Home
>
Journals & magazines
>
IEE Proceedings - Control Theory and Applications
>
Volume 145
Issue 2
IEE Proceedings - Control Theory and Applications
Volume 145, Issue 2, March 1998
Volumes & issues:
Volume 145, Issue 2
March 1998
-
- Author(s): Y. Suzuki
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 113 –118
- DOI: 10.1049/ip-cta:19981751
- Type: Article
- + Show details - Hide details
-
p.
113
–118
(6)
When a magnetic bearing–rotor system is excited by ground motion, the rotor may come into contact with the stator because of its low stiffness and the system may suffer heavy damage. Although magnetic bearings are equipped with touchdown bearings for emergencies such as earthquakes, it is desirable to design a controller which can restrain the foundation-excited response of a rotor within the designed gap. In proportional-integral-derivative (PID) control, gains have to be adjusted for many purposes and tradeoffs in control performance are inevitable. This paper thus presents acceleration feedforward control methods designed to reduce the ground-motion response of the active magnetic bearing system without sacrificing other control performances. When this acceleration feedforward control is applied to an experimental apparatus, the response of a rotor to ground motion is reduced to about half that by PID control alone. Furthermore, this suppression of the response is carried out with less control current. - Author(s): H.-P. Lee
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 119 –126
- DOI: 10.1049/ip-cta:19981796
- Type: Article
- + Show details - Hide details
-
p.
119
–126
(8)
A scan loop model for a spin-stabilised seeker is introduced, which includes gyrodynamics with direct- and cross-spring constants for considering the autoerection effect of the gyro. The LQG/LTR and H∞ controllers are designed for the seeker scan loop system which has model uncertainty and is subject to external disturbances. The performance of LQG/LTR controller can be improved by obtaining uniform singular values over all frequencies for the target feedback loop. The H∞ controller is designed in the framework of the standard H∞ optimisation problem with model matching. The proposed H∞ method can reflect not only frequency domain specifications but also time domain ones, such as transient response characteristics and multivariable interaction between output channels, differently from the mixed sensitivity problem. It is shown that the designed LQG/LTR and H∞ controllers offer good performance and robustness properties, and both controllers are very effective in the seeker scan loop system. - Author(s): J.L. Lin and S.J. Chen
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 127 –134
- DOI: 10.1049/ip-cta:19981861
- Type: Article
- + Show details - Hide details
-
p.
127
–134
(8)
Given a nominally regular, impulse-free and -stable linear singular system, a one-parameter family of perturbations is considered. Several new formulas related to the Kronecker operations of linear fractional transformations (LFTs) are established. Based on LFT technique and guardian map theory, a systematic approach is provided to derive a closed-form solution for the maximal bounds under which the regularity, impulse immunity and -stability are preserved to achieve required performance and robust stability. The LFT approach provides a uniform framework for robustness analysis, for both uncertain linear continuous-time and discrete-time singular systems. Two examples are given to illustrate the approach. - Author(s): L. Behera ; S. Chaudhury ; M. Gopal
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 135 –140
- DOI: 10.1049/ip-cta:19981704
- Type: Article
- + Show details - Hide details
-
p.
135
–140
(6)
The use of a self-organising neural network as a feedforward compensator for robot tracking control applications is proposed. The topology of the input space is adaptively mapped onto a set of neurons where each neuron represents a discrete cell in the input domain. Within each cell, a linear mapping is established between the input and output space. The training of such a network involves training of a weight vector that represents the topology of the input space and weight vectors (action space weights) that linearly code an input pattern to action space. In the first phase of network training, a ‘neural-gas’ algorithm is employed for learning the topology of the input space while weight vectors representing control action space is learned by backpropagating feedback control action. During this phase of learning, the weights associated with neurons in the neighbourhood of winning neurons are also updated. In the second stage, a recursive least squares based estimation scheme is applied to fine tune the action space weights associated with winning neurons only, without disturbing the input topology map learned in the first phase. The proposed scheme has been compared with multilayered network (MLN) and radial basis function network (RBFN) based inverse dynamics learning schemes. Simulation results show that the proposed scheme has better generalisation capability than both MLN and RBFN. - Author(s): C.-J. Zhang ; C. Shao ; T.-Y. Chai
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 141 –149
- DOI: 10.1049/ip-cta:19981847
- Type: Article
- + Show details - Hide details
-
p.
141
–149
(9)
The adaptive control issue of a class of linear time-varying plants with uniformly bounded but piecewise Lipschitz continuous parameters is considered. A pole-placement control strategy which allows the plant to be with fast varying parameters is employed, under the condition of the number of discontinuities of the plant parameters being small on average. For the case where plant parameters are partially unknown, an indirect adaptive control scheme is developed by combining the controller with an estimator with projection and normalisation. In addition, it is shown theoretically that the closed-loop system is stable in the bounded-input bounded-output sense. A simulation example is also given to show the applicability of the control scheme. - Author(s): H. Krishnan and M. Vidyasagar
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 151 –158
- DOI: 10.1049/ip-cta:19981949
- Type: Article
- + Show details - Hide details
-
p.
151
–158
(8)
The single-link flexible beam is an infinite-dimensional system. Many researchers have proposed controlling such a beam using an approximate model consisting of a finite a number of modes. But the number of modes that one should retain in the model for the purpose of controller design is not clear. The authors begin with a full-order model containing all the modes of the system within the bandwidth of the actuator and sensors. Control design based on such a model would result in a high-order controller that may not be feasible to implement in practice. Hence, a low-order model for the system is obtained using Hankel-norm minimisation. This procedure gives an excellent reduced-order model in the sense that the reduced model is close to the original system in the graph topology. A controller is designed for the flexible beam on the basis of the reduced-order model thus obtained. Experimental results show that a controller designed for the reduced-order model guarantees effective vibration control of the flexible beam. - Author(s): W.-D. Zhang ; Y.-X. Sun ; X.-M. Xu
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 159 –164
- DOI: 10.1049/ip-cta:19981854
- Type: Article
- + Show details - Hide details
-
p.
159
–164
(6)
The Dahlin controller is studied in the complex-frequency domain in terms of performance and robust stability. Several well known digital control algorithms are compared with the Dahlin controller and found to be equivalent to it. The possibility of extending the Dahlin controller to the control of plants with zeros outside the unit circle and unstable plants is discussed. The essential cause of ringing is investigated and some ambiguous formulation is clarified. A new procedure is developed for digital controller design. Compared with conventional methods, it provides a more effective method of eliminating ringing. Finally, numerical examples are given to illustrate the new approach. - Author(s): Y.-H. Chang and G.L. Wise
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 165 –175
- DOI: 10.1049/ip-cta:19981738
- Type: Article
- + Show details - Hide details
-
p.
165
–175
(11)
The authors investigate the robust gamma stability problem of linear time invariant systems with state space representations. The perturbations of concern are assumed to be time invariant with some given structures. Based on real stability radii, they derive various stability robustness criteria such that all the eigenvalues of the perturbed systems are kept in a specified region, a wedge or a disc in the complex plane. Both the cases of continuous-time and discrete-time systems are discussed. The authors also propose a convergent algorithm to improve stability bounds iteratively. Examples illustrate that less conservative bounds can be obtained. Compared with the existing results, they improve the stability bounds by 20 to 48% after only a few iterations. - Author(s): M.A. Brdyś ; G.J. Kulawski ; J. Quevedo
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 177 –188
- DOI: 10.1049/ip-cta:19981682
- Type: Article
- + Show details - Hide details
-
p.
177
–188
(12)
Design of control techniques for nonlinear systems, where state measurement is not available, still poses a major challenge. Recent successful applications of static neural networks for control suggest that certain intrinsic properties of neural networks could also be utilised for output feedback control, where the neural network serves as a dynamic model of the system. Some steps have been taken in this direction, most of them of a heuristic nature. An adaptive control technique for nonlinear plants with an unmeasurable state is presented based on a recurrent neural network employed as a dynamical model of the plant. Using this dynamical model a feedback linearising control is computed and applied to the plant, while parameters of the model are updated online to allow for partially unknown and time-varying plant. Stability of the algorithm is proved for the case of constant reference output, and some further insights into convergence issues for the general case of tracking problem are provided. Performance of the proposed control method is illustrated in simulations. - Author(s): S.R. Duncan and K.W. Corscadden
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 189 –195
- DOI: 10.1049/ip-cta:19981619
- Type: Article
- + Show details - Hide details
-
p.
189
–195
(7)
The control strategy is based on minimising the expected range of variations observed within a single scan across the width of the sheet. This can be considered as an ℓ∞ minimisation problem and implemented using efficient algorithms based on the simplex method of linear programming. The BIBO stability of the controlled system is analysed and it is shown that the stability of the full multivariable system is determined by the stability of a scalar dynamic term. In general, the controller is suboptimal in the sense that it minimises an upper bound on the expected range of variations across the sheet, but for a certain class of disturbance models the expected value of the range can be minimised optimally by using the minimum variance solution. - Author(s): A.F. Stronach and P. Vas
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 197 –203
- DOI: 10.1049/ip-cta:19981894
- Type: Article
- + Show details - Hide details
-
p.
197
–203
(7)
The paper discusses the design and DSP implementation of artificial-intelligence-based (AIB) speed estimators for control applications in electromechanical drives. The design and performance of AIB estimators based on feedforward and recursive artificial neural networks (ANNs), associative memory networks (AMNs) and neuro-fuzzy networks (NFNs) are compared and discussed. Emphasis is placed on the development of minimal configuration estimators with a view to reducing DSP requirements. It is shown that it is an advantage of the AIB approach to estimator design that neither a conventional drive model nor a knowledge of any drive parameters are required and that an estimate of rotor speed can be obtained using only measurements of supply voltages and/or currents. The DSP system used is based on the Texas Instruments TMS320C31 mounted in a host PC. Results are presented for the real-time application to the speed control of a small DC drive and the estimators are shown to provide a sufficiently accurate speed estimate resulting in stable, robust, speed control. The DSP requirements and performances of each of the estimator forms are presented and compared and it is shown that the overheads imposed by implementation of these estimators is small. - Author(s): M.C. Berg
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 204 –210
- DOI: 10.1049/ip-cta:19981580
- Type: Article
- + Show details - Hide details
-
p.
204
–210
(7)
The features of a special coordinate basis for proper linear and time-invariant multivariable systems are illustrated in the paper. Through a particular choice of state, input and output coordinates, this special coordinate basis demonstrates the physical meaning and importance of finite and infinite zero structure, the conditions for the existence of right and left inverse systems, and how to construct right and left inverse systems when they exist. - Author(s): S. Huang and W. Ren
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 211 –217
- DOI: 10.1049/ip-cta:19981618
- Type: Article
- + Show details - Hide details
-
p.
211
–217
(7)
In the paper, the authors consider the control design problem of vehicle following systems with actuator delays. An upper bound for the time delays is constructed to guarantee the individual vehicle stability. Several conditions are presented to meet the requirements of eliminating ‘slinky’ effects. They prove that the zero steady state can be achieved using the proposed control. Simulations are used to examine our claims. - Author(s): K.W. Lim ; W.K. Ho ; T.H. Lee ; K.V. Ling ; W. Xu
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 219 –225
- DOI: 10.1049/ip-cta:19981740
- Type: Article
- + Show details - Hide details
-
p.
219
–225
(7)
The paper incorporates pole restriction into the generalised predictive controller (GPC). The closed-loop poles are restricted to a region determined from settling time and maximum percentage overshoot. The design is less restrictive than pole placement in that a region rather than fixed points is specified for the closed-loop poles. This property becomes important when process dynamics vary significantly during operation. Furthermore, the algorithm is efficient, as the control weighting λ need not be computed at every sample. A piecewise time-invariant controller is obtained, thus the stability robustness of the system is enhanced. - Author(s): F.N. Koumboulis ; M.G. Skarpetis ; B.G. Mertzios
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 226 –230
- DOI: 10.1049/ip-cta:19981752
- Type: Article
- + Show details - Hide details
-
p.
226
–230
(5)
Sufficient conditions are derived to solve the problem of robust regional stabilisation of linear systems with nonlinear, uncertain structure and uncertain order. The problem of increasing the speed and accuracy of uncertain spool-valve actuators is studied. The robust regional stabilising control technique is applied to compensate for the large variations in the uncertainties of the electro-pneumatic actuator. The problem of the robust stability of the electro-pneumatic actuator is proved to always be solvable, via an independent of the actuator's uncertainties static state feedback law depending only upon the stability margin. The closed loop response remains satisfactory for all values in the uncertainty domain. - Author(s): A. Balestrino ; F.B. Verona ; A. Landi
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 231 –235
- DOI: 10.1049/ip-cta:19981793
- Type: Article
- + Show details - Hide details
-
p.
231
–235
(5)
A neural network approach for on-line parameter estimation in unknown or poorly known processes with a time delay is proposed. The case of plants with unknown time delay and/or steady state gain has been considered. The main result of the paper is the analytical proof of the weight distribution as a sampling centred on the correct value of the time delay. Such a property, along with the estimation of the steady-state gain of the process from the sum of the weights, leads to an accurate identification of the unknown parameters of a process with time delay. A practical application of such a result is the design of an adaptive Smith controller. Simulation results are included in the paper to illustrate the proposed technique. - Author(s): F.M. Al-Sunni and S.H. Al-Amer
- Source: IEE Proceedings - Control Theory and Applications, Volume 145, Issue 2, p. 236 –240
- DOI: 10.1049/ip-cta:19981848
- Type: Article
- + Show details - Hide details
-
p.
236
–240
(5)
The authors present robust stability bounds for sampled data systems. The bounds are derived for the general case of additive perturbation in a system, and the control gain matrices for continuous time systems under discrete state feedback control. They then present a numerical controller design algorithm based on the derived bounds. Examples are used for demonstration.
Acceleration feedforward control for active magnetic bearing systems excited by ground motion
Scan loop control design for a spin-stabilised seeker
LFT approach to robust -stability bounds of uncertain linear singular systems
Application of self-organising neural networks in robot tracking control
Indirect adaptive control for a class of linear time-varying plants
Control of single-link flexible beam using Hankel-norm-based reduced-order model
Robust digital controller design for processes with dead times: New results
Robust gamma stability of highly perturbed systems
Recurrent networks for nonlinear adaptive control
Mini-max control of cross-directional variations on a paper machine
Design, DSP implementation, and performance of artificial-intelligence-based speed estimators for electromechanical drives
Introduction to a special coordinate basis for multivariable linear systems
Longitudinal control with time delay in platooning
Generalised predictive controller with pole restriction
Robust regional stabilisation of an electropneumatic actuator
On-line process estimation by ANNs and Smith controller design
Robust control of sampled data systems
Most viewed content for this Journal
Article
content/journals/ip-cta
Journal
5
Most cited content for this Journal
We currently have no most cited data available for this content.
