Sub-Optimality of a Dyadic Adaptive Control Architecture

AA Paranjape, SJ Chung - arXiv preprint arXiv:2010.10329, 2020 - arxiv.org
arXiv preprint arXiv:2010.10329, 2020arxiv.org
The dyadic adaptive control architecture evolved as a solution to the problem of designing
control laws for nonlinear systems with unmatched nonlinearities, disturbances and
uncertainties. A salient feature of this framework is its ability to work with infinite as well as
finite dimensional systems, and with a wide range of control and adaptive laws. In this paper,
we consider the case where a control law based on the linear quadratic regulator theory is
employed for designing the control law. We benchmark the closed-loop system against …
The dyadic adaptive control architecture evolved as a solution to the problem of designing control laws for nonlinear systems with unmatched nonlinearities, disturbances and uncertainties. A salient feature of this framework is its ability to work with infinite as well as finite dimensional systems, and with a wide range of control and adaptive laws. In this paper, we consider the case where a control law based on the linear quadratic regulator theory is employed for designing the control law. We benchmark the closed-loop system against standard linear quadratic control laws as well as those based on the state-dependent Riccati equation. We pose the problem of designing a part of the control law as a Nehari problem. We obtain analytical expressions for the bounds on the sub-optimality of the control law.
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