Blockwise Subspace Identification for Active Noise Control

In this paper, a subspace identification solution is provided for active noise control (ANC) problems. The solution is related to so-called block updating methods, where instead of updating the (feedforward) controller on a sample by sample base, it is updated each time based on a block of N samples. The use of the subspace identification based ANC methods enables non-iterative derivation and updating of MIMO compact state space models for the controller. The robustness property of subspace identification methods forms the basis of an accurate model updating mechanism, using small size data batches. The design of a feedforward controller via the proposed approach is illustrated for an acoustic duct benchmark problem, supplied by TNO Institute of Applied Physics (TNO-TPD), the Netherlands. We also show how to cope with intrinsic feedback. A comparison study with various ANC schemes, such as block filtered-U, demonstrates the increased robustness of a subspace derived controlle

Optimal and Robust Feedback Controller Estimation for a Vibrating Plate using Subspace Model Identification

This paper presents a method to estimate the H2 optimal and a robust feedback controller by means of Subspace Model Identification using the internal model control (IMC) approach. Using IMC an equivalent feed forward control problem is obtained, which is solved by the Causal Wiener filter for the H2 optimal controller. The robust variant, called the Cautious Wiener filter, optimizes the average performance w.r.t. probabilistic model errors. The identification of the Causal and Cautious Wiener filters are control-relevant. The method is illustrated by experiments on a 4-inputs 4-outputs vibrating plate with additional mass variation

Leren van Mobiliteits-Experimenten tot de Vierde Macht:: een Meta-Lab tussen vier Nederlandse Stedelijke Regio’s

Dit paper presenteert de voorlopige resultaten van het project SUMMALab waarin een nieuwe ‘meta-lab’ benadering wordt getest. SUMMALab is een meta-lab rond mobiliteits-experimenten in de Metropoolregio Amsterdam, de Metropoolregio Rotterdam-Den Haag en de gemeenten Den Haag, Delft en Rotterdam. Een meta-lab is nietzelf een lab, maar een verzamelplaats waar verschillende onderzoeken en experimenten in samenhang worden gebracht zodat er sneller en beter van de experimenten geleerd kan worden. De meta-lab benadering respecteert en ondersteunt enerzijds lokale leeragenda's en hun focus op lokale oplossingen voor lokale problemen, en gebruikt anderzijds het potentieel van lokale experimenten om bij te dragen aan een centrale leeragenda gebaseerd op de 'grote maatschappelijke uitdagingen'

Increasing the robustness of a preconditioned filtered-X LMS algorithm

This letter presents a robustification of the preconditioned Filtered-X LMS algorithm proposed by Elliott et al.. The method optimizes the average performance for probabilistic uncertainty in the secondary path and relaxes the SPR condition for global convergence. It also prevents large amplification in the pre-conditioning filters due to secondary path zeros on and/or close to the unit circle, which may yield overactuation in practical applications

Convergence analysis of the Filtered-U LMS algorithm for active noise control in case perfect cancellation is not possible

The Filtered-U LMS algorithm, proposed by Eriksson for active noise control applications, adapts the coefficients of an infinite-impulse response controller. Conditions for global convergence of the Filtered-U LMS algorithm were presented by Wang and Ren (Signal Processing, 73 (1999) 3) and Mosquera and Pérez-González (Signal Processing, 80 (2000) 5) for the case where perfect noise cancellation is achievable, which means only measurement noise remains. This paper shows that the assumption of perfect cancellation is not necessary. In real situations perfect cancellation is often not achievable due to delays and non-minimum phase zeros. The conclusion is derived by analysis of the structure of the Wiener optimal solution. This also leads to the suggestion of preconditioning filters in the Filtered-U LMS updating. The preconditioning has shown considerable increase of the convergence rate in a realistic simulation study

A decomposition approach to distributed control of dynamic deformable mirrors

Deformable mirrors with spatially invariant dynamic response can be considered as part of the class of decomposable systems. Such systems can be thought of as the interconnection of a number of identical subsystems, and they can be used to model certain classes of large scale systems. We show in this article that the technique allows the design of a distributed H2 controller for a deformable mirror of any size, with a computational cost that does not increase with the size of the mirror. The method shows a performance close to that of the centralized H2 optimal controller in a simulation example, which is about two times better (in terms of H2 norm) than the performance of a decentralized PI controller, with additional notches to suppress the high resonance frequencies of the deformable mirror. © Taylor & Francis Group, LLC

Optimal control of tip-tilt modes on-sky adaptive optics demonstration

An H2-optimal control approach for Adaptive Optics has been validated in an on-sky experiment on a solar telescope. A substantial performance improvement over the integrator control approach is demonstrated for control of the tip-tilt modes. The experimental results correspond reasonably well with simulations based on measured data