@conference {
	title = {Decentralized control of autonomous vehicles},
	author = {Baras, John S., Tan, Xiaobo., Hovareshti, Pedram.},
	year = {2003},
	month = {12/2003},
	abstract = {Decentralized control methods are appealing in coordination of multiple vehicles due to their low demand for long-range communication and their robustness to single-point failures. In this paper we explore a decentralized approach to path generation for a group of vehicles in a battlefield scenario. The mission is to maneuver the vehicles to cover a target area while avoiding obstacles and threats during the maneuver. Each vehicle makes its moving decision by minimizing a potential function that encodes information about its neighbours, obstacles, threats and the target. Preliminary analysis of vehicle behaviors is conducted. Simulation has shown that this approach leads to interesting emergent behaviors, and the behaviors can be varied by adjusting the weighting coefficients of different potential function terms.},
	address = {Maui, Hawaii},
	booktitle = {42nd IEEE Conference on Decision and Control},
	pages = {pp. 1532-1537}
}
@conference {
	title = {Jointly optimal quantization, estimation, and control of hidden Markov chains},
	author = {Baras, John S., Tan, Xiaobo., Xi, Wei.},
	year = {2003},
	month = {12/2003},
	abstract = {It is of interest to understand the tradeoff between the communication resource consumption and the achievable system performance in networked control systems. In this paper we explore a general framework for tradeoff analysis and decision making in such systems by studying joint quantization, estimation, and control of a hidden Markov chain. Dynamic programming is used to find the optimal quantization and control scheme that minimizes a weighted combination of different cost terms including the communication cost, the delay, the estimation error, and the running cost. Simulation and analysis based on example problems show that this approach is able to capture the tradeoffs among competing objectives by adjusting the cost weights.},
	address = {Maui, Hawaii},
	booktitle = {42nd IEEE Conference on Decision and Control},
	pages = {pp. 1098-1103}
}
@conference {
	title = {A dynamic model for magnetostrictive hysteresis},
	author = {Tan, Xiaobo., Baras, John S., Krishnaprasad, P S.},
	year = {2003},
	month = {06/2003},
	abstract = {The rate-dependent hysteresis present in thin magnetostrictive actuators can be captured by a dynamic model, consisting of a Preisach operator coupled to an ordinary differential equation in an unusual way. The model presents interesting problems in analysis and computation due to its special structure. In this paper, we first transform the model into a more amenable form and gain insight into the model by introducing a new hysteretic operator. Then we investigate some system-theoretic properties of the model: stability of equilibria, input-output stability, reachability~and observability. Existence of periodic solutions under periodic forcing is also established. Finally, numerical integration schemes for the model are discussed.},
	address = {Denver, Colorado},
	booktitle = {2003 American Control Conference},
	pages = {pp. 1074-1079}
}
@conference {
	title = {A robust control framework for smart actuators},
	author = {Tan, Xiaobo., Baras, John S.},
	year = {2003},
	month = {06/2003},
	abstract = {Hysteresis in smart actuators presents a challenge in control of these actuators. A fundamental idea to cope with hysteresis is inverse compensation. But due to the open loop nature of inverse compensation, its performance is susceptible to model uncertainties and to errors introduced by inverse schemes. In this paper, we develop a robust control framework for smart actuators by combining inverse control with the l/sub 1/ robust control theory, where the inversion error is modeled as an exogenous disturbance with a magnitude bound quantifiable in terms of parameter uncertainties and inversion schemes. Through the example of controlling a magnetostrictive actuator, we present a systematic controller design method which guarantees robust stability and robust trajectory tracking while taking actuator saturation into account. Simulation and experimental results are provided.},
	address = {Denver, Colorado},
	booktitle = {2003 American Control Conference},
	pages = {pp. 4645-4650}
}
