| | **Title of Thesis** Sampled Data Regulation Based On Realizable Reconstruction Filter | **Author(s)**
Muwahida Liaquat
| **Institute/University/Department Details** College of Electrical And Mechanical Engineering / National University of Sciences and Technology, Islamabad | **Session** 2013 | **Subject** Electrical Engineering | **Number of Pages** 212 | **Keywords (Extracted from title, table of contents and abstract of thesis)** Realizable, Sampled, Reconstruction, Data, Filter, Based, Regulation | **Abstract** This dissertation deals with the output feedback sampled-data regulation of a continuous
system usually referred to as the plant.The output of the plant is required to asymptotically track
a continuous reference signal, which in turn is assumed to be generated by an exogenous system.
Only the samples of both the output of the plant as well as the reference signal are available for
measurement.The problem is to design discrete observers for state estimation of both the plant
and the exogenous system followed by a discrete controller.The discrete control signal generated
by the controller is to be connected to the input of the plant by using some generalized hold
device (GHD).The conventional zero order hold device is not a suitable candidate for tracking
applications in general.A GHD incorporates required signal dynamics and hence captures the
inter-sampling behavior through its impulsive nature.The result is an augmented system
incorporating dynamics of the plant, exogenous system and GHD.The customary methods of designing a GHD may result in a higher order solution that
could possibly compromise the stabilizability of the overall system. On the other hand, the
classical reconstruction filter that recovers a continuous signal from its samples is not an option due to its non-causal nature.The commonly used approximations to the ideal reconstruction filter
introduce a delay and hence are not suitable for closed-loop applications. A realizable
reconstruction filter (RRF) is introduced in this dissertation that addresses the aforementioned
limitations. RRF is essentially a specialized GHD that has its utility in both closed-loop and
signal processing applications.The application of RRF for sampled-data regulation is explored for three important
classes of systems.To begin with, a control scheme is developed for linear time invariant (LTI)
systems.A couple of examples of its application on physical systems along with stability
analysis demonstrate the effectiveness of the proposed scheme.Next, single input single output
feedback linearizable systems are investigated in the framework of the suggested theory.An
impulsive observer estimates the states and disturbances using samples of the plant output. Batch
processed least square estimation for initialization results in improved transient behavior.Subsequently, a linearizing control enables to utilize the theory developed for LTI systems on
this problem.The overall control scheme is demonstrated by examples.The proposed method is
then extended to the sampled-data regulation of feedback linearizable MIMO systems with focus
on n-link robotic manipulators.An example of PUMA 560 robotic manipulator is included in the
discussion.A class of linear time varying systems can be transformed into LTI systems (usually
though sinusoidal transformation).The consequence is that constant references get converted
into sinusoidal signals.Active control of gyroscopic systems is one such example.This problem
is also presented in the dissertation.Simulation of impulsive systems requires special considerations that are not handled by
commonly available simulators.A simulation method is specifically developed for impulsive
systems to facilitate closed-loop simulations.
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