688 research outputs found
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
PID control system analysis and design
With its three-term functionality offering treatment of both transient and steady-state responses,
proportional-integral-derivative (PID) control provides a generic and efficient solution to realworld
control problems. The wide application of PID control has stimulated and sustained
research and development to "get the best out of PID", and "the search is on to find
the next key technology or methodology for PID tuning".
This article presents remedies for problems involving the integral and derivative terms. PID design objectives,
methods, and future directions are discussed. Subsequently, a computerized, simulation-based approach
is presented, together with illustrative design results for first-order, higher order, and nonlinear plants. Finally,
we discuss differences between academic research and industrial practice, so as to motivate new research
directions in PID control
On algebraic time-derivative estimation and deadbeat state reconstruction
This note places into perspective the so-called algebraic time-derivative
estimation method recently introduced by Fliess and co-authors with standard
results from linear state-space theory for control systems. In particular, it
is shown that the algebraic method can in a sense be seen as a special case of
deadbeat state estimation based on the reconstructibility Gramian of the
considered system.Comment: Maple-supplements available at
https://www.tu-ilmenau.de/regelungstechnik/mitarbeiter/johann-reger
Adaptive Higher Order Sliding Modes for Two-Dimensional Derivative Estimation
International audienceIn this paper, some recent technical of the derivatives noisy transient signals estimation is extended to the two-dimensional case. This technique, which called higher order sliding modes is mostly used in the synthesis of robust controllers and is also shown a good results in the synthesis of the rth order robust dierentiators. In this work, such dierentiators are used as an edge detection method into image application. The proposed algorithm use an adaptive mechanism for tuning up its parameters in real time, in order to increase the efficiency of basic scheme. Some comparative study with a conventional methods of edge detection is performed
Fractional - order system modeling and its applications
In order to control or operate any system in a closed-loop, it is important to know its behavior in the form of
mathematical models. In the last two decades, a fractional-order model has received more attention in system identification instead of classical integer-order model transfer function. Literature shows recently that some techniques on fractional calculus and fractional-order models have been presenting valuable contributions to real-world processes and achieved better results. Such new developments have impelled research into extensions of the classical identification techniques to advanced fields of science and engineering. This article surveys the recent methods in the field and other related challenges to implement the fractional-order derivatives and miss-matching with conventional science. The comprehensive discussion on available literature would help the readers to grasp the concept of fractional-order modeling and can facilitate future investigations. One can anticipate manifesting recent advances in fractional-order modeling in this paper and unlocking more opportunities for research
Output Filter Aware Optimization of the Noise Shaping Properties of {\Delta}{\Sigma} Modulators via Semi-Definite Programming
The Noise Transfer Function (NTF) of {\Delta}{\Sigma} modulators is typically
designed after the features of the input signal. We suggest that in many
applications, and notably those involving D/D and D/A conversion or actuation,
the NTF should instead be shaped after the properties of the
output/reconstruction filter. To this aim, we propose a framework for optimal
design based on the Kalman-Yakubovich-Popov (KYP) lemma and semi-definite
programming. Some examples illustrate how in practical cases the proposed
strategy can outperform more standard approaches.Comment: 14 pages, 18 figures, journal. Code accompanying the paper is
available at http://pydsm.googlecode.co
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