Richard W. Longman, professor; Ph.D., University of California, San Diego, 1969. He specializes in dynamics and control including learning, repetitive, and optimal control theory and applications. Other areas of interest include system identification, robotics in space, and satellite altitude and shape control.
R. W. Longman, “Learning from Theory, Simulations, and Experiments: A Case Study from Iterative Learning Control,” Encyclopedia of the Sciences of Learning, N. M. Seel, Editor, 7 Volumes, 4300 pages, Springer Publications (2012)
R. W. Longman, “On the Theory and Design of Linear Repetitive Control Systems,” European Journal of Control, 16(5), 447-496 (2010)
R. W. Longman, “Iterative Learning Control: A Method that can Improve Product Quality and Productivity in Manufacturing,” Journal of the Chinese Institute of Engineers, Special Issue on Manufacturing and Engineering Systems (Keynote Address), 35(1), 3-15 (Jan 2012)
R.W. Longman, J.-N. Juang, M.Q. Phan, and K.Xu, “On Multi-Input Multi-Output Repetitive Control Design Methods,” Journal of The Chinese Society of Mechanical Engineers, Special Issue in Honor of Han Min Hsia, 32(6), 477-492 (2011)
R.W. Longman, Y.-T. Peng, T. Kwon, H. Lus, R. Betti, and J.-N. Juang, “Adaptive Inverse Iterative Learning Control,” Journal of The Chinese Society of Mechanical Engineers, Special Issue in Honor of Han Min Hsia, 32(6), 493-506 (2011)