arXiv subjects

Isaac Yaesh

Publications and source records attributed to Isaac Yaesh.

4 recordsLinked to original sources

arXiv2025

Utilization of noise for the control of a class of non-linear systems

Utilization of noise for the control of a class of non-linear systems is presented. The application of state-multiplicative noise as a mean of control is far more limited then the use of standard determinis?tic gains. Nevertheless, so called Stochastic Anti Resonance (SAR) with state-multiplicative noise based control, do arise in a variety of situations such as in engineering applications, physics modelling, bi?ology, and models of visuo-motor tasks. Linear Matrix Inequalities based conditions from recent publications are reviewed, that character?ize stochastic stability of such nonlinear systems applying SAR. While those results dealt with systems that are, apriori, modelled using sec?tor bounded nonlinearities, we demonstrate that more general systems that can be approximated as such, can be also controlled using SAR.

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arXiv2020

Training without Gradients -- A Filtering Approach

A particle filtering approach is suggested for the training of multi-layer neural networks without utilizing gradients calculation. The network weights are considered to be the components of the estimated state-vector of a noise driven linear system, whereas the neural network serves as the measurement function in the estimation problem. A simple example is used to provide a preliminary demonstration of the concept, which remains to be further studied for training deep neural networks.

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arXiv2020

Static Output Feedback in an Anisotropic Norm Setup Revisited

The synthesis problem of static output feedback controllers within the anistropic-norm setup is revisited. A tractable synthesis approach involving iterations over a convex optimization problem is suggested, similarly to existing results for the Hinfinity-norm minimization case. The results are formulated by a couple of Linear Matrix Inequalities coupled via a bilinear equality, revealing, as in the Hinfinity case, the duality between the control-type and filtering type LMIs and allowing a tractable iterative method to cope with practical static output feedback synthesis problems. The resulting optimization scheme is then applied to a flight control problem, where the merit of the anisotropic norm setup is shown to provide a useful trade-off between closed loop response and feedback gains.

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arXiv2020

Optimal Disturbance Attenuation Approach with Measurement Feedback to Missile Guidance

Pursuit-evasion differential games using the Disturbance Attenuation approach are revisited. Under this approach, the pursuer actions are considered to be control actions, whereas all external actions, such as target maneuvers, measurement errors and initial position uncertainties, are considered to be disturbances. Two open issues have been addressed, namely the effect of noise on the control gains, and the effect of trajectory shaping on the solution. These issues are closely related to the question of the best choice for the disturbance attenuation ratio. Detailed analyses are performed for two simple pursuit-evasion cases: a Simple Boat Guidance Problem and Missile Guidance Engagement.

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