Performance Of Nonlinear Control System Research Articles

Hellinger distance based probability distribution approach to performance monitoring of nonlinear control systems

Control performance monitoring has attracted great attention in both academia and industry over the past two decades. However, most research efforts have been devoted to the performance monitoring of linear control systems, without considering the pervasive nonlinearities (e.g. valve stiction) present in most industrial control systems. In this work, a novel probability distribution distance based index is proposed to monitor the performance of non-linear control systems. The proposed method uses Hellinger distance to evaluate change of control system performance. Several simulation examples are given to illustrate the effectiveness of the proposed method.

Introduction to the special issue on ‘Performance of nonlinear control systems’

Introduction to the special issue on ‘Performance of nonlinear control systems’

Call for Papers: International Journal of Robust and Nonlinear Control Performance of Nonlinear Control Systems

The International Journal of Robust and Nonlinear Control is inviting papers for a special issue on ‘Performance of Nonlinear Control Systems’ (for a description of the scope, see below). Authors are kindly requested to submit their papers by October 1st 2011 following the link Online Submission on the journals homepage: wileyonlinelibrary.com/journal/rnc. Authors must select Nathan van de Wouw or Marcel Heertjes as the Submitting Editor. Each submission must be clearly identified as a submission for this special issue by entering Performance of Nonlinear Control Systems in the Special Issue Title Field. The manuscripts should be prepared in accordance with the publication format described in ‘For Authors’ on the journal homepage. Scope: The topic of this special issue is the performance analysis and performance-oriented design of nonlinear control systems. Nonlinear control has received wide attention in the systems and control literature and examples of the practical application of nonlinear control in practice are widely available. Still, the majority of the (theoretical) advances made are related to the design of stabilizing nonlinear controllers for (nonlinear) plants, indeed no easy task in general, while not accounting for performancerelated issues. Moreover, in many industries, still the application of linear control techniques prevails. One of the main reasons is the fact that performance is key in practical applications, be it in the form of transient performance criteria, such as rise time and overshoot, or in the form of sensitivity to perturbations, such as measurement noise and external disturbances. On the one hand, linear control techniques have been so successful since a profound (frequencydomain) framework for performance analysis exists. On the other hand, linear control is subject to fundamental (performance) limitations, a famous example of which is the Bode sensitivity integral. Nonlinear control may overcome such limitations. To harvest the full potential of nonlinear control in practice, the further development of powerful performance analysis tools for nonlinear control systems and matching performance-based design techniques for nonlinear controllers are needed, hence this special issue. Resuming, topics of particular interest are, but not limited to: • Performance limitations in linear control systems and how nonlinear control may be employed to overcome such limitations. • Tools for performance analysis of nonlinear control systems. • Performance-based synthesis techniques of nonlinear controllers. • (Industrial) application of high-performance nonlinear controllers.

Control of magnetic suspension systems by maintaining continuous equilibrium points

The paper describes a technique for enhancing the performance of nonlinear control systems in general but magnetic suspension systems in particular. The main consideration in determining controller structure is based on a heuristic idea of “maintaining continuous equilibrium points”. For the case investigated here in addition to the PID Control an adaptive reference current is shown to improve markedly response to external force disturbances. The controller designed is simple, robust and tunable.

On Performance Bounds for Control Systems

A technique based on Lyapunov’s second method is described for deriving bounds for the performance of nonlinear control systems. As an illustration, a performance bound is derived for systems associated with the so-called Lurie problem. As opposed to conventional sensitivity analysis, performance bounds are also determined for systems designed using grossly inaccurate models.

Effect of distortion on the performance of non-linear control systems

The paper considers the behaviour of a simple saturating control system subjected to a random input signal, evaluating the variation of error with forward loop gain. Booton's linearization technique is the foundation of the analysis, and it is shown that this method predicts that the error will decrease monotonically to a constant value as the forward gain is increased indefinitely. However, this approximate method neglects the additional error introduced by the distorting effect of the non-linear characteristic. As the forward gain is increased so that the non-linear operation becomes more pronounced, distortion, and the error due to this distortion, increase. Therefore, to determine optimum operating conditions it is necessary to show how the total error, including that due to distortion, varies with forward loop gain. For the particular system considered, it is found that, as the forward loop gain is increased, the reduction in error of the linear system always exceeds the increase in error owing to greater distortion. As a result, the mean-square value of the error is a minimum for infinite forward loop gain. Distortion has an important influence on the error spectrum at low frequencies, and fundamentally limits performance at frequencies much less than the natural frequency of the system. Zero error at these very low frequencies is possible only when the forward loop gain is so small that saturation has a negligible effect. Thus the optimum forward loop gain depends on the particular application of the control system. To minimize the mean-square magnitude of the error signal, the forward loop gain should be as high as possible. When the criterion of performance is based on the error at very low frequencies, then a lower forward loop gain is preferable. Experimental results are presented for the particular system analysed.