This paper presents a robust fractional order controller for flexible-joint electrically driven robots under imperfect transformation of control space. The proposed approach is free from manipulator dynamics, thus free from problems associated with torque control strategy in the design and implementation. As a result, the proposed controller is simple, fast response and superior to the torque c...

This paper presents a robust fractional order controller for flexible-joint electrically driven robots under imperfect transformation of control space. The proposed approach is free from manipulator dynamics, thus free from problems associated with torque control strategy in the design and implementation. As a result, the proposed controller is simple, fast response and superior to the torque c...

In this paper the control of flexible joint manipulators is studied in detail. The model of N -axis flexible joint manipulators is derived and reformulated in the form of singular perturbation theory and an integral manifold is used to separate fast dynamics from slow dynamics. A composite control algorithm is proposed for the flexible joint robots, which consists of two main parts. Fast contro...

This paper presents a novel robust fractional PIλ controller design for flexible joint electrically driven robots. Because of using voltage control strategy, the proposed approach is free of problems arising from torque control strategy in the design and implementation. In fact, the motor's current includes the effects of nonlinearities and coupling in the robot manipulator. Therefore, cancella...

This paper proposes a family of robust counterpart for uncertain linear programs (LP) which is obtained for a general definition of the uncertainty region. The relationship between uncertainty sets using norm bod-ies and their corresponding robust counterparts defined by dual norms is presented. Those properties lead us to characterize primal and dual robust counterparts. The researchers show t...

Missing data are common in longitudinal studies due to drop-out, loss to follow-up, and death. Likelihood-based mixed effects models for longitudinal data give valid estimates when the data are missing at random (MAR). These assumptions, however, are not testable without further information. In some studies, there is additional information available in the form of an auxiliary variable known to...

In this paper, we introduce a subspace-augmented MUSIC technique for recovering the joint sparse support of a signal ensemble corrupted by additive impulsive noise. Our approach uses multiple vectors of random compressed measurements and employs fractional lower-order moments stemming from modeling the underlying signal statistics with symmetric alpha-stable distributions. We show through simul...

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context-dependent modeling is a well-known approach to increase modeling accuracy in continuous speech recognition. the most common way to implement this approach is via triphone modeling. nevertheless, the large number of such models results in several problems in model training, whilst the robust training of such models is often hardly obtained. one approach to solve this problem is via param...