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Volume 150
Issue 2
IEE Proceedings - Control Theory and Applications
Volume 150, Issue 2, March 2003
Volumes & issues:
Volume 150, Issue 2
March 2003
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- Author(s): N. Tan and D.P. Atherton
- Source: IEE Proceedings - Control Theory and Applications, Volume 150, Issue 2, p. 101 –111
- DOI: 10.1049/ip-cta:20030117
- Type: Article
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p.
101
–111
(11)
A method for the computation of the magnitude and phase envelopes of uncertain transfer functions is presented. The idea is to factor the transfer function into its real and complex pair roots and find the maximum and minimum magnitudes of the gain and phase of each factor. The Bode envelopes of the given uncertain system are then found from those of the individual factors. This approach, which is different from those based on the interval polynomial method of Kharitonov, has the major advantage that the representation is more applicable to practical situations where typically the coefficients of the various factored terms relate to physical parameters of a mathematical model. Further, the method results in the narrowest Bode envelopes and therefore can yield improved controller designs. The describing function analysis and the absolute stability problem of nonlinear systems with variable plant parameters are also studied. An approach which enables one to predict the existence of limit cycles in a control system which simultaneously contains nonlinearities and parametric uncertainties is given. The proposed method makes use of the popular describing function technique and these narrowest possible Bode envelopes of linear uncertain transfer functions in factored form. The technique can be used to cover the cases of linear elements, which have a multilinear or nonlinear uncertainty structure, and a nonlinear element with or without memory. New formulations of the circle and off-axis circle criteria are given for use with Bode diagrams so that the absolute stability of nonlinear systems with variable plant parameters can be studied. Examples are given to show how the proposed method can be used to assess the effects of parametric variations in feedback loops. - Author(s): Q. Song ; W.J. Hu ; T.N. Zhao
- Source: IEE Proceedings - Control Theory and Applications, Volume 150, Issue 2, p. 112 –118
- DOI: 10.1049/ip-cta:20030065
- Type: Article
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p.
112
–118
(7)
The HVAC industry expects the automation and control systems to perform well throughout the year without the requirement to re-tune the system and to conserve energy. To satisfy these requirements it is necessary to provide a basic control algorithm that will respond well to the presence of nonlinear behaviour in HVAC equipment. The PID algorithm has to be enhanced to handle the highly nonlinear functionality, range of operation and robustness. The neural network is one of the best candidates to deal with these issues. However, it is important to address stability and disturbance properly, to obtain optimal performance of the neural control system. The design and application of a robust neural network algorithm are discussed and how it compliments the fixed proportional control algorithm to provide the desired functionality as well as the adaptation of the VAV control system for a wide range of disturbances and parameter changes. - Author(s): J. Moreno ; R. Kelly ; R. Campa
- Source: IEE Proceedings - Control Theory and Applications, Volume 150, Issue 2, p. 119 –126
- DOI: 10.1049/ip-cta:20030083
- Type: Article
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p.
119
–126
(8)
The velocity control of a direct-drive mechanical arm with high friction is considered. The friction at the robot joints is assumed to be captured by a bristle deflection model. Two joint velocity controllers with friction compensation are introduced. Experiments show the superiority of the proposed schemes with respect to the velocity controllers when friction is compensated using the classical viscous plus Coulomb model of friction. - Author(s): J. Jugo ; A. Anakabe ; J.M. Collantes
- Source: IEE Proceedings - Control Theory and Applications, Volume 150, Issue 2, p. 127 –131
- DOI: 10.1049/ip-cta:20030016
- Type: Article
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p.
127
–131
(5)
Different approaches for stability analysis of large-signal steady states in the harmonic domain have been developed in recent years. Particular efforts have been focused on microwave and RF circuit design, where harmonic balance (HB) techniques are used extensively. In this work, frequency-domain control-design techniques are proposed in order to improve the stability margins of large-signal steady states. The methodology is based on circuit linearisation around the steady state under study and the calculation of the corresponding linear model through frequency domain identification techniques. To validate the proposed approach, the stabilisation of a circuit based on a varactor diode is presented. - Author(s): H. Du ; L. Zhang ; Z. Lu ; X. Shi
- Source: IEE Proceedings - Control Theory and Applications, Volume 150, Issue 2, p. 132 –138
- DOI: 10.1049/ip-cta:20030101
- Type: Article
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p.
132
–138
(7)
This design of a linear parameter-varying (LPV) controller for the rejection of sinusoidal disturbance with time-varying frequency but measurable on-line for implementation purposes is described. The approach proposed is based on modelling the sinusoidal disturbance with a measurable time-varying frequency as an LPV model and adding this model to the controlled linear time-invariant (LTI) system to formulate an augmented LPV system. Then a stabilising H∞-like LPV controller is constructed for the augmented LPV system based on the Lyapunov approach with a single quadratic Lyapunov function. The effectiveness of the LPV controller is assessed by means of several simulation trials on a two-mass–spring–damper system. Numerical results are used to demonstrate the validity of the analytical results and the ability of the algorithms to reject sinusoidal disturbance with time-varying frequency. - Author(s): S. Chen ; X. Hong ; C.J. Harris
- Source: IEE Proceedings - Control Theory and Applications, Volume 150, Issue 2, p. 139 –146
- DOI: 10.1049/ip-cta:20030253
- Type: Article
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p.
139
–146
(8)
A construction algorithm for multioutput radial basis function (RBF) network modelling is introduced by combining a locally regularised orthogonal least squares (LROLS) model selection with a D-optimality experimental design. The proposed algorithm aims to achieve maximised model robustness and sparsity via two effective and complementary approaches. The LROLS method alone is capable of producing a very parsimonious RBF network model with excellent generalisation performance. The D-optimality design criterion enhances the model efficiency and robustness. A further advantage of the combined approach is that the user only needs to specify a weighting for the D-optimality cost in the combined RBF model selecting criterion and the entire model construction procedure becomes automatic. The value of this weighting does not influence the model selection procedure critically and it can be chosen with ease from a wide range of values. - Author(s): F. Alonge ; F. D'Ippolito ; F.M. Raimondi
- Source: IEE Proceedings - Control Theory and Applications, Volume 150, Issue 2, p. 147 –154
- DOI: 10.1049/ip-cta:20030149
- Type: Article
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p.
147
–154
(8)
Nonlinear system identification by means of wavelet-based neural networks (WBNNs) is presented. An iterative method is proposed, based on a way of combining genetic algorithms (GAs) and least-square techniques with the aim of avoiding redundancy in the representation of the function. GAs are used for optimal selection of the structure of the WBNN and the parameters of the transfer function of its neurones. Least-square techniques are used to update the weights of the net. The basic criterion of the method is the addition of a new neurone, at a generic step, to the already constructed WBNN so that no modification to the parameters of its neurones is required. Simulation experiments and comparison with neural nets having different activation functions for the neurones are also presented. - Author(s): D.W. Clarke and J.W. Park
- Source: IEE Proceedings - Control Theory and Applications, Volume 150, Issue 2, p. 155 –169
- DOI: 10.1049/ip-cta:20030140
- Type: Article
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p.
155
–169
(15)
A loop's phase-margin φm provides helpful information: often it predictably affects damping, and the corresponding frequency ωm is related to the closed-loop bandwidth. However, its use in controller design is frequently hampered by lack of knowledge of the plant's transfer-function G(s). Hence, as with the popular autotuning methods, the authors consider a simple algorithm that automatically determines the frequency ωd and gain |G(jωd)| corresponding to a prescribed plant phase-lag φd as this information can be used simply to tune a PI regulator This adaptive approach is shown to have the structure of a phased-locked loop (PLL). The key ingredient in a PLL is its phase-sensitive detector (PSD), as phase cannot be estimated instantaneously and the deduced value is affected by harmonics and noise. Four common PSDs are compared and it is found that the Hilbert-transform PSD has uniformly effective behaviour. Predictions of the convergence and noise-rejection properties of the algorithm are presented and confirmed via simulation. The same algorithm can be used for loop monitoring, in which plant variations are tracked via on-line estimation of ωd(t). A benefit of the algorithm is that it enables active probing of a plant by low-amplitude sinewaves, as good tracking is possible even with signal-to-noise ratios much less than one. - Author(s): A.H. Tan
- Source: IEE Proceedings - Control Theory and Applications, Volume 150, Issue 2, p. 170 –178
- DOI: 10.1049/ip-cta:20030147
- Type: Article
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p.
170
–178
(9)
Analytical results have been obtained for first-order direction-dependent processes perturbed using maximum length ternary (MLT) signals. In particular, the process output and the input-output crosscorrelation function are derived, leading to a theoretical expression for the combined time constant of the process. The importance of doing this is that the direction-dependent behaviour can be detected, and the combined linear dynamics of the process can be estimated, from the input-output crosscorrelation function. In the above derivations, it is assumed that the process dynamics are faster in the upward direction, and that the clock-pulse interval is chosen such that the output always decreases when the input is at signal level zero. The first of these assumptions does not affect the terms in the crosscorrelation function because the input signal is inverse-repeat. The second assumption is shown to be valid during most of the signal period. The errors caused by the deviation from the ideal case are assessed, and are found to be small. Hence, the ideal case can be used as an effective benchmark against which results from an identification test as specified above can be measured. Advantages and disadvantages of using the MLT signal, instead of the maximum length binary or its inverse-repeat signal, are discussed. A simulation example is also shown to verify the obtained theoretical results. - Author(s): S.-G. Kim ; K.-H. Cho ; J.-T. Lim
- Source: IEE Proceedings - Control Theory and Applications, Volume 150, Issue 2, p. 179 –182
- DOI: 10.1049/ip-cta:20030015
- Type: Article
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p.
179
–182
(4)
A hierarchical consistency problem for the hierarchical supervisory control of discrete event systems under partial observation is considered, since observability is a practical and general property in real systems. The notion of H-observability is introduced to ensure hierarchical consistency between low- and high-level systems, and an analytical framework for the hierarchical supervisory control is established. - Author(s): R. Bárcena and M. De la Sen
- Source: IEE Proceedings - Control Theory and Applications, Volume 150, Issue 2, p. 183 –188
- DOI: 10.1049/ip-cta:20030066
- Type: Article
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p.
183
–188
(6)
Remarkable improvement in the performance of digitally handled systems may be achieved by using properly adjusted fractional-order hold (FROH) circuits. Nevertheless, the tuning methods formerly proposed in the bibliography are exclusively applicable for a certain range of sufficiently small sampling periods. Such a range is analytically obtained and its significance for the applicability of such methods is discussed. - Author(s): J.-H. Park and G.-T. Park
- Source: IEE Proceedings - Control Theory and Applications, Volume 150, Issue 2, p. 189 –197
- DOI: 10.1049/ip-cta:20030148
- Type: Article
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p.
189
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(9)
The design of a robust adaptive fuzzy observer for uncertain nonlinear dynamic systems is presented. The Lyapunov synthesis approach is used to guarantee a uniformly ultimately bounded property of the state observation error, as well as of all other signals in the closed-loop system. The realisation of the minimal dynamic order of the observer is considered. For this purpose, a method, which does not need a strictly positive real condition is combined with a dynamic rule activation scheme with an on-line estimation of fuzzy parameters. No a priori knowledge of an upper bound on the lumped uncertainty is required. The theoretical results are illustrated through a simulation example. - Author(s): C.-W. Park and Y.-W. Cho
- Source: IEE Proceedings - Control Theory and Applications, Volume 150, Issue 2, p. 198 –204
- DOI: 10.1049/ip-cta:20030017
- Type: Article
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p.
198
–204
(7)
A direct model reference adaptive control via Takagi–Sugeno fuzzy modelling and parallel distributed compensation (PDC) is developed for the MIMO plant model to control an uncertain flexible joint manipulator. The proposed control scheme is proposed to provide asymptotic tracking of a reference signal for the systems with uncertain parameters. From Lyapunov stability analysis and simulation results, the developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.
New approach to assessing the effects of parametric variations in feedback loops
Robust neural network controller for variable airflow volume system
Manipulator velocity control using friction compensation
Control design in the harmonic domain for microwave and RF circuits
LPV technique for the rejection of sinusoidal disturbance with time-varying frequency
Sparse multioutput radial basis function network construction using combined locally regularised orthogonal least square and D-optimality experimental design
System identification via optimised wavelet-based neural networks
Phase-locked loops for plant tuning and monitoring
Identification of direction-dependent processes using maximum length ternary signals
Hierarchical supervisory control of discrete event systems based on H-observability
On the sufficiently small sampling period for the convenient tuning of fractional-order hold circuits
Adaptive fuzzy observer with minimal dynamic order for uncertain nonlinear systems
Adaptive tracking control of flexible joint manipulator based on fuzzy model reference approach
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