31,055 research outputs found
Time-Varying Input and State Delay Compensation for Uncertain Nonlinear Systems
A robust controller is developed for uncertain, second-order nonlinear
systems subject to simultaneous unknown, time-varying state delays and known,
time-varying input delays in addition to additive, sufficiently smooth
disturbances. An integral term composed of previous control values facilitates
a delay-free open-loop error system and the development of the feedback control
structure. A stability analysis based on Lyapunov-Krasovskii (LK) functionals
guarantees uniformly ultimately bounded tracking under the assumption that the
delays are bounded and slowly varying
State feedback control with time delay
In this thesis we start with an introduction to the theory of vibration control. We broadly classify the control methods into passive and active schemes. We introduce the problem of state feedback control and provide the classical solution in the form of Ackermann formula. We then identify the limitations of the classical approach and present the more elegant solution of partial pole assignment without spillover. We highlight the problem with model uncertainties and describe the method of pole assignment using data from measured receptances. This approach is extended for pole assignment for a linear vibrating system by using state feedback control delayed in time. This approach is significantly advantageous over various conventional state-space approaches which need to use information of , and matrices. Since the method relies solely on measured receptances, it negates the need to know , and matrices. It is shown that for a system with degrees of freedom, we may assign eigenvalues. Assigning eigenvalues in a time delayed system does not necessarily regulate the dynamics of the system or guarantee its stability. We separate the eigenvalues into two groups, primary and secondary, and propose method of a posteriori analysis to ensure that the primary eigenvalues have been assigned. The method is demonstrated by various examples. For state feedback control, the control is achieved by measuring the states of the system and feeding them back into the system after multiplying them with appropriate control gain. This makes it imperative to measure all the states of the system. In practical control applications, all states are not accessible for measurement. We address the problem of inaccessibility of states making it difficult to implement the state feedback control. We introduce the theory of linear state estimation also called observer design. We identify the limitations of this approach and introduce the concept of state reconstruction by delayed action. We develop a method to reconstruct the inaccessible states by introducing delay in the system and using information from accessible states. The results are demonstrated by examples
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
Pole Placement and Reduced-Order Modelling for Time-Delayed Systems Using Galerkin Approximations
The dynamics of time-delayed systems (TDS) are governed by delay differential equa-
tions (DDEs), which are infinite dimensional and pose computational challenges. The
Galerkin approximation method is one of several techniques to obtain the spectrum of DDEs
for stability and stabilization studies. In the literature, Galerkin approximations for DDEs
have primarily dealt with second-order TDS (second-order Galerkin method), and the for-
mulations have resulted in spurious roots, i.e., roots that are not among the characteristic
roots of the DDE. Although these spurious roots do not affect stability studies, they never-
theless add to the complexity and computation time for control and reduced-order modelling
studies of DDEs. A refined mathematical model, called the first-order Galerkin method, is
proposed to avoid spurious roots, and the subtle differences between the two formulations
(second-order and first-order Galerkin methods) are highlighted with examples.
For embedding the boundary conditions in the first-order Galerkin method, a new
pseudoinverse-based technique is developed. This method not only gives the exact location
of the rightmost root but also, on average, has a higher number of converged roots when
compared to the existing pseudospectral differencing method. The proposed method is
combined with an optimization framework to develop a pole-placement technique for DDEs
to design closed-loop feedback gains that stabilize TDS. A rotary inverted pendulum system
apparatus with inherent sensing delays as well as deliberately introduced time delays is used
to experimentally validate the Galerkin approximation-based optimization framework for the
pole placement of DDEs.
Optimization-based techniques cannot always place the rightmost root at the desired
location; also, one has no control over the placement of the next set of rightmost roots.
However, one has the precise location of the rightmost root. To overcome this, a pole-
placement technique for second-order TDS is proposed, which combines the strengths of the
method of receptances and an optimization-based strategy. When the method of receptances
provides an unsatisfactory solution, particle swarm optimization is used to improve the
location of the rightmost pole. The proposed approach is demonstrated with numerical
studies and is validated experimentally using a 3D hovercraft apparatus.
The Galerkin approximation method contains both converged and unconverged roots
of the DDE. By using only the information about the converged roots and applying the
eigenvalue decomposition, one obtains an r-dimensional reduced-order model (ROM) of the
DDE. To analyze the dynamics of DDEs, we first choose an appropriate value for r; we
then select the minimum value of the order of the Galerkin approximation method system
at which at least r roots converge. By judiciously selecting r, solutions of the ROM and the
original DDE are found to match closely. Finally, an r-dimensional ROM of a 3D hovercraft
apparatus in the presence of delay is validated experimentally
Predictive scheme for observer-based control of LTI systems with unknown disturbances
International audienceIn this work, it is shown that the results introduced in [1], that hold for full state measurement, can be extended to partial state measurement. In particular, it is proven that the combination of an observer with the new predictive scheme of [1] leads to a better disturbance attenuation than using the same observer with the standard predictive scheme. Finally, some simulations illustrate the results for constant and time-varying disturbances
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