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Control Theory & Applications, IET

Issue 1 • Date January 2009

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Displaying Results 1 - 13 of 13
  • Anti-windup design: an overview of some recent advances and open problems

    Page(s): 1 - 19
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (351 KB)  

    The anti-windup technique which can be used to tackle the problems of stability and performance degradation for linear systems with saturated inputs is dealt with. The anti-windup techniques which can be found in the literature today have evolved from many sources and, even now, are diverse and somewhat disconnected from one another. In this survey, an overview of many recent anti-windup techniques is provided and their connections with each other are stated. The anti-windup technique is also explained within the context of its historical emergence and the likely future directions of the field are speculated. The focus is on so-called dasiamoderndasia anti-windup techniques which began to emerge during the end of the 20th century and which allow a priori guarantees on stability to be made. The survey attempts to provide constructive LMI conditions for the synthesis of anti-windup compensators in both global and local contexts. Finally, some interesting extensions and open problems are discussed, such as nested saturations, the presence of time delays in the state or the input, and anti-windup for non-linear systems. View full abstract»

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  • An innovative method for estimating the roll angle in two-wheeled vehicles is proposed. the roll angle is a crucial variable in the dynamics of two-wheeled vehicles, since it greatly affects the behaviour of the tire-road contact forces. hence, the capability of providing in real time a reliable measure of such quantity allows us to evaluate the dynamic properties of the vehicle and its tyres, and represents the enabling technology for the design of advanced braking, traction and stability control systems. the method proposed is based on a lowcost sensor configuration, suitable for industrial purposes. the validity of the proposed approach is assessed in a multi-body motorbike simulator environment and also on an instrumented test vehicle.

    Page(s): 20 - 32
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1000 KB)  

    An innovative method for estimating the roll angle in two-wheeled vehicles is proposed. The roll angle is a crucial variable in the dynamics of two-wheeled vehicles, since it greatly affects the behaviour of the tire-road contact forces. Hence, the capability of providing in real time a reliable measure of such quantity allows us to evaluate the dynamic properties of the vehicle and its tyres, and represents the enabling technology for the design of advanced braking, traction and stability control systems. The method proposed is based on a low-cost sensor configuration, suitable for industrial purposes. The validity of the proposed approach is assessed in a multi-body motorbike simulator environment and also on an instrumented test vehicle. View full abstract»

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  • Adaptive machine tool system regulation

    Page(s): 33 - 48
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1087 KB)  

    Least effort controller design procedures, for multivariable, machine tool models, are considered. The employment of these regulators for adaptive system analysis is proposed. An approximate relationship between the nonlinear, stochastic process system dynamics and the linear, mid-range model is employed. Model-reference, adaptive, multivariable control is advocated with the model-system error vector augmenting the actuator signals, during the system transient. The amplitude of the model-system uncertainty and the guarantee of closed-loop stability are established as mandatory performance requirements. To illustrate the theoretical procedures outlined, a nonlinear, distributed-lumped parameter model is employed, in a machine tool system application study. An adaptive model-reference control strategy is formulated using a simple, analytical representation for the system. The response of the adaptive system, following input and cutting load disturbances, is computed and the effectiveness of this form of controller is commented upon. View full abstract»

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  • Iterative learning control with initial rectifying action for nonlinear continuous systems

    Page(s): 49 - 55
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (235 KB)  

    A new iterative learning control (ILC) method with initial rectifying action for nonlinear continuous multivariable systems is presented. Unlike general ILC techniques, the proposed ILC approach allows initial outputs of an ILC system at different iterations to fluctuate randomly around the initial value of the desired output. The proposed strategy includes an initial rectifying action of ILC on a very small initial time interval, and pursues the reference trajectory tracking beyond the initial time interval. The output tracking error beyond the initial time interval can be driven to a residual set whose size depends on the estimation error of input matrix. A numerical example is used to illustrate the effectiveness of the proposed ILC approach. View full abstract»

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  • Tracking control of sampled-data fuzzy-model-based control systems

    Page(s): 56 - 67
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (221 KB)  

    The tracking control approach for the sampled-data fuzzy-model-based control systems is presented. Compared with the stabilisation problem, tracking control problem is more difficult as the system states of the nonlinear plant are required to be driven to follow those of the stable reference model. A sampled-data fuzzy controller is proposed to realise the tracking control problem. The sampling activity introduces discontinuity, which complicates the closed-loop system dynamics and makes the system analysis difficult. As a result, the stability analysis approach used in pure-continuous fuzzy control systems cannot be applied. Furthermore, favourable characteristics that lead to relaxed stability analysis results vanish because of the existence of the sampling activity. The system stability is investigated using the Lyapunov-based approach. The membership function information of both fuzzy model and fuzzy controller is employed to alleviate the conservativeness of the stability analysis results. LMI-based stability conditions are derived to aid the design of stable sampled-data fuzzy-model-based tracking control systems. An application example is given to illustrate the merits of the proposed approach. View full abstract»

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  • Stochastic output feedback controller for singular Markovian jump systems with discontinuities

    Page(s): 68 - 78
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (198 KB)  

    The class of continuous-time linear Markovian jump singular systems with discontinuities has been dealt with. Based on the stochastic stability in mean square sense of the system under study, a sufficient condition is proposed for the design of an output feedback controller which guarantees that the closed-loop system is piecewise regular, impulse-free and stochastically stable in mean square sense. First, the proposed approach is established in terms of bilinear and linear matrix inequalities. Then, the sequential linear programming matrix method is used to convert the nonlinear and non-convex output feedback problem on a convex optimisation one. A numerical example is presented to show the usefulness of the proposed results. View full abstract»

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  • Design of proportional-integral observers for discrete-time descriptor linear systems

    Page(s): 79 - 87
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (173 KB)  

    A type of proportional-integral observers for discrete-time linear systems is proposed. Based on a complete parametric solution to the generalised Sylvester matrix equation, a parametric design approach for such a type of observers is proposed. The proposed approach provides all the gain matrices of the observer, gives the parametric expression for the corresponding finite left eigenvector matrix of the observer system matrix and guarantees the regularity of the observer system. A numerical example is provided to show the design procedure and illustrate the effectiveness of the proposed approach. View full abstract»

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  • Improved delay-dependent stability analysis for uncertain stochastic hopfield neural networks with time-varying delays

    Page(s): 88 - 97
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (180 KB)  

    The problem of delay-dependent stability analysis for uncertain stochastic Hopfield neural networks with time delays is investigated. The parametric uncertainties are norm-bounded and the delays are time-varying. On the basis of Lyapunov-Krasovskii approach, new stochastic stability conditions with delay dependence are formulated in terms of linear matrix inequalities. In the derivations, some cross terms, which are ignored in the existing methods, are considered by introducing some free-weighting matrices. Two illustrative examples are proposed to demonstrate the improvement of our results over the previous ones. View full abstract»

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  • Frequency-dependent approach to model validation for iterative identification and control schemes

    Page(s): 98 - 109
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (448 KB)  

    Classical validation methods dasiaacceptdasia or dasiarejectdasia a model as a valid representation of a plant for some intended use. However, this binary decision has several problems. First, models are neither good nor bad but have a certain valid frequency range and secondly the procedure gives no insight into why the model is not useful or how to improve the model. Moreover within the framework of iterative identification and control design the model validation issue arises the following requirements: (i) Is it possible to improve an existing model? (ii) How can the model be improved? and (iii) What performance increase can provide the designed controller? These facts question the suitability of traditional model validation schemes in general and their suitability for iterative control schemes in particular. We present a new validation procedure that overcomes these problems by performing a frequency-dependent model validation. The validation procedure is then more informative because of its frequency information content. As a result the same model can be validated for some frequency band and invalidated for a distinct frequency range. View full abstract»

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  • Dilated model predictive control strategy for linear parameter-varying systems with a time-varying terminal set

    Page(s): 110 - 120
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (206 KB)  

    We propose a model predictive control (MPC) strategy for input-saturated polytopic linear parameter-varying (LPV) discrete-time systems. Under the hypothesis that the plant parameter is measurable at each time instant, a dilation technique and parameter time-varying Lyapunov functions are exploited to reduce the conservativeness of pre-existing robust MPC paradigms. The contribution of this paper is to extend the MPC scheme presented in (Casavola et al. 2006) to the general case of control horizons of arbitrary length N, by considering the terminal constraint set to be time-varying. Feasibility and closed-loop stability of this strategy are proved and a final numerical example presented in order to show performance improvements with respect to pre-existing techniques. View full abstract»

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  • Robust model predictive control with zone control

    Page(s): 121 - 135
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (360 KB)  

    Model predictive control (MPC) is usually implemented as a control strategy where the system outputs are controlled within specified zones, instead of fixed set points. One strategy to implement the zone control is by means of the selection of different weights for the output error in the control cost function. A disadvantage of this approach is that closed-loop stability cannot be guaranteed, as a different linear controller may be activated at each time step. A way to implement a stable zone control is by means of the use of an infinite horizon cost in which the set point is an additional variable of the control problem. In this case, the set point is restricted to remain inside the output zone and an appropriate output slack variable is included in the optimisation problem to assure the recursive feasibility of the control optimisation problem. Following this approach, a robust MPC is developed for the case of multi-model uncertainty of open-loop stable systems. The controller is devoted to maintain the outputs within their corresponding feasible zone, while reaching the desired optimal input target. Simulation of a process of the oil refining industry illustrates the performance of the proposed strategy. View full abstract»

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  • Robust adaptive terminal sliding mode-based synchronised position control for multiple motion axes systems

    Page(s): 136 - 150
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (874 KB)  

    A novel robust adaptive terminal sliding mode position synchronised control (RATSMPSC) approach is developed for the operation of multiple motion axes systems. The RATSMPSC structure is designed in cross-coupling error space to stabilise position tracking of each axis while coordinating its motion with other axes in finite time. The criterion for the design is that any position error and synchronisation error should be converged to zero in finite time simultaneously. An adaptive mechanism is employed to estimate controller parameters so that the request of prior knowledge of the bounds of system uncertainty can be alternatively resolved. The corresponding stability analysis is presented to lay a foundation for a theoretical understanding to the underlying issues as well as safely operating real systems. The proposed approach has strong rejection capacity against external disturbances and robustness to deal with model uncertainties. An illustrative example is initially simulated to demonstrate the performance of the approach. View full abstract»

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  • Combined direct and indirect adaptive control for a class of nonlinear systems

    Page(s): 151 - 159
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (186 KB)  

    A new adaptive control methodology is proposed for a class of state feedback linearisable nonlinear systems. The new scheme combines direct and indirect adaptive control regimes in an effort to improve speed and accuracy of the adaptation which would lead to increased tracking performance. The adaptive scheme is a certainty equivalence-based methodology and can be viewed as the modified version of a direct adaptive controller. The parameter update dynamics is driven both by the identification error and the tracking error. Closed-loop error dynamics is shown to be stable by using Lyapunov analysis with tracking error and identification error convergence. The proposed method is applied for the control of a typical auto catalysed chemical reaction in order to demonstrate the efficient use of the algorithm when compared with a direct adaptive scheme. View full abstract»

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IET Control Theory & Applications is devoted to control systems in the broadest sense, covering new theoretical results and the applications of new and established control methods.

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