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Volume 148
Issue 6
IEE Proceedings - Control Theory and Applications
Volume 148, Issue 6, November 2001
Volumes & issues:
Volume 148, Issue 6
November 2001
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- Author(s): G.-R. Duan and G.-R. Duan
- Source: IEE Proceedings - Control Theory and Applications, Volume 148, Issue 6, p. 433 –441
- DOI: 10.1049/ip-cta:20010773
- Type: Article
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p.
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Based on a method for right coprime factorisations of linear systems using matrix elementary transformations, it is shown that a very simple iteration formula exists for right coprime factorisations of multi-input linear systems in system upper Hessenberg forms. This formula gives directly the coefficient matrices of the pair of solutions to the right coprime factorisation of the system Hessenberg form, and involves only inverses of a few triangular matrices and some matrix products and summations. Based on this formula, a simple, efficient procedure for determining a right coprime factorisation of a multi-input linear system is proposed, which first converts a given linear system into its system Hessenberg form using some orthogonal similarity transformations and then applies the iteration formula to the converted system Hessenberg form. An example demonstrates the use of the approach. - Author(s): J.D. Chen ; C.H. Lien ; K.K. Fan ; J.H. Chou
- Source: IEE Proceedings - Control Theory and Applications, Volume 148, Issue 6, p. 442 –447
- DOI: 10.1049/ip-cta:20010772
- Type: Article
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p.
442
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The asymptotic stability of a class of neutral systems with multiple discrete and distributed time delays is considered. The Lyapunov stability theorem and a linear matrix inequality (LMI) approach are applied to solve the stability problem for such systems. Discrete-delay-independent and discrete-delay-dependent criteria are proposed to guarantee stability for the systems considered. Some numerical examples are given to illustrate that the results obtained are not conservative. - Author(s): F. Valenciaga ; P.F. Puleston ; P.E. Battaiotto
- Source: IEE Proceedings - Control Theory and Applications, Volume 148, Issue 6, p. 448 –455
- DOI: 10.1049/ip-cta:20010785
- Type: Article
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p.
448
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(8)
A variable structure controller to regulate the output power of a standalone hybrid generation system is presented. The system comprises photovoltaic and wind generation, a storage battery bank and a variable monophasic load. The control law admits two modes of operation. The first takes place when the insolation regime is sufficient to satisfy the power demand. The second mode of operation takes place under insufficient insolation regimes. The latter leads the system operation at the maximum power operation point (MPOP) to save as much stored energy as possible. A new method based on the IncCond algorithm is developed. Sliding mode control techniques are used to design the control law. These techniques provide a simple control law design framework and contribute with their well known robustness properties. Finally, guidelines based on chattering considerations are given for the design of the practical system. - Author(s): C.J. Harris and X. Hong
- Source: IEE Proceedings - Control Theory and Applications, Volume 148, Issue 6, p. 456 –465
- DOI: 10.1049/ip-cta:20010758
- Type: Article
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p.
456
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A connection between a neurofuzzy network model with the Mixture of Experts Network (MEN) modelling approach is established. Based on this linkage, two new neurofuzzy MEN construction algorithms are proposed to overcome the curse of dimensionality that is inherent in the majority of associative memory networks and/or other rule based systems. The first construction algorithm employs a function selection manager module in an MEN system; a conventional latticed based neurofuzzy model is initially generated followed by parsimonious model selection at each iteration using a new simple MEN construction method using a cost criterion based on the MEN model output sensitivity to each expert. This scheme uses an extension to the well established normalised least means squares as a model parametric learning algorithm. The second construction algorithm is based on a new parallel learning algorithm in which each model rule is trained independently, for which the parameter convergence property of the new learning method is established. As with the first approach, an expert selection criterion is utilised in this algorithm, where each rule is either trained or inhibited. These two construction methods are equivalent in their effectiveness in overcoming the curse of dimensionality by reducing the dimensionality of the regression vector, but the latter has the additional computational advantage of parallel processing. The proposed algorithms are analysed for effectiveness followed by numerical examples to illustrate their efficacy for some difficult data based modelling problems. - Author(s): L. Carotenuto ; G. Franzè ; P. Muraca
- Source: IEE Proceedings - Control Theory and Applications, Volume 148, Issue 6, p. 466 –471
- DOI: 10.1049/ip-cta:20010771
- Type: Article
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p.
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The authors report on a study of the pole placement problem via static output feedback for linear time-invariant multivariable systems from a geometric point of view. The main tool for this analysis is a novel formulation of the equations characterising the solution. This allows an explicit expression of the output feedback gain matrix K. A computational procedure to find the matrix K is given that does not require restrictive assumptions on the open- and closed-loop system. The algorithm makes use of symbolic computation, performed using the software MATHEMATICA(R). - Author(s): M.L. Ni ; M.J. Er ; W.E. Leithead ; D.J. Leith
- Source: IEE Proceedings - Control Theory and Applications, Volume 148, Issue 6, p. 472 –477
- DOI: 10.1049/ip-cta:20010770
- Type: Article
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For a class of uncertain time-delay systems, a new approach to the design of robust tracking and model following controllers is presented. In the case that the system uncertainties satisfy the generalised matching conditions, the resultant linear controller guarantees uniform ultimate boundedness of the tracking error, and furthermore the error bound can be made arbitrarily small. In the case of mismatched uncertainties, a sufficient condition is presented such that the controller ensures ultimate boundedness of the tracking error. The main feature of this approach is that much larger system uncertainties arising in the control matrix can be admitted. Two numerical examples are included to show the effectiveness of the approach. - Author(s): M.R. Katebi and M.H. Moradi
- Source: IEE Proceedings - Control Theory and Applications, Volume 148, Issue 6, p. 478 –487
- DOI: 10.1049/ip-cta:20010786
- Type: Article
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p.
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The design of predictive PID controllers with similar features to the model-based predictive controllers (MPC) is considered. Corresponding to a prediction horizon of size M, a bank of M parallel conventional PID controllers is defined. All the controllers have the same three terms gains, but the ith controller operates on the future error signal at time (t+i). A known future set point and dead time can be easily incorporated and the input constraints can be handled via the solution of constrained MPC problem or integral windup techniques. The stability of the closed loop system is studied and the optimal values of PID gains are derived. The controller reduces to a conventional PI or PID controller for the first or second-order system, respectively. The controller can be implemented on the existing process control hardware and the conventional PID tuning knobs can be used to adjust the controller performance. Simulation studies for a number of different systems show that the controller performance is close to an MPC type control algorithm. - Author(s): L. Menini and A. Tornambè
- Source: IEE Proceedings - Control Theory and Applications, Volume 148, Issue 6, p. 488 –496
- DOI: 10.1049/ip-cta:20010713
- Type: Article
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p.
488
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The goal of the paper is to extend some previous results concerned with state feedback stabilisation of mechanical systems subject to nonsmooth impacts, to the case when only position measurements are available for feedback. Fully actuated n-degrees-of-freedom mechanical systems are considered (whereas earlier studies considered only one-degree-of-freedom systems) whose dynamics would be linear in the absence of the inequality constraint delimiting the admissible region. For such systems, a class of compensators that ensures exponential and BIBS stabilisation (without using velocity measurements, which were requested in earlier studies) is proposed and their efficacy is proven by means of Lyapunov techniques. Simulations and experimental results are included to show the effectiveness of the theory presented. - Author(s): P. Suchomski
- Source: IEE Proceedings - Control Theory and Applications, Volume 148, Issue 6, p. 497 –501
- DOI: 10.1049/ip-cta:20010774
- Type: Article
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p.
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Fundamental issues related to numerical conditioning of the discrete-time Lyapunov and Riccati equations given in so-called delta-domain forms are addressed. Having observed that forward shift operator techniques for solving these equations become ill-conditioned for a sufficiently small sampling period, the author shows that numerical robustness and reliability of computations can be significantly improved via utilising the delta-operator representations of the origin equations. Relative condition numbers of these equations are defined to evaluate their conditioning. Results from numerical experiments dealing with reachability and observability Gramians as well as suboptimal control in H∞ are reported that confirm the claim that the delta-domain formulations are much better-conditioned than their counterpart versions based on the forward shift operator. - Author(s): S. H. Jin ; J. B. Park ; K. K. Kim ; T. S. Yoon
- Source: IEE Proceedings - Control Theory and Applications, Volume 148, Issue 6, p. 502 –508
- DOI: 10.1049/ip-cta:20010693
- Type: Article
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p.
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A decentralised ℋ∞ state estimation algorithm is proposed for the multisensor state estimation problems. The idea comes from the fact that the suboptimal ℋ∞ state estimators are just Kalman filters in Krein space. By applying the alternative form of the Kalman filter equations, which is considered to be more appropriate for the decentralised filters due to its structure, to the Krein space state-space model associated with the suboptimal ℋ∞ state estimation problem, the corresponding alternative form of the suboptimal ℋ∞ state estimator is formulated. Using this alternative form, the decentralised ℋ∞ state estimation algorithm is developed, which is composed of the equations for the local and central fusion filters. The proposed estimator is robust against unknown but energy-bounded external disturbances and is also fault tolerant due to its inherent redundancy. In addition, the ℋ∞ central fusion equations, which are newly developed, can reduce the global estimation error much more effectively than the conventional central fusion equations. Numerical examples are given to verify the performance as well as the robustness and the fault tolerance of the proposed algorithm. - Author(s): G. Schreier ; J. DeLeon ; A. Glumineau ; R. Boisliveau
- Source: IEE Proceedings - Control Theory and Applications, Volume 148, Issue 6, p. 509 –515
- DOI: 10.1049/ip-cta:20010641
- Type: Article
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p.
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A cascade observer for a class of nonlinear, state affine, cascade systems is proposed to estimate the state of the induction motor. The observer is validated on the experimental set-up of an induction motor benchmark located at IRCCyN (Nantes, France). - Author(s): J. Zhou ; R. Zhou ; Y. Wang ; G. Guo
- Source: IEE Proceedings - Control Theory and Applications, Volume 148, Issue 6, p. 516 –522
- DOI: 10.1049/ip-cta:20010694
- Type: Article
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p.
516
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An improved proximate time-optimal (PTO) positioning control approach with discrete-time sliding-mode control theory for a Hard Disk Drive (HDD) servo is presented. A third order velocity reference profile is introduced to improve the second order ones in the conventional proximate time-optimal servomechanism (PTOS). The proposed approach eliminates the mode-switching mechanism and dramatically reduces the seek time by 5–50%. Moreover, it is robust to unmodelled dynamics and parameter variations. Its effectiveness is verified in a simulation. - Author(s): G. Belforte and P. Gay
- Source: IEE Proceedings - Control Theory and Applications, Volume 148, Issue 6, p. 523 –529
- DOI: 10.1049/ip-cta:20010640
- Type: Article
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In this paper the problem of Hammerstein dynamic system identification is considered when nonlinear static blocks are described by generalised polynomials and linear time invariant blocks are modelled by ARX structures. The measurement error is characterised in a set membership context. The proposed approach accomplishes parameter identification introducing an extended Hammerstein model the parameter bounds of which can derive overbounds, which can, however, be tight up against to the Hammerstein model parameter uncertainties. The procedure for deriving such overbounds is presented in detail. The consistency of the algorithm for an increasing number of measurements is theoretically proved under the standard set membership assumption that theorises no overbounding of the measurement error, the extreme values of which always reoccur. The degree of conservativeness of the overbounds is evaluated through a simulation study based on a literature model and on a large set of randomly chosen systems. Both white noise and staircase inputs are considered. The results show that in most cases the derived overbounds are at most 10% larger than the actual bounds. - Author(s): X. Hong and C.J. Harris
- Source: IEE Proceedings - Control Theory and Applications, Volume 148, Issue 6, p. 530 –538
- DOI: 10.1049/ip-cta:20010704
- Type: Article
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A common problem in many data based modelling algorithms such as associative memory networks is the problem of the curse of dimensionality. In this paper, a new two-stage neurofuzzy system design and construction algorithm (NeuDeC) for nonlinear dynamical processes is introduced to effectively tackle this problem. A new simple preprocessing method is initially derived and applied to reduce the rule base, followed by a fine model detection process based on the reduced rule set by using forward orthogonal least squares model structure detection. In both stages, new A-optimality experimental design-based criteria we used. In the preprocessing stage, a lower bound of the A-optimality design criterion is derived and applied as a subset selection metric, but in the later stage, the A-optimality design criterion is incorporated into a new composite cost function that minimises model prediction error as well as penalises the model parameter variance. The utilisation of NeuDeC leads to unbiased model parameters with low parameter variance and the additional benefit of a parsimonious model structure. Numerical examples are included to demonstrate the effectiveness of this new modelling approach for high dimensional inputs. - Author(s): B Marinescu and H. Bourlès
- Source: IEE Proceedings - Control Theory and Applications, Volume 148, Issue 6, page: 539 –539
- DOI: 10.1049/ip-cta:20010806
- Type: Article
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- Author(s): M.J Grimble
- Source: IEE Proceedings - Control Theory and Applications, Volume 148, Issue 6, p. 539 –540
- DOI: 10.1049/ip-cta:20010932
- Type: Article
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Right coprime factorisations using system upper Hessenberg forms—the multi-input system case
Criteria for asymptotic stability of a class of neutral systems via a LMI approach
Power control of a photovoltaic array in a hybrid electric generation system using sliding mode techniques
Neurofuzzy mixture of experts network parallel learning and model construction algorithms
New computational procedure to the pole placement problem by static output feedback
New approach to the design of robust tracking and model following controllers for uncertain delay systems
Predictive PID controllers
Dynamic position feedback stabilisation of multidegrees-of-freedom linear mechanical systems subject to nonsmooth impacts
Numerical conditioning of delta-domain Lyapunov and Riccati equations
Krein space approach to decentralised ℋ∞ state estimation
Cascade nonlinear observers: application to an experimental induction motor benchmark
Improved proximate time-optimal sliding-mode control of hard disk drives
Discrete time Hammerstein model identification with unknown but bounded errors
Neurofuzzy design and model construction of nonlinear dynamical processes from data
Comment: LQG controllers for discrete-time multivariable systems with different transport delays in signal channels
Reply: LQG controllers for discrete-time multivariable systems with different transport delays in signal channels
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