Online ISSN
1751-8652
Print ISSN
1751-8644
IET Control Theory & Applications
Volume 5, Issue 4, 3 March 2011
Volumes & issues:
Volume 5, Issue 4
3 March 2011
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- Author(s): M.F.S.V. D'Angelo ; R.M. Palhares ; R.H.C. Takahashi ; R.H. Loschi
- Source: IET Control Theory & Applications, Volume 5, Issue 4, p. 539 –551
- DOI: 10.1049/iet-cta.2009.0033
- Type: Article
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p.
539
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(13)
This study presents a novel approach for incipient fault detection in dynamical systems which is based on a two-step fuzzy/Bayesian formulation for change point detection in time series. The first step consists of a fuzzy-based clusterisation to transform the initial data, with arbitrary distribution, into a new one that can be approximated with a beta distribution. The second step consists in using the Metropolis–Hastings algorithm to the change point detection in the transformed time series. The incipient fault is detected as long as it characterises a change point in such transformed time series. The problem of incipient fault detection in the RTN DAMADICS is analysed. - Author(s): F.-J. Lin ; H.-J. Hsieh ; P.-H. Chou ; Y.-S. Lin
- Source: IET Control Theory & Applications, Volume 5, Issue 4, p. 552 –564
- DOI: 10.1049/iet-cta.2010.0168
- Type: Article
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p.
552
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(13)
A digital signal processor-based cross-coupled functional link (FL) radial basis function network (FLRBFN) control is proposed in this study for the synchronous control of a dual linear motors servo system that is installed in a gantry position stage. The dual linear motors servo system comprises two parallel permanent magnet linear synchronous motors (PMLSMs). First, the dynamics of the field-oriented control PMLSM servo drive with a lumped uncertainty, which contains parameter variations, external disturbance and friction force, is introduced. Then, to achieve accurate trajectory tracking performance with robustness, an intelligent control approach using FLRBFN is proposed for the field-oriented control PMLSM servo drive system. The proposed FLRBFN is a radial basis function network embedded with a FL neural network. Moreover, to guarantee the convergence of the FLRBFN, a discrete-type Lyapunov function is provided to determine the varied learning rates of the FLRBFN. In addition, since a cross-coupled technology is incorporated into the proposed intelligent control scheme for the gantry position stage, both the position tracking errors and synchronous errors of dual linear motors will converge to zero, simultaneously. Finally, some experimental results are illustrated to depict the validity of the proposed control approach. - Author(s): L. Ntogramatzidis and A. Ferrante
- Source: IET Control Theory & Applications, Volume 5, Issue 4, p. 565 –578
- DOI: 10.1049/iet-cta.2010.0239
- Type: Article
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In this study, the authors introduce a range of techniques for the exact design of PID controllers for feedback control problems involving requirements on the steady-state performance and standard frequency-domain specifications on the stability margins and crossover frequencies. These techniques hinge on a set of simple closed-form formulae for the explicit computation of the parameters of the controller in finite terms as functions of the specifications, and therefore they eliminate the need for graphical, heuristic or trial-and-error procedures. The relevance of this approach is (i) theoretical, since a closed-form solution is provided for the design of PID-type controllers with standard frequency-domain specifications; (ii) computational, since the techniques presented here are readily implementable as software routines, for example, using MATLAB®; (iii) educational, because the synthesis of the controller reduces to a simple exercise on complex numbers that can be solved with pen, paper and a scientific calculator. These techniques also appear to be very convenient within the context of adaptive control and self-tuning strategies, where the controller parameters have to be calculated online. Furthermore, they can be easily combined with graphical and first/second-order plant approximation methods in the cases where the model of the system to be controlled is not known. - Author(s): G.S. Kvascev ; Z.M. Djurovic ; B.D. Kovacevic
- Source: IET Control Theory & Applications, Volume 5, Issue 4, p. 579 –593
- DOI: 10.1049/iet-cta.2009.0647
- Type: Article
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579
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(15)
A new adaptive algorithm for the robust estimation of parameters of linear dynamic discrete-time systems in the presence of non-Gaussian impulsive noise within a measurement sequence is proposed in this study. Starting from the theory of robust estimation, a simple, adaptive, practically applicable robust approximate maximum likelihood algorithm is derived that, in the cases of contaminated normal distribution of measurement noise, demonstrates a high level of efficiency. The QQ-plot technique, combined with data cleaning based on the robustified winsorisation technique, is used as a framework for the classification of sorted data into the class of regular normally distributed data and the class of irregular data belonging to the contaminating distribution with a variance that is much greater than nominal. The link between the QQ-plot technique and a specific linear regression is established, so that the estimation of statistical parameters of the contaminated measurement distribution is performed using the least-squares technique. Then, the suboptimal maximum likelihood criterion is defined, and the system parameter estimation problem is solved robustly, using the proposed recursive robust parameter estimation scheme. Simulation results illustrate the discussion and show the efficiency of the proposed adaptive recursive parameter estimation algorithm in the presence of glint spikes or outliers. - Author(s): A.M. D'Amato ; B.O.S. Teixeira ; D.S. Bernstein
- Source: IET Control Theory & Applications, Volume 5, Issue 4, p. 594 –605
- DOI: 10.1049/iet-cta.2010.0023
- Type: Article
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594
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The authors present a two-step method for identifying single-input, single-output (SISO) Wiener systems. First, using a single harmonic input, they estimate a non-parametric model of the static non-linearity, which is assumed to be only piecewise continuous. Second, using the identified non-parametric map, the authors use retrospective cost optimisation to identify a parametric model of the linear dynamic system. This method is demonstrated on several examples of increasing complexity. - Author(s): S.M. Azizi ; M.M. Tousi ; K. Khorasani
- Source: IET Control Theory & Applications, Volume 5, Issue 4, p. 606 –621
- DOI: 10.1049/iet-cta.2010.0320
- Type: Article
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606
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(16)
In this work, a novel multi-agent framework for cooperative supervisory estimation of linear time-invariant systems is proposed. This framework is developed based on the notion of subobservers and a discrete-event system (DES) supervisory control and is applicable to large-scale systems. We introduce a group of subobservers where each subobserver is estimating certain states that are conditioned on a given input, output and state information. The cooperation among the subobservers is managed by a DES supervisor. The supervisor makes decisions regarding the selection and configuration of a set of subobservers to successfully estimate all the system states, while the feasibility of the overall integrated cooperative subobservers is verified. When certain anomalies (faults) are present in the system, or the sensors and subobservers become unreliable, the supervisor reconfigures the set of selected subobservers so that the impacts of anomalies on the estimation performance are minimised to the extent that is possible. The application and capabilities of our proposed methodology in a practical industrial process is demonstrated through numerical simulations. - Author(s): R. Sipahi and W. Qiao
- Source: IET Control Theory & Applications, Volume 5, Issue 4, p. 622 –629
- DOI: 10.1049/iet-cta.2010.0202
- Type: Article
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p.
622
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This study investigates the stability of a class of single-delay interconnected dynamics where dynamics share only delayed information with each other while seeking consensus in a large scale network with fixed topology. The coupled dynamics, which are infinite dimensional because of the presence of delays, can remain stable for at most a certain amount of delays called the delay margin. This margin is intricately determined by the nature of the dynamics, the network connectivity and coupling strengths among the dynamics. Here we present a systematic approach to correlate the finite dimensional network graph properties to the delay margin associated with an infinite dimensional eigenvalue problem. In particular, the developed mathematical approach leads to the responsible eigenvalue concept, which becomes the one and only one eigenvalue that directly determines the delay margin of the entire network. Case studies are provided to demonstrate the effectiveness of the approach as well as the connections between delay margin and the eigenvalues of the corresponding graph Laplacian. - Author(s): H.-N. Wu and H.-X. Li
- Source: IET Control Theory & Applications, Volume 5, Issue 4, p. 630 –639
- DOI: 10.1049/iet-cta.2009.0611
- Type: Article
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This study deals with the problem of robust adaptive ℒ∞-gain neural filter design for a class of uncertain systems with unknown non-linearities and persistently bounded disturbances. A neural filter is constructed for the signal estimation of the system, where two radial basis function neural networks (NNs) are employed to approximate the estimates of the unknown non-linearities in the state dynamics and measurement equation of the system, respectively. The addressed problem is to design such a filter such that the state estimation error is uniformly ultimately bounded and the signal estimation error satisfies an ℒ∞-gain performance. The linear matrix inequality (LMI)-based condition for the existence of a robust adaptive ℒ∞-gain neural filter is provided. In the proposed filtering scheme, by using the orthogonal projection of the state estimation error onto the null space of the linear measurement distribution matrix, the weight update laws of NNs are represented in terms of the available measurement residual. Furthermore, using the existing LMI optimisation technique, a suboptimal neural filter can be obtained in the sense of minimising an upper bound of the ℒ∞-gains. Finally, a simulation example is given to illustrate the effectiveness of the proposed design method.
Fuzzy/Bayesian change point detection approach to incipient fault detection
Digital signal processor-based cross-coupled synchronous control of dual linear motors via functional link radial basis function network
Exact tuning of PID controllers in control feedback design
Adaptive recursive M-robust system parameter identification using the QQ-plot approach
Semi-parametric identification of Wiener systems using a single harmonic input and retrospective cost optimisation
Multi-agent methodology for distributed and cooperative supervisory estimation subject to unreliable information
Responsible eigenvalue concept for the stability of a class of single-delay consensus dynamics with fixed topology
Robust adaptive ℒ∞-gain neural filtering for non-linear systems in the presence of bounded disturbances
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- Author(s): X. Zhang ; Y. Fang ; Y. Zhang
- Source: IET Control Theory & Applications, Volume 5, Issue 4, p. 640 –646
- DOI: 10.1049/iet-cta.2010.0172
- Type: Article
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p.
640
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(7)
A discrete-time time-varying smooth state feedback controller is presented for the set point control of non-holonomic chained systems. The control law drives the system state to zero with an exponential convergent rate without any assumption on the initial state and the sampling rate. Specifically, the discretised model is broken up into two subsystems, and the first control input is explicitly designed such that the second subsystem is transformed into a perturbed linear time-varying system by introducing a novel state transformation, for which classical linear control techniques can be easily adopted to drive the state to the origin. Simulation results are provided to validate the presented approach. - Author(s): J.M. Cano ; M. López-Martínez ; F.R. Rubio
- Source: IET Control Theory & Applications, Volume 5, Issue 4, p. 647 –654
- DOI: 10.1049/iet-cta.2010.0205
- Type: Article
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p.
647
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(8)
This study presents a method to analyse the stability of the feedback interconnection of a class of systems, when the signals associated with the feedback interconnection are sampled asynchronously. A transformation based on L2-gain is designed and introduced on both sides of the interconnection. This transformation enlarges the maximum sampling time such that the interconnection remains stable. The transformation is designed in such a way that both systems have finite L2-gain and verifies the small-gain theorem. This design method makes easier the migration of wired continuous-time control loops to unwired asynchronous ones by just adding this transformation to both sides of the interconnection. The analysis is performed by using the concept of maximum sampling time that preserves small gain (MASG), starting from the continuous-time definition of the property. Finally, a synthesis method is included to obtain the transformation, assuming that the minimum sampling time available in the communication channel is given as a constraint. The synthesis method follows an iterative procedure and solves a set of matrix inequalities. We report on real experiments applied to the remote control of the rotor speeds of a quadrotor.
Discrete-time control of chained non-holonomic systems
Asynchronous networked control of linear systems via L2-gain-based transformations: analysis and synthesis
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