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There is a growing interest in applying Stackelberg games to model resource allocation for patrolling security problems in which defenders must allocate limited security resources to protect targets from attack by adversaries. In real-world adversaries are sophisticated presenting dynamic strategies. Most existing approaches for computing defender strategies calculate the game against fixed behavioral...
The traffic signal control setting is the most important factor that impacts the road network efficiency. The problem consists on generate appropriate signal patterns by controlling the timing of the green/red light cycles at an intersection with the goal of optimally reduce congestion and the amount of time wasted stuck in traffic. This is a very complicated problem. This paper deals with the solution...
The notion of collaboration implies that related agents interact with each other looking for cooperative stability. This notion consents agents to select optimal strategies and to condition their own behavior on the behavior of others in a strategic forward looking manner. In game theory the collective stability is a special case of the Nash equilibrium called strong Nash equilibrium. In this paper...
In this paper the robust adaptive control of a multicomponent nonideal distillation column is considered. A simple dynamic neural network is used to estimate the distillation column, then a adaptive controller is proposed. Because the approximation capability of dynamic neural network is limited, a sliding mode compensator is addressed. It is shown that the effect of system uncertainties can be eliminate...
The problem addressed is the filtering of the states of a time-varying linear system subject to random disturbances and parametric unstructured uncertainties. We give an upper bound on the performance index of the proposed filter defined as the expected squared estimation error. The filter has a Kalman structure with the gain being a function of free design parameters and of a solution to an artificially...
Linear controlled stochastic differential equations (LCSDE) subject to both multiplicative and additive stochastic noises are considered. We study a robust “practical” stabilization for this class of LCSDE meaning that almost all trajectories of this stochastic model converges in a “mean-square sense” to a bounded zone located in an ellipsoidal set. Also, we present a result related to convergence...
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