We study strongly convex distributed optimization problems where a set of agents are interested in solving separable problem collaboratively. In this paper, we propose and two time-scale decentralized gradient descent algorithm for broad class lossy sharing information over time-varying graphs. One fades out the (lossy) incoming from neighboring agents, one regulates local loss functions' gradi...

In this paper, we consider the Byzantine-robust stochastic optimization problem defined over decentralized static and time-varying networks, where agents collaboratively minimize summation of expectations local cost functions, but some are unreliable due to data corruptions, equipment failures or cyber-attacks. The agents, which called as Byzantine thereafter, can send faulty values their neigh...

This paper designs an Optimized Adaptive Combined Hierarchical Sliding Mode Controller (OACHSMC) for a time-varying crane model in presence of uncertainties. Uncertainties have always been one of the most important challenges in designing control systems, which include the unknown parameters or un-modeled dynamics in the systems. Sliding mode controller (SMC) is able to compensate the system in...

• Delay sensitive multimedia applications are booming over a variety of time-varying networks (e.g. sensor networks, WiMax, Wireless LAN, etc.) • Existing dynamic distributed network environments cannot provide adequate support for delay-sensitive multimedia applications • This problem has been investigated for a decade, but we still do not have efficient solutions for it.

this paper presents a new observer design methodology for a time varying actuator fault estimation. a new linear matrix inequality (lmi) design algorithm is developed to tackle the limitations (e.g. equality constraint and robustness problems) of the well known so called fast adaptive fault estimation observer (fafe). the fafe is capable of estimating a wide range of time-varying actuator fault...