Title:
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A novel adaptive algorithm and its application to estimation and distributed control
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This thesis deals with a robust finite-time adaptive law and its application
to estimation and (distributed) control. Through the augmentation of a recently
developed novel robust finite-time adaptive law to various schemes such as an
adaptive observer (for the case of a single SISO system), an adaptive controller
(for the case of a single MIMO system) and a distributed adaptive controller (for
the case of multi SIMO and multi MIMO systems), robustness and finite-time
convergence in the parameter estimation can be achieved. In contrast to conventional
adaptive laws (e.g. gradient descent and least-square based method) which
only guarantee exponential stability, robustness is 'achieved without compromising
the need for finite-time convergence. Auxiliary filters are constructed exempting
the algorithm from requiring state velocity (angular acceleration for the case of
robotic manipulator control) in the adaptation algorithm. Capitalizing' on the
use of a sliding mode-like switching term in the adaptation law coupled with the
introduced auxiliary integrated regressors, the parameters are constructed within
finite time. Finite-time convergence for consensus of a distributed cooperative
(adaptive) control system is achieved by incorporating finite-time sliding surfaces
in each connected agent in a network. Nonnegative matrix theory is extended to
allow the Lyapunov analysis of the proposed finite-time distributed adaptive controller
for multi-degree multi-manipulators. The algorithms are analysed using
Lyapunov analysis to prove stability as well as robustness and finite-time convergence.
Lyapunov function for the analysis with the case of bounded disturbance
presence is also showcased. The algorithms have been successfully applied to
an automotive problem to estimate road gradient and mass of vehicle, requiring
engine torque and velocity only. The novel adaptive algorithm has been shown
for the practical control of a robotic arm and for the cooperative control of two
humanoid robotic manipulators for link and Cartesian coordinate control.
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