This paper considers a distributed convex optimization problem over time-varying multi-agent network, where each agent has its own decision variables that should be set so as to minimize individual objective subject local constraints and global coupling constraints. Over directed graphs, we propose algorithm incorporates the push-sum protocol into dual sub-gradient methods. Under convexity assu...

The paper presents a novel type of fuzzy sets, called time-Varying Fuzzy Sets (VFS). These fuzzy sets are based on the Gaussian membership functions, they are depended on the error and they are characterized by the displacement of the kernels to both right and left side of the universe of discourse, the two extremes kernels of the universe are fixed for all time. In this work we focus only on t...

Mechanical machining processes are common manufacturing strategies to re-shape materials to desired specification. The mechanistic approach has revealed the mechanics of the machining processes with various parameters determined. The aim of this work is to investigate the impact of swept angle optimization and their influence on the specific cutting energy in milling AISI 1045 steel alloy. This...

gravitational search algorithm (gsa) is one of the newest swarm based optimization algorithms, which has been inspired by the newtonian laws of gravity and motion. gsa has empirically shown to be an efficient and robust stochastic search algorithm. since introducing gsa a convergence analysis of this algorithm has not yet been developed. this paper introduces the first attempt to a formal conve...

Gravitational search algorithm (GSA) is one of the newest swarm based optimization algorithms, which has been inspired by the Newtonian laws of gravity and motion. GSA has empirically shown to be an efficient and robust stochastic search algorithm. Since introducing GSA a convergence analysis of this algorithm has not yet been developed. This paper introduces the first attempt to a formal conve...

Gravitational search algorithm (GSA) is one of the newest swarm based optimization algorithms, which has been inspired by the Newtonian laws of gravity and motion. GSA has empirically shown to be an efficient and robust stochastic search algorithm. Since introducing GSA a convergence analysis of this algorithm has not yet been developed. This paper introduces the first attempt to a formal conve...

In this paper, a time-varying two-phase (TVTP) optimization neural network is proposed based on the two-phase neural network and the time-varying programming neural network. The proposed TVTP algorithm gives exact feasible solutions with a finite penalty parameter when the problem is a constrained time-varying optimization. It can be applied to system identification and control where it has som...

This paper focuses on the problem of finite-time boundedness and finite-time passivity of discrete-time T-S fuzzy neural networks with time-varying delays. A suitable Lyapunov--Krasovskii functional(LKF) is established to derive sufficient condition for finite-time passivity of discrete-time T-S fuzzy neural networks. The dynamical system is transformed into a T-S fuzzy model with uncertain par...

In this paper we consider the Optimal robust disturbance attenuation problem (ORDAP) for continuous time-varying systems subject to time-varying unstructured uncertainty. We show that for causal (possibly time-varying) continuous systems, ORDAP is equivalent to finding the smallest fixed point of a ‘two-disc’ type optimization problem under time-varying feedback control laws. Duality is applied...