Journal Papers

• N. Bezzo, R. Fierro, A. Swingler, and S. Ferrari, “Mobile Router Networks: A Disjunctive Programming Approach,” International Journal of Robotics and Automation, submitted.
• S. Ferrari, G. Zhang, and T. Wettergren, “Probabilistic Track Coverage in Cooperative Sensor Networks,” IEEE Transactions on Systems, Man, and Cybernetics - Part B, in revision.
• K. C. Baumgartner, S. Ferrari, and A. Rao, “Optimal Control of a Mobile Sensor Network for Cooperative Target Detection,” IEEE Journal of Oceanic Engineering, Vol. 34, No. 4, pp. 678-697, October 2009.  [PDF]
• K. C. Baumgartner, S. Ferrari, and T. Wettergren, “Robust Deployment of Ocean Sensor Networks,” IEEE Sensors Journal, Vol. 9, No. 9, pp. 1029-1048, 2009.  [PDF]
• G. Zhang, S. Ferrari, and M. Qian, “Information Roadmap Method for Robotic Sensor Path Planning,” Journal of Intelligent and Robotic Systems, Vol. 56, pp. 69-98, 2009.  [PDF]
• S. Ferrari, R. Fierro, B. Perteet, C. Cai, and K. C. Baumgartner, “A Geometric Optimization Approach to Detecting and Intercepting Dynamic Targets Using a Mobile Sensor Network,” SIAM Journal on Control and Optimization, Vol. 48, No. 1, pp. 292-320, 2009.  [PDF]
• C. Cai and S. Ferrari, “Information-Driven Sensor Path Planning by Approximate Cell Decomposition,” IEEE Transactions on Systems, Man, and Cybernetics - Part B, Vol. 39, No. 3, pp. 672-689, June 2009.  [PDF]
• S. Ferrari and C. Cai, “Information-Driven Search Strategies in the Board Game of CLUE®,” IEEE Transactions on Systems, Man, and Cybernetics - Part B, Vol. 39, No. 3, pp. 607-625, June 2009.  [PDF]
• S. Ferrari, “Multi-Objective Algebraic Synthesis of Neural Control Systems by Implicit Model Following,” IEEE Transactions on Neural Networks, Vol. 20, No. 3, pp. 406-419, March 2009.  [PDF]
• Baumgartner, K. C., Ferrari, S., and Palermo, G., “Constructing Bayesian Networks for Criminal Profiling from Limited Data,” Knowledge-Based Systems, Vol. 21, No. 7, pp. 563-572, October 2008.  [PDF]
• Ferrari S., Steck J. E, and Chandramohan R., “Adaptive Feedback Control by Constrained Approximate Dynamic Programming,” IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, Vol. 38, No. 4, pp. 982-987, August 2008.  [PDF]
• Baumgartner, K. C., and Ferrari, S., “A Geometric Approach to Analyzing Track Coverage in Sensor Networks”, IEEE Transactions on Computer, Vol. 57, No. 8, pp. 1113-1128, August 2008.  [PDF]
• Ferrari, S., Baumgartner, K. C., Palermo, G., Bruzzone, R., Strano, M., “Network Models of Criminal Behavior: Comparing Bayesian and Neural Networks for Decision Support in Criminal Investigations” IEEE Control Systems Magazine, Vol. 28, No. 4, pp. 65-77, August 2008.  [PDF]
• S. Ferrari and M. Jensenius, “A Constrained Optimization Approach to Preserving Prior Knowledge During Incremental Training,” IEEE Transactions on Neural Networks, Vol. 19, No. 6, June 2008.  [PDF]
• Ferrari, S., Vaghi, A. “Demining Sensor Modeling and Feature-level Fusion by Bayesian Networks,” IEEE Sensors Journal, Vol. 6, No. 2, pp. 471-483, April 2006.  [PDF]
• Ferrari, S., Stengel, R. F. “Smooth Function Approximation by Neural Networks,” IEEE Transactions on Neural Networks, Vol. 16, No.1, pp. 24-38, January 2005.  [PDF]
• Ferrari, S., Stengel, R. F. “On-line Adaptive Critic Flight Control,” Journal of Guidance, Control, and Dynamics, Vol. 27, No. 5, pp. 777-786, Sept-Oct 2004.  [PDF]
• Ferrari, S., Stengel, R. F. “Classical/Neural Synthesis of Nonlinear Control Systems,” Journal of Guidance, Control, and Dynamics, Vol. 25, No. 3, pp. 442-448, May-June 2002.  [PDF]

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Book Chapters

• Ferrari, S., Stengel, R. F. “Model-based Adaptive Critic Designs,” Learning and Approximate Dynamic Programming, J. Si, A. Barto, W. Powell, Eds., John Wiley & Sons, 2004.  [PDF]
• Crispin, Y., Ferrari, S. “Adaptive Control of Chaos Induced Capsizing of a Ship,” in Intelligent Engineering Systems through Artificial Neural Networks, Vol. 5, Fuzzy Logic and Evolutionary Progr., C.H. Dagli et. al, Eols, ASME Press, NY, 1995.

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MORE PUBLICATIONS
Peer-Reviewed Conference Proceedings

• S. Ferrari and G. Daugherty, “A Q-Learning Approach to Automated Unmanned Air Vehicle (UAV) Demining,” Proc. IEEE Conference on Robotics and Automation, Anchorage, Alaska, 2010, submitted.
• S. Ferrari, G. Foderaro, and A. Tremblay “A Probability Density Function Approach to Distributed Sensors Path Planning,” Proc. IEEE Conference on Robotics and Automation, Anchorage, Alaska, 2010, submitted.
• S. Ferrari and G. Foderaro, “A Potential Field Approach to Finding Minimum-Exposure Paths in Wireless Sensor Networks,” Proc. IEEE Conference on Robotics and Automation, Anchorage, Alaska, 2010, submitted.
• S. Ferrari, R. Fierro, and D. Tolic, “A Geometric Optimization Approach to Tracking Maneuvering Using a Heterogeneous Mobile Sensor Network,” Proc. IEEE Conference on Decision and Control, Shanghai, China, December 2009.  [PDF]
• G. Zhang and S. Ferrari, “An Adaptive Artificial Potential Function Approach for Geometric Sensing,” Proc. IEEE Conference on Decision and Control, Shanghai, China, December 2009.  [PDF]
• G. Di Muro and S. Ferrari, “A Constrained Backpropagation Approach to Solving Partial Differential Equations in Nonstationary Environments,” Proc. International Joint Conference on Neural Networks, Atlanta, GA, 2009.  [PDF]
• G. Di Muro and S. Ferrari, “Penalty Function Method for Exploratory Adaptive-Critic Neural Network Control,” Proc. Mediterranean Conference on Control and Automation (MED’09), Thessaloniki, Greece, January 2009, pp. 1410-1414.  [PDF]
• D. Tolic, R. Fierro, and S. Ferrari, “Cooperative multi-target tracking via hybrid modeling and geometric optimization,” Proc. Mediterranean Conference on Control and Automation (MED’09), Thessaloniki, Greece, January 2009, pp. 440-445.  [PDF]
• Fierro, R., Ferrari, S., and Cai, C., “An Information-Driven Framework for Motion Planning in Robotic Sensor Networks: Complexity and Experiments,” Proc. IEEE Conference for Decision and Control, Cancun, MX, 2008, pp. 483-489.  [PDF]
• Cai, C., and Ferrari, S., “A Q-Learning Approach to Developing an Automated Computer Player for the Board Game of CLUE®,” Proc. International Joint Conference on Neural Networks, Hong Kong, 2008, pp. 2347-2353.  [PDF]
• Di Muro, G. and Ferrari, S., “A Constrained-Optimization Approach to Training Neural Networks for Smooth Function Approximation and System Identification,” Proc. International Joint Conference on Neural Networks, Hong Kong, 2008, pp. 2354-2360.  [PDF]
• S. Ferrari, B. Mehta, G. Di Muro, A. M.J. VanDongen, and C. Henriquez, “Biologically Realizable Reward-Modulated Hebbian Training for Spiking Neural Networks,” Proc. International Joint Conference on Neural Networks, Hong Kong, 2008, pp. 1781-1787.  [PDF]
• Cai, C., and Ferrari, S., “Bayesian Network Modeling of Acoustic Sensor Measurements” Proc. IEEE Sensors Conference, Atlanta, GA, 2007, pp. 345-348.  [PDF]
• Ferrari, S., Cai, C., Fierro, R., and Perteet, B., “A Multi-Objective Optimization Approach to Detecting and Tracking Dynamic Targets in Pursuit-Evasion Games,” Proc. American Control Conference, New York, NY, 2007, pp. 5316-5321.  [PDF]
• Baumgartner, K. C., and Ferrari, S., “Optimal Placement of a Moving Sensor Network for Track Coverage,” Proc. American Control Conference, New York, NY, 2007, pp. 4040-4046.  [PDF]
• Cai, C., and Ferrari, S., “Comparison of Information-Theoretic Functions for Decision Support in Sensor Fusion and Classification,” American Control Conference, New York, NY, 2007, pp. 63-133.  [PDF]
• R. Chandramohan, J. Steck, and S. Ferrari, “On the Development of an Adaptive Critic Reconfigurable Flight Controller,” Infotech@Aerospace, April 2007.
• Cai, C., and Ferrari, S., “On the Development of an Intelligent Computer Player for CLUE®: A Case Study in Preposterior Decision Analysis,” Proc. American Control Conference, Minneapolis, MN, 2006, pp. 4350- 4355.  [PDF]
• Ferrari, S., “Track Coverage in Sensor Networks,” Proc. American Control Conference, Minneapolis, MN, 2006, pp. 2053-2059.  [PDF]
• Ferrari, S., Jensenius, M. “Robust and Reconfigurable Flight Control by Neural Networks,” AIAA 2005-7037, Infotech@Aerospace, Arlington, VA, September 2005.  [PDF]
• Crews B. K., Ferrari, S., Salfati, C. G. “Bayesian Network Modeling of Offender Behavior for Criminal Profiling, “ Proc. IEEE Conference for Decision and Control, Seville, Spain, 2005, pp. 2702-2709.  [PDF]
• Qian, M., Ferrari, S. “Control of Distributed Sensors by Dynamic Bayesian Networks,” Proc. SPIE Symposium on Smart Structures and Materials, San Diego, CA, 2005, pp. 85-96.
• Vaghi, A., Ferrari, S. “Sensor Network Management by a Graphical Model Approach,” Proc. European Conference on Structural Control, Vienna, Austria, July 2004.
• Ferrari, S., Stengel, R. F. “An Adaptive Critic Global Controller,” Proc. American Control Conference, Anchorage, AK, 2002, pp. 2665- 2670.  [PDF]
• Ferrari, S., Stengel, R. F. “Algebraic Training of a Neural Network,” Proc. American Control Conference, Arlington, VA, 2001, pp. 1605-1610.  [PDF]
• Ferrari, S., Stengel, R. F. “Classical/Neural Synthesis of Nonlinear Control Systems,” Proc. AIAA Guidance, Navigation, and Control Conference, Denver, CO, August 2000.
• Crispin, Y., Ferrari, S. “Model-Reference Adaptive Control of Chaos in Periodically Forced Dynamical Systems,” Proc. AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Bellevue, WA, September 1996.

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Theses

• Kelli C. Baumgartner, Control and Optimization of Track Coverage in Underwater Sensor Networks, Ph.D. Thesis, Duke University, 2007.
• Kelli C. Baumgartner, Bayesian Network Modeling of Offender Behavior for Criminal Profiling, M.S. Thesis, Duke University, 2005.
• Mark A. Jensenius, Constrained Learning in Neural Control Systems, M.S. Thesis, Duke University, 2005.
• Alberto Vaghi, Sensor Management by Graphical Model Approach, Politecnico Di Milano, 2004.
• Silvia Ferrari, Algebraic and Adaptive Learning in Neural Control Systems, Ph.D. Thesis, Princeton University, 2002

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