Use of particle filters in an active control algorithm for noisy nonlinear structural dynamical systems

Sajeeb, R.; Manohar, C.S.; Roy, Debasish

doi:10.1016/j.jsv.2007.05.043

Cited by 13 publications

(4 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Particle filters can be used to track the time-varying state of nonlinear dynamical systems. They have been applied to structural dynamics problems since (at least) 2006 [8] and have, for example, been used to aid active control [9], predict the chaotic behaviour of nonlinear systems [10] and track the time-varying parameters present in vehicle-structure interaction problems [11]. Being a wellestablished technique, only a brief description is given here (see [12] for a tutorial).…”

Section: Particle Filtersmentioning

confidence: 99%

Using Particle Filters to Analyse the Credibility in Model Predictions

Green

2015

AMM

View full text Add to dashboard Cite

Models are often used to make predictions far from the region where they were trained and validated. In this paper attempts are made to analyse the credibility that can be placed in such predictions. The proposed approach involves treating a model’s parameters as time-variant (even if it is believed that this is not the case), before utilising Bayesian tracking techniques to realise parameter estimates. An example is used to demonstrate that, relative to a Bayesian approach where the parameters are assumed to be time-invariant, treating the parameters as time-variant can reveal important flaws in the model and raise questions about its ability to make credible predictions.

show abstract

Section: Particle Filtersmentioning

confidence: 99%

Using Particle Filters to Analyse the Credibility in Model Predictions

Green

2015

AMM

View full text Add to dashboard Cite

show abstract

“…Linear techniques such as optimal control [93][94][95], pole placement [96], and H-infinity [54] have been modified to be used in active structural control. Non-linear problems have also been considered using techniques such as sliding mode control [97][98][99], Lyapunov control design [73], particle filters [100], and adaptive approaches [101] (discussed in Section 6)see reference [102] for a review of techniques used for active aeroelastic control. Adaptive approaches have also been applied to vibration absorber applications using other actuation systems such as shape memory alloys, see, for example references [103] or magnetostrictive alloys [104].…”

Section: Active Vibration Controlmentioning

confidence: 99%

A review of non-linear structural control techniques

Wagg

Neild

2011

Proceedings of the Institution of Mechanical Engineers, Part C:

View full text Add to dashboard Cite

In this articles the authors present a review of non-linear structural control techniques. This is an area of growing importance in a range of engineering applications, where non-linear behaviour is encountered. Structural control is usually divided into three main areas: (a) passive (b) semi-active, and (c) active control. This article follows this convention, and highlights in each section the relevant state of the art for non-linear systems, with additional references to related linear approaches.

show abstract

“…We use the proposed filter in the active control of the Duffing oscillator, described in the previous section, assuming that the parameters α, β and c are unknown. We had earlier studied the problem of nonlinear system control, where standard SIS and bootstrap filters were employed for state estimation [23] and the system parameters were assumed to be known. Here we address the problem of combined parameter estimation and control using the semi-analytical filtering strategy developed herein.…”

Section: Parameter Estimation In Active Controlmentioning

confidence: 99%