as with
an output or state feedback MRAC design. A stable adaptive control scheme is
developed based on LDS decomposition of the plant high-frequency gain matrix,
which guarantees closed-loop stability and asymptotic output tracking. The
proposed partial-state feedback MRAC scheme not only expands the existing
family of MRAC, but also provides new features to the adaptive control system,
including additional design flexibility and feedback capacity. Based on its
additional design flexibility, a minimal-order MRAC scheme is also presented,
which reduces the control adaptation complexity and relaxes the feedback
information requirement, compared to the existing MRAC schemes. New results are
presented for plant-model matching, error model, adaptive law and stability
analysis. A simulation study of a linearized aircraft model is conducted to
demonstrate the effectiveness and new features of the proposed MRAC control
scheme.
