Abstract
〈Vol.1 No.2(2008.3)〉
Titles
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■ Tracking and Disturbance Rejection of Extended Constant Signals with
Unknown Disturbance Structure Using MPC
Univ. of Toronto・Edward Joseph DAVISON and
Univ. of Ontario Inst. of Tech・Ruth MILMAN
This paper considers the Model Predictive Control (MPC) set point tracking/regulation
problem for a discrete LTI system, which is subject to a class of unbounded
disturbances/tracking signals called extended constant signals of unknown
structure. Examples of disturbances which belong to this class include
constant disturbances as well as unbounded signals such as w[k] = {k} and
log(k), k=1,2,3,…. A discussion re the choice of window size for MPC is
also made; in particular, it is shown that the window size must be larger
than a certain lower bound, which can be easily determined, in order to
guarantee closed loop stability in MPC control. The main contribution is
a formulation of the system's plant equations under which, for output regulation,
no knowledge of the structure or magnitude of disturbances is needed in
order to achieve set point regulation for this class of extended constant
signals. The result is of interest since it also implies that no disturbance
observer is necessary in order to solve the set point tracking/regulation
problem when full-state feedback is available. The results are experimentally
verified.
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■ Output Regulation with Redundant Measurements
Univ. of Rome・Francesco Delli PRISCOLI,
Albelto ISIDORI and
Univ. of Bologna・Lorenzo MARCONI
The present paper addresses an extension of the classical problem of output regulation. It is shown how the availability of supplementary measurement outputs, in addition to the regulated variable, can be exploited to purpose of overcoming certain current design limitations, extending the analysis to classes of systems with a possibly unstable zero dynamics.
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■ Data Driven Synthesis of Three Term Digital Controllers
Tennessee State Univ.・Lee H. KEEL,
The MathWorks, Inc.・Subhasish MITRA and
Texas A&M Univ.・Shankar P. BHATTACHARYYA
This paper presents a method for digital PID and first order controller synthesis based on frequency domain data alone. The techniques given here first determine all stabilizing controllers from measurement data. In both PID and first order controller cases, the only information required are frequency domain data (Nyquist-Bode data) and the number of open-loop RHP poles. Specifically no identification of the plant model is required. Examples are given for illustration.
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■ Comparison of Low-complexity Controllers in Varying Time-delay Systems
Helsinki Univ. of Tech.・Lasse M. ERIKSSON and
Heikki N. KOIVO
Motivated by the recent development in networked control systems and control over wireless, this paper presents a comparison of five control algorithms that are based on PID, IMC and fuzzy gain scheduling techniques and discusses their performance in varying time-delay systems. The low complexity of the proposed algorithms makes their use attractive in resource-constrained environments such as wireless sensor and actuator networks. The control system consists of a controller, a simple process and an output delay in the feedback loop. Three different delay models are considered in this framework; constant, random, and correlated random delay. In addition to presenting modifications to the control algorithms to better fit the varying time-delay systems a delay-robust tuning method is proposed, and the performance of various controllers is evaluated using simulation. The results show the benefits of adapting the controller parameters based on delay measurement if its amplitude is significant with respect to the time-constant of the process. Nevertheless, the PID algorithm used in the study also performs well in all scenarios, and this is achieved by its careful tuning.
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■ Integrating Information Architecture and Control or Estimation Design
Univ. of California San Diego・Faming LI,
Mauricio C. de OLIVEIRA and Robert E. SKELTON
This paper presents a system level optimal design by integrating the feedback control design and sensor/actuator selection. Instead of the traditional approach of designing the feedback control law with predefined sensors and actuators, we determine the precision of sensor/actuator and the output feedback control law simultaneously such that the total sensor/actuator precision is minimized, subject to the specified control performance (output covariance upper bound). In the case of the full order output feedback control, we provide a complete solution to this problem which is converted into an equivalent convex problem. This convex problem is used as the basis of an \emph{ad hoc} algorithm to reduce the number of sensors and actuators, starting from a large admissible set. The algorithm iteratively deletes instruments until the design specifications can no longer be met.
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■ Sensing, Control and System Integration for Autonomous Vehicles: A Series
of Challenges
The Ohio State Univ.・U. OZGUNER and K. REDMILL
One of the important examples of mechatronic systems can be found in autonomous ground vehicles. Autonomous ground vehicles provide a series of challenges in sensing, control and system integration. In this paper we consider off-road autonomous vehicles, automated highway systems and urban autonomous driving and indicate the unifying aspects. We specifically consider our own experience during the last twelve years in various demonstrations and challenges in attempting to identify unifying themes. Such unifying themes can be observed in basic hierarchies, hybrid system control approaches and sensor fusion techniques.
▲ ■ Simplified Matrix Pencil All-Solutions H∞ Controller Formulae
Univ. of Southern California・Anantha KARTHIKEYAN
and Michael G. SAFONOV
Simplified matrix pencil formulae for solution of the H∞ control problem for the case ●●●● are presented. The formulae are useful in developing more numerically robust algorithms in H∞ control.The formulae apply to descriptor form plants.
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■ Optimal Tuning of PID Parameters Using Iterative Learning Approach
National Univ. of Singapore・Jian-Xin XU, Deqing HUANG and
India Inst. of Tech.・Srinivas PINDI
Proportional-integral-derivative (PID) controller is the most predominant
industrial controller that constitutes more than 90% feedback loops. Time
domain performance of PID, including peak overshoot, settling time and
rise time, is directly relevant to PID parameters. In this work we propose
an iterative learning tuning method (ILT) -- an optimal tuning method for
PID parameters by means of iterative learning. PID parameters are updated
whenever the same control task is repeated. The first novel property of
the new tuning method is that the time domain performance or requirements
can be incorporated directly into the objective function to be minimized.
The second novel property is that the optimal tuning does not require as
much the plant model knowledge as other PID tuning methods. The new tuning
method is essentially applicable to any plants that are stabilizable by
PID controllers. The third novel property is that any existing PID auto-tuning
methods can be used to provide the initial setting of PID parameters, and
the iterative learning process guarantees that a better PID controller
can be achieved. The fourth novel property is that the iterative learning
of PID parameters can be applied straightforward to discrete-time or sampled-data
systems, in contrast to existing PID auto-tuning methods which are dedicated
to continuous-time plants. In this paper, we further exploit efficient
searching methods for the optimal tuning of PID parameters. Through theoretical
analysis, comprehensive investigations on benchmarking examples, and real-time
experiments on the level control of a coupled-tank system, the effectiveness
of the proposed method is validated.
▲ ■ H∞ Control for Continuous-time Systems with Multiple Input Delays: A Smoothing Estimation Approach
Shandong Univ.・Huanshui ZHANG and
Nanyang Tech. Univ.・Lihua XIE
This paper is concerned with the finite horizon H∞ full-information control for continuous time systems with multiple input delays. The main contributions of the paper are two folds. First, parallel to the duality between the LQR of linear systems without delays and the optimal filtering, we establish the duality between the H∞ full-information control of systems with multiple input delays and an H∞ smoothing estimation of a stochastic backward system without involving delays. The duality allows us to address the complicated multiple input delays system problem via the standard projection and innovation analysis. Secondly, by defining a stochastic indefinite linear space and applying a re-organized innovation analysis, an explicit controller is constructed in terms of two standard Riccati differential equations. As special cases, solutions to the H∞ control problem for systems with single input delay and the H∞ control with preview are obtained.
▲ ■ Coordinated Rhythmic Motion by Uncoupled Neuronal Oscillators with Sensory
Feedback
Univ. of Virginia・Tetsuya IWASAKI
IThis paper explores the potential of biological oscillators as a basic
unit for feedback control to achieve rhythmic motion of locomotory systems.
Among those properties of biological control systems that are useful for
engineering applications, we focus on decentralized coordination, that
is, the ability of uncoupled neuronal oscillators to coordinate rhythmic
body movements to achieve locomotion with the aid of local sensory feedback.
We will consider the reciprocal inhibition oscillator (RIO) as a candidate
for the basic control unit, and show that uncoupled RIOs can achieve decentralized
coordination of a prototype mechanical rectifier (PMR) that captures essential
dynamics underlying animal locomotion by a simple arm-disk configuration.
Optimality of the induced locomotion is studied in comparison with analytical
results we derive for statically optimal PMR locomotion.
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