@conference {
	title = {Event-Triggered Controller Synthesis for Dynamical Systems withTemporal Logic Constraints},
	author = {Maity, Dipankar., Baras, John S.},
	year = {2018},
	month = {06/2018},
	abstract = {In this work, we propose an event-triggered control framework for dynamical systems with temporal logical constraints. Event-triggered control methodologies have proven to be very efficient in reducing sensing, communication and computation costs. When a continuous feedback control is replaced with an event-triggered strategy, the corresponding state trajectories also differ. In a system with logical constraints, such small deviation in the trajectory might lead to unsatisfiability of the logical constraints. In this work, we develop an approach where we ensure that the event-triggered state trajectory is confined within an ~tube of the ideal trajectory associated with the continuous state feedback. At the same time, we will ensure satisfiability of the logical constraints as well. Furthermore, we show that the proposed method works for delayed systems as long as the delay is bounded by a certain quantity.},
	address = {Milwaukee USA},
	booktitle = {2018 American Control Conference},
	pages = {pg. 1134-1138}
}
@conference {
	title = {Covariance-Based Transmission Power Control for Estimation over Wireless Sensor Networks},
	author = {Soleymani, Touraj., Zoppi, Samuel, Vilgelm, Mikhail, Hirche, Sandra., kellerer, Wolfgang, John S. Baras},
	year = {2018},
	month = {06/2018},
	abstract = {In this study, we would like to design a transmission power control mechanism for minimizing the transmit power of a wireless sensor node subject to a constraint on the quality of estimation at a remote estimator. In particular, we measure the estimation distortion by a mean square error function, and model the transmit power as a function of the packet success rate using the IEEE 802.15.4 standard which was formed for the specification of low-data-rate and low-power wireless communication. We formulate the problem with an infinite horizon discounted cost function. We show that there is a separation between the designs of the optimal estimator and optimal transmit power policy. Then, we use dynamic programming to characterize the optimal transmit power policy in terms of the estimation error covariance. Finally, we propose approximate value iteration as an approximation algorithm to calculate a near-optimal transmit power policy.},
	address = {Limassol, Cyprus},
	booktitle = {European Control Conference 2018},
	pages = {pp. 857-862}
}
@conference {
	title = {Stochastic Control Formulation of The Car Overtake Problem},
	author = {Raghavan, Aneesh., Wei, Jieqiang., Baras, John S., Johansson, Karl Henrik.},
	year = {2018},
	month = {06/2018},
	abstract = {~In this paper, we consider the classic car overtake problem. There are three cars, two moving along the same direction in the same lane while the third car moves in the direction opposite to that of the first two cars in the adjacent lane. The objective of the trailing car is to overtake the car in front of it avoiding collision with the other cars in the scenario. The information available to the trailing car is the relative position, relative velocities with respect to other cars and its position and past actions. The relative position and relative velocity information is corrupted by noise. Given this information, the car needs to make a decision as to whether it wants to overtake or not. We present a control algorithm for the car which minimizes the probability of collision with both the cars. We also present the results obtained by simulating the above scenario with the control algorithm. Through simulations we study the effect of the variance of the measurement noise and the time at which the decision is made on the probability of collision.},
	address = {Savona, Italy},
	booktitle = {15th IFAC Symposium on Control in Transportation Systems},
	pages = {pp. 124-129}
}
