Silvia Ferrari, Paul Ruffin Scarborough Associate Professor of Mechanical Engineering and Materials Science

Silvia Ferrari

Professor Ferrari's research aims at providing intelligent control systems with a higher degree of mathematical structure to guide their application and improve reliability. Decision-making processes are automated based on concepts drawn from control theory and the life sciences. Recent efforts have focused on the development of reconfigurable controllers implementing neural networks with procedural long-term memories. Full-scale simulations show that these controllers are capable of learning from new and unmodeled aircraft dynamics in real time, improving performance and even preventing loss of control in the event of control failures, nonlinear and near-stall dynamics, and parameter variations. New optimal control problems and methods based on computational geometry are being investigated to improve the effectiveness of integrated surveillance systems by networks of autonomous vehicles, such as, underwater gliders and ground robots.

Office Location:  
Office Phone:  (919) 660-5310
Email Address: send me a message

Teaching (Fall 2012):

Education:

PhDPrinceton University, Princeton, NJ2002
MAPrinceton University, Princeton, NJ1999
BSEmbry-Riddle Aeronautical University, Daytona Beach, FL1997
Specialties:

neural networks
Bayesian networks
Controls
Smart Technology
Research Interests:

Approximate dynamic programming
Reconfigurable control of aircraft
On-line learning in neural and Baysian networks
Sensor planning for integrated surveillance systems
Intelligent systems for criminal profiling

Keywords:

Approximate dynamic programming
• Reconfigurable control of aircraft
• On-line learning in neural and Baysian networks
• Sensor planning for integrated surveillance systems
• Intelligent systems for criminal profiling

Current Ph.D. Students  

  • Guoxian Zhang  
  • Gianluca DiMuro  
  • Chenghui Cai  
Representative Publications

  1. C. Cai and S. Ferrari, Information-Driven Sensor Path Planning by Approximate Cell Decomposition, IEEE Transaction on Systems, Man, and Cybernetics - Part B (Submitted, in revision)
  2. S. Ferrari, Multi-Objective Algebraic Synthesis of Neural Control Systems by Implicit Model Following, IEEE Transactions on Neural Networks (Submitted, in press)
  3. 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 (August 2008), pp. 982-987
  4. K. Baumgartner and S. Ferrari, A geometric transversal approach to analyzing track coverage in sensor networks, Ieee Transactions On Computers, vol. 57 no. 8 (August, 2008), pp. 1113 -- 1128, ISSN 0018-9340
  5. Baumgartner, K.C., and Ferrari S., Constructing Bayesian Networks for Criminal Profiling from Limited Data, Knowledge-Based Systems (Accepted, in press) (Available online at: http://dx.doi.org/10.1016/j.knosys.2008.03.019.)
  6. Ferrari, S., and Jensenius M., A Constrained Optimization Approach to Preserving Prior Knowledge During Incremental Training, IEEE Transactions on Neural Networks, vol. 19 no. 6 (June 2008)
  7. Ferrari, Silvia and Vaghi, Alberto, Demining sensor modeling and feature-level fusion by bayesian networks, IEEE Sensors Journal, vol. 6 no. 2 (2006), pp. 471 - 483 [JSEN.2006.870162]  [abs]
  8. Ferrari, Silvia and Stengel, Robert F., Smooth function approximation using neural networks, IEEE Transactions on Neural Networks, vol. 16 no. 1 (2005), pp. 24 - 38 [TNN.2004.836233]  [abs]
  9. S. Ferrari and R. F. Stengel, Online adaptive critic flight control, Journal Of Guidance Control And Dynamics, vol. 27 no. 5 (2004), pp. 777 -- 786, ISSN 0731-5090
  10. Ferrari, Silvia and Stengel, Robert F., Classical/neural synthesis of nonlinear control systems, Journal of Guidance, Control, and Dynamics, vol. 25 no. 3 (2002), pp. 442 - 448  [abs]

Recent Honors and Awards