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A survey on gain-scheduled control and filtering for parameter-varying systems
Copyright © 2014 Guoliang Wei et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.This paper presents an overview of the recent developments in the gain-scheduled control and filtering problems for the parameter-varying systems. First of all, we recall several important algorithms suitable for gain-scheduling method including gain-scheduled proportional-integral derivative (PID) control, H 2, H â and mixed H 2 / H â gain-scheduling methods as well as fuzzy gain-scheduling techniques. Secondly, various important parameter-varying system models are reviewed, for which gain-scheduled control and filtering issues are usually dealt with. In particular, in view of the randomly occurring phenomena with time-varying probability distributions, some results of our recent work based on the probability-dependent gain-scheduling methods are reviewed. Furthermore, some latest progress in this area is discussed. Finally, conclusions are drawn and several potential future research directions are outlined.The National Natural Science Foundation of China under Grants 61074016, 61374039, 61304010, and 61329301; the Natural Science Foundation of Jiangsu Province of China under Grant BK20130766; the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning; the Program for New Century Excellent Talents in University under Grant NCET-11-1051, the Leverhulme Trust of the U.K., the Alexander von Humboldt Foundation of Germany
Profitable Scheduling on Multiple Speed-Scalable Processors
We present a new online algorithm for profit-oriented scheduling on multiple
speed-scalable processors. Moreover, we provide a tight analysis of the
algorithm's competitiveness. Our results generalize and improve upon work by
\textcite{Chan:2010}, which considers a single speed-scalable processor. Using
significantly different techniques, we can not only extend their model to
multiprocessors but also prove an enhanced and tight competitive ratio for our
algorithm.
In our scheduling problem, jobs arrive over time and are preemptable. They
have different workloads, values, and deadlines. The scheduler may decide not
to finish a job but instead to suffer a loss equaling the job's value. However,
to process a job's workload until its deadline the scheduler must invest a
certain amount of energy. The cost of a schedule is the sum of lost values and
invested energy. In order to finish a job the scheduler has to determine which
processors to use and set their speeds accordingly. A processor's energy
consumption is power \Power{s} integrated over time, where
\Power{s}=s^{\alpha} is the power consumption when running at speed .
Since we consider the online variant of the problem, the scheduler has no
knowledge about future jobs. This problem was introduced by
\textcite{Chan:2010} for the case of a single processor. They presented an
online algorithm which is -competitive. We provide an
online algorithm for the case of multiple processors with an improved
competitive ratio of .Comment: Extended abstract submitted to STACS 201
PID control system analysis, design, and technology
Designing and tuning a proportional-integral-derivative
(PID) controller appears to be conceptually intuitive, but can
be hard in practice, if multiple (and often conflicting) objectives
such as short transient and high stability are to be achieved.
Usually, initial designs obtained by all means need to be adjusted
repeatedly through computer simulations until the closed-loop
system performs or compromises as desired. This stimulates
the development of "intelligent" tools that can assist engineers
to achieve the best overall PID control for the entire operating
envelope. This development has further led to the incorporation
of some advanced tuning algorithms into PID hardware modules.
Corresponding to these developments, this paper presents a
modern overview of functionalities and tuning methods in patents,
software packages and commercial hardware modules. It is seen
that many PID variants have been developed in order to improve
transient performance, but standardising and modularising PID
control are desired, although challenging. The inclusion of system
identification and "intelligent" techniques in software based PID
systems helps automate the entire design and tuning process to
a useful degree. This should also assist future development of
"plug-and-play" PID controllers that are widely applicable and
can be set up easily and operate optimally for enhanced productivity,
improved quality and reduced maintenance requirements
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