Real-data testing results of a real-time nonlinear freeway traffic state estimator are presented with a particular focus on its adaptive features. The pursued general approach to the real-time adaptive estimation of complete traffic state in freeway stretches or networks is based on stochastic nonlinear macroscopic traffic flow modeling and extended Kalman filtering. One major innovative aspect...

In some statistical process control applications, the combination of both variable and attribute quality characteristics which are correlated represents the quality of the product or the process. In such processes, identification the time of manifesting the out-of-control states can help the quality engineers to eliminate the assignable causes through proper corrective actions. In this paper, f...

This paper presents a reset state estimator to improve the position estimation for motion control systems with sensor quantization. The reset scheme is guided by the idea that the actual output is known exactly to be at the mid-point of the two consecutive quantizer levels and is within the range of a quantizer level bounded by half of quantization step size. Hence, using this information to up...

Development of an adaptive target state estimation algorithm for use with advanced missile guidance laws is presented. The target state estimator employs a linear neural network as the decisionmaking element in a nine-state dynamic model of the target. A Kalman filtering algorithm is used to estimate the neural network weights and the target states. The estimator performance is evaluated in a p...

Todays, use of combination of two or more methods was considered to control of systems. In this paper ispresented how to design of a nonlinear H∞ (NL-H∞) controller for flexible joint robot (FJR) based on boundedUKF state estimator. The UKF has more advantages to standard EKF such as low bios and no need toderivations. In this research, based on spong primary model for FJRs, same as rigid robot...

One may consider a discrete-event simulation as a Markov chain evolving on a suitably rich state space. One way that regenerative cycles may be constructed for general state-space Markov chains is to generate auxiliary coinflip random variables at each transition, with a regeneration occurring if the coin-flip results in a success. The regenerative cycles are therefore randomized with respect t...

An event-based state estimation problem is considered where the state of a dynamic system is observed from multiple distributed sensors that sporadically transmit their measurements to a remote estimator over a common bus. The common bus allows each sensor to run a copy of the remote estimator and to make the triggering decision based on this estimate: a measurement is transmitted only if its p...