Minimum-Order Observer-Based Multivariable MRAC Systems

Traditionally, for output tracking control of multivariable systems, either a state feedback or output feedback controller is used. This paper studies what are the minimal system signals sufficient for building a feedback controller to achieve output tracking, and the corresponding minimum-order feedback controllers. It is shown that there exist feedback controllers which use a scalar signal measurement from an $M$-output system for constructing an effective feedback controller to achieve output tracking or matching of an $M$-dimensional reference signal or system. Such a feedback controller thus has a minimum order as compared with other output tracking controllers. This new concept is generalized to the design of feedback controllers with a vector of $n_{0}$ signal measurements from the controlled system for output tracking of $M$ signals, to provide more design flexibilities. Such a set of feedback signals may be a part of the system outputs or a combination of the outputs or may not be a part of the outputs. Adaptive versions of such minimum-order controllers are also developed. All developed controllers ensure desired closed-loop system stability and asymptotic output tracking. Simulation results verify the effectiveness and the advantages of the new model reference adaptive control (MRAC) systems.

• Publication year

  2018

• Venue

  American Control Conference

• Publication date

  2018-06-01

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.23919/ACC.2018.8430870
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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