Bücher von Derong Liu

It is with great pleasure that I offer my reflections on Professor Anthony N. Michel's retirement from the University of Notre Dame. I have known Tony since 1984 when he joined the University of Notre Dame's faculty as Chair of the Depart- ment of Electrical Engineering. Tony has had a long and outstanding career. As a researcher, he has made im- portant contributions in several areas of systems theory and control theory, espe- cially stability analysis of large-scale dynamical systems. The numerous awards he received from the professional societies, particularly the Institute of Electrical and Electronics Engineers (IEEE), are a testament to his accomplishments in research. He received the IEEE Control Systems Society's Best Transactions Paper Award (1978), and the IEEE Circuits and Systems Society's Guillemin-Cauer Prize Paper Award (1984) and Myril B. Reed Outstanding Paper Award (1993), among others. In addition, he was a Fulbright Scholar (1992) and received the Alexander von Hum- boldt Forschungspreis (Alexander von Humboldt Research Award for Senior U.S. Scientists) from the German government (1997). To date, he has written eight books and published over 150 archival journal papers. Tony is also an effective administrator who inspires high academic standards.

Among continuous-time systems, the control of affine and nonaffine nonlinear systems is studied using the ADP approach which is then extended to other branches of control theory including decentralized control, robust and guaranteed cost control, and game theory.

Stability of Dynamical Systems

Procedures and results are determined which constitute the first successful synthesis procedure for associative memories by means of artificial neural networks with arbitrarily pre-specified full or partial interconnecting structure and with or without symmetry constraints for the connection matrix.

This book approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). It shows readers how to derive necessary stability and convergence criteria for their own systems.

Fuzzy logic methodology has proven effective in dealing with complex nonlinear systems containing uncertainties that are otherwise difficult to model.

This text offers a wide selection of techniques aimed at achieving three goals: the suppression, the synchronization, and the generation of chaos. It includes introductory material reviewing the history of chaos control and key mathematical preliminaries.