Mathematical optimization is one of the cornerstones of modern engineering research and
practice. Yet, throughout all application domains, mathematical optimization is, for the most …

Extremum seeking is a form of adaptive control where the steady-state input-output
characteristic is optimized, without requiring any explicit knowledge about this input-output …

We introduce a non-model based approach for locally stable convergence to Nash equilibria
in static, noncooperative games with N players. In classical game theory algorithms, each …

We present a Newton-based extremum seeking algorithm for the multivariable case. The
design extends the recent Newton-based extremum seeking algorithms for the scalar case …

Traditional automated vehicle path-tracking algorithms require plant models to derive the
respective control laws. However, the accurate vehicle model is difficult to obtain due to the …

Stochastic Averaging and Extremum Seeking treats methods inspired by attempts to
understand the seemingly non-mathematical question of bacterial chemotaxis and their …

Distributed power electronic reactive power sources-such as smart PV inverters-may play an
important role in regulating customer voltages and reducing system losses in future …

We survey some of the rich history of control over the past century with a focus on the major
milestones in adaptive systems. We review classic methods and examples in adaptive linear …

We present a non-model based approach for asymptotic, locally exponentially stable
attainment of the optimal open-loop control sequence for unknown, discrete-time linear …

This book presents analytical and experimental methods and achievements in design,
modeling and control of automotive propulsion systems. The text presents a systems view on …