We study a general setting of active noise cancellation problems from the H , point of view and present a solution that optimally limits the worst case energy gain from the interfering measurement errors, external disturbances, and initial condition uncertainty to the residual noise. The optimal bounding of this energy gain is the main characteristic of the proposed solution. To impose a finite impulse response (FIR) structure on the controller, we suggest an adaptation scheme for the weight vector of an FIR filter that approximates the H,-optimal solution. Our discussions in this paper explain; (i) why and how this new adaptive scheme generalizes previous results on the H,-optimality of the LMS algorithm, (ii) d h y it is an alternative for the widely used Filtered-X Leash-MeanSquares (FxLMS) algorithm, and (iii) how the formulation provides an appropriate framework t o address the issues of modeling error and robustness. Simulations are used to compare the performance of the proposed (approximate) H,-optimal adaptive scheme with the FxLMS algorithm.
In this paper we report on electron beam lifetime measurements as a function of scraper position, RF voltage and bunch fill pattern in SPEAR3. We then outline development of an empirical, macroscopic model using the beam-loss rate equation. By identifying the dependence of loss coefficients on accelerator and beam parameters, a numerically-integrating simulator can be constructed to compute beam decay with time. In a companion paper, the simulator is used to train a parametric, non-linear dynamics model for the system [1].
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