This course covers computational aspects arising in the analysis and design of linear and nonlinear large-scale systems.  Topics include:

• Optimization via analytic and numerical techniques
• Approximation of functions for stability and performance analysis
• Efficient numerical solution for special classes of poorly conditioned ordinary differential equations
• Analysis and design of fault tolerant control and on-line performance monitoring systems
• Analysis under uncertainty and noise
• Model and data reduction via time-scale, chemometric, and decomposition methods
• Fundamentals of Monte Carlo methods, genetic algorithms, and artificial neural networks for parameter estimation and sensitivity analysis
• Application to large-scale mechanical and chemical systems

 

S. Boyd, et al., , SIAM.

ECE 415, Math 383, and Math 384.  CS350, CS358, and CS370 would be helpful.

1 unit.