The proposed article deals with uncertain description of permanent-magnet DC motor Maxon RE 35 via parametric uncertainty and H-infinity controller design. There was analyzed influence of uncertainties of the particular motor parameters on the model behavior. Consequently there was designed an H-infinity controller via Matlab functions. The behavior of the obtained controller was analyzed on th...

Melioration-defined as choosing a lesser, local gain over a greater longer term gain-is a behavioral tendency that people and pigeons share. As such, the empirical occurrence of meliorating behavior has frequently been interpreted as evidence that the mechanisms of human choice violate the norms of economic rationality. In some environments, the relationship between actions and outcomes is know...

The fuzzy set is one of the powerful tools used to describe an uncertain environment. As well as quantifying any potential return and risk, portfolio liquidity is taken into account and a linear programming model for portfolio rebalancing with transaction costs is proposed. The level of return that an investor might aspire to, the risk and the liquidity of portfolio are vague in an uncertain fi...

It is difficult to understand a scene from visual information in uncertain real world. Since Bayesian network (BN) is known as good in this uncertainty, it has received significant attention in the area of vision-based scene understanding. However, BN-based modeling methods still have the difficulties in modeling complex relationships and combining several modules, as well as the high computati...

If the future is uncertain, optimal intertemporal decisions rely on anticipating one’s own optimal future behavior as is typical in dynamic programming. Our aim is to detect experimentally stylized facts about intertemporal decision making in a rich stochastic environment. Compared to previous experimental studies our experimental design is more complex since the time horizon is uncertain and t...

 We consider a generalization of the classical quadratic assignment problem, where coordinates of locations are uncertain and only upper and lower bounds are known for each coordinate. We develop a mixed integer linear programming model as a robust counterpart of the proposed uncertain model. A key challenge is that, since the uncertain model involves nonlinear objective function of the ...

Because a robot usually operates in environments with uncertain information, path planning for the robot should be performed in real-time so as to match process speed based on sensors. This paper presents an efficient approach to behavior based motion planning of a manipulator with many degrees of freedom, which is based on an algorithm for fast mapping obstacles from a robot's workspace (W-spa...

Our research has successfully extended the planningas-satisfiability paradigm to support contingent planning under uncertainty (uncertain initial conditions, probabilistic effects of actions, uncertain state estimation). Stochastic satisfiability (SSAT), ty pe of Boolean satisfiability problem in which some of the variables have probabilities attached to them, forms the basis of this extension....

We discuss the problem of scheduling tasks that consume uncertain amounts of a resource with known capacity and where the tasks have uncertain utility. In these circumstances, we would like to find schedules that exceed a lower bound on the expected utility when executed. We describe several different event execution models that motivate different formulations of the expected value of a schedul...

This paper presents a new adaptive control architecture to achieve stabilization and command following of uncertain dynamical systems with improved transient performance. The proposed framework is predicated on a new and novel controller architecture involving an artificial basis function in the update law. Specifically, the proposed artificial basis function allows to shape the system error, w...