| dc.description.abstract | A class of engineering systems is modeled by Differential Algebraic Equations
(DAEs), which are also known as singular, descriptor, semistate and generalized
systems. In the chemical engineering processes, the differential equations are
constituted by the dynamic balances of mass and energy, while the thermodynamic
equilibrium relations, empirical correlations, and pseudo-steady-state conditions
build the algebraic equations. The robotic systems with kinematic constraints are
also modeled by DAE systems.
Physical and complex plants are exposed to extraneous noises and signals such as
sensor measurement noise, structural vibration and environmental disturbances. For
example, the external disturbance of a wind gust on an aircraft affects its control
system. The challenge of almost disturbance decoupling is to design a controller to
attenuate the effect of disturbances on the output to an arbitrary degree of accuracy
in the L2
gain sense.
It is worth noting that some parameters of the real plants are naturally unknown due
to the difficulty of measurement. For example, the damping, stiffness and friction
coefficients in the dynamic equations of a constrained robotic system are difficult to
measure.
In this work, the problem of adaptive almost disturbance decoupling for a class of
nonlinear DAE systems is investigated. The DAE system is converted to equivalent
lower triangular structure by regularization and standardization algorithms and an
adaptive almost disturbance decoupling controller is constructed based on adaptive
backstepping technique. At the end, an application of the design procedure to a
physical model is shown and the results are discussed. | en_US |
