Online ISSN
1751-8652
Print ISSN
1751-8644
IET Control Theory & Applications
Volume 5, Issue 10, 7 July 2011
Volumes & issues:
Volume 5, Issue 10
7 July 2011
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- Author(s): M. Gilson ; H. Garnier ; P.C. Young ; P.M.J. Van den Hof
- Source: IET Control Theory & Applications, Volume 5, Issue 10, p. 1147 –1154
- DOI: 10.1049/iet-cta.2009.0476
- Type: Article
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p.
1147
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(8)
This study presents in a new unified way, optimal instrumental variable methods for identifying discrete-time transfer function models when the system operates in a closed loop. The conditions for the optimal design of prefilters and instruments depending on common model structures are analysed and different approaches are developed according to whether the controller is known or not. The performance of the proposed approaches is evaluated by Monte-Carlo analysis in comparison with other alternative closed-loop estimation methods. - Author(s): A.C. Charalampidis and G.P. Papavassilopoulos
- Source: IET Control Theory & Applications, Volume 5, Issue 10, p. 1155 –1166
- DOI: 10.1049/iet-cta.2010.0553
- Type: Article
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p.
1155
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(12)
This study deals with recursive state estimation for non-linear systems. A new set of σ-points for the unscented Kalman filter is proposed as well as a way to substitute a non-linear output with a linear one. The importance of the function of the state which must be estimated is also illustrated and also the need for taking it into account when designing the state estimator. Mode-based estimators are proposed. All the suggested methods are compared with standard extended Kalman filter, unscented Kalman filter and particle filter with sampling importance resampling using simulations. The results show that the modifications proposed in some cases lead to considerable reduction in the estimation error. - Author(s): R. Cepeda-Gomez ; N. Olgac ; D.A. Sierra
- Source: IET Control Theory & Applications, Volume 5, Issue 10, p. 1167 –1175
- DOI: 10.1049/iet-cta.2010.0201
- Type: Article
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p.
1167
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A robustising sliding mode control strategy is implemented on two competing multi-agent swarms, called pursuers and evaders, with equal membership count. Newtonian dynamic models are considered, which include drag forces as well as the inter-agent attraction/repulsion forces. The proposed sliding mode control law achieves the stability and the capture of the evaders by the pursuers despite the uncertainties in the evader behaviour. The group pursuit is conceived in two phases: the approach phase during which the two swarms act like two individuals and the assigned pursuit phase when each pursuer is assigned to an evader. Furthermore, the authors take into account a turning action for the evaders, which adds to their agility. This property is considered as a part of the uncertainty in the dynamics. The control parameters are separately studied to assess their influences on the pursuit. - Author(s): Z. Li
- Source: IET Control Theory & Applications, Volume 5, Issue 10, p. 1176 –1188
- DOI: 10.1049/iet-cta.2010.0176
- Type: Article
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1176
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(13)
In this study, adaptive fuzzy output feedback motion/force control is investigated for wheeled inverted pendulums with unmodelled dynamics, whose states and time derivatives of the output are unavailable. The proposed adaptive fuzzy output feedback control reconstructs the system states by using a high-gain observer, and makes use of bounds online adaptation mechanism to cancel the dynamics uncertainties. Based on Lyapunov synthesis, the proposed control ensures that the system outputs track the given bounded reference signals within a small neighbourhood of zero, and guarantees zero-dynamics stability. The effectiveness of the proposed control is verified through extensive simulations.
Optimal instrumental variable method for closed-loop identification
Development and numerical investigation of new non-linear Kalman filter variants
Application of sliding mode control to swarms under conflict
Adaptive fuzzy output feedback motion/force control for wheeled inverted pendulums
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- Author(s): S.-I. Park ; J.-W. Hong ; I.-J. Ha
- Source: IET Control Theory & Applications, Volume 5, Issue 10, p. 1189 –1194
- DOI: 10.1049/iet-cta.2010.0266
- Type: Article
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p.
1189
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(6)
This study presents the exact solution to the minimum-time position control problem of electromechanical systems including linear brushless dc motor drivers. In its derivation, the authors consider fully actuator dynamics as well as physical limitations in current, voltage and jerk. In particular, it is given explicitly in feedback form. In order to demonstrate further the practical use of the authors results, the authors also present some simulation results for the case of on-the-fly control quite often required in industrial control systems. - Author(s): J. Chen ; F. Sun ; Y. Yin ; C. Hu
- Source: IET Control Theory & Applications, Volume 5, Issue 10, p. 1195 –1202
- DOI: 10.1049/iet-cta.2010.0142
- Type: Article
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p.
1195
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(8)
This study investigates the problem of state feedback robust stabilisation for discrete-time fuzzy singularly perturbed systems (SPSs) with parameter uncertainty. The considered system is approximated by Takagi–Sugeno fuzzy model. Based on a matrix spectral norm approach, new sufficient conditions, which ensure the existence of state feedback controller such that the resulting closed-loop system is asymptotically stable, are given. The gains of controllers are obtained by solving a set of ɛ-independent linear matrix inequalities (LMIs) such that, the ill-conditioned problems caused by ɛ can be easily avoided. In contrast to the existing results, the proposed method can be applied to both certain and uncertain SPSs with greater singular perturbation parameter ɛ. A numerical example is provided to illustrate the reduced conservatism of the authors’ results. - Author(s): Z.-J. Yang ; Y. Wang ; S. Kanae
- Source: IET Control Theory & Applications, Volume 5, Issue 10, p. 1203 –1213
- DOI: 10.1049/iet-cta.2010.0140
- Type: Article
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p.
1203
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Parameter adaptation and disturbance observer (DOB) have been considered as two contrastively different approaches in motion control problems. In the authors' previous work, the two techniques were merged into one control design with a theoretically guaranteed performance. A drawback of the method is that the controller has to be relatively complicated owing to the interactions between the two mechanisms. In this study, by exploiting the cascade features of backstepping design, the DOB is inserted into the position-loop which compensates for the velocity error that may not be suppressed to be sufficiently small by the adaptive mechanism owing to the presence of unparameterised uncertainties. This results in a much simpler controller since the two mechanisms are separated. Simulation results show that the proposed controller, while being much simpler than the authors' previously proposed controller, yields a comparable control performance. - Author(s): W. Li and Y. Jia
- Source: IET Control Theory & Applications, Volume 5, Issue 10, p. 1214 –1222
- DOI: 10.1049/iet-cta.2010.0240
- Type: Article
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p.
1214
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This study investigates the problem of distributed fusion for a class of jump Markov systems in a not fully-connected sensor network. A distributed information filter is proposed from the point of view of the consensus theory. To this end, the best-fitting Gaussian (BFG) approximation approach is applied to overcome the difficulty of lacking a global model for multiple model estimation fusion, and a recursive formula is presented for calculating the mean and covariance of this Gaussian distribution. Based on the approximated linear Gaussian system, local information filter is derived for each sensor and the filtering estimates are fused with its neighbouring sensor nodes using the dynamic average-consensus strategy. Performance comparison of the proposed filter with the optimal centralised fusion filter is demonstrated through a multi-static manoeuvring target-tracking simulation study. - Author(s): S.-J. Park
- Source: IET Control Theory & Applications, Volume 5, Issue 10, p. 1223 –1227
- DOI: 10.1049/iet-cta.2010.0563
- Type: Article
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p.
1223
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A competitive market is representative of the free market economy where it is well known that an invisible hand (also referred to as the Walrasian auctioneer) always achieves an equilibrium of demand and supply. In this study, the dynamic behaviours of supply and demand of a competitive market are modelled by finite-state automata. Using the discrete event models, this study shows that a competitive market controlled by the Walrasian auctioneer may fail in leading to equilibria. However, the Walrasian auctioneer can always achieve equilibria through a non-blocking supervisory control together with a government policy. - Author(s): M.W. Sun ; R.G. Yang ; Z.Q. Chen
- Source: IET Control Theory & Applications, Volume 5, Issue 10, p. 1228 –1234
- DOI: 10.1049/iet-cta.2010.0325
- Type: Article
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PID control is widely used to control stable processes; however, its application to integrating unstable processes is less common. Integrating unstable process is often approximated by an integrating-unstable-first-order-plus-dead-time model based on which the simple analytical tuning formulae of PD control are derived to meet gain and phase margin (GPM) specifications. The previous tuning approach based on GPM only takes the increasing gain margin into account; however, the decreasing gain margin is commonly more critical. Using Routh stability criterion, the decreasing gain margin is obtained by Pade approximation of the delay based on the established tuning rule. The numerical polynomial solving approach is employed to seek the feasible stability margin region, which is explicitly plotted in the 2-D plane. At the same time, a novel tuning rule based on the decreasing gain margin is presented. The results demonstrate that the feasible GPM region is a small portion of the original one. Finally, some numerical examples are provided to validate the analysis result.
Minimum-time position control of a linear brushless dc motor driver with non-zero initial condition
State feedback robust stabilisation for discrete-time fuzzy singularly perturbed systems with parameter uncertainty
New approach to an adaptive robust motion controller combined with a disturbance observer
Consensus-based distributed information filter for a class of jump Markov systems
Non-blocking supervisory control of dynamic competitive markets
Genuine feasible stability margin region for integrating unstable processes with PD control
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