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 (ES) is a powerful approach to the optimization and stabilization of
unknown dynamic systems and is an active field of research in control theory. This paper …

Economic model predictive control (EMPC) is a variant of model predictive control aimed at
maximization of system's profitability. It allows one to explicitly deal with hard and average …

This paper develops a fractional-order sliding mode based extremum seeking controller (FO
SM-ESC) for the optimization of nonlinear systems. The proposed FO SM-ESC, involving an …

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 …

In this paper, an aggregate game is adopted for the modeling and analysis of energy
consumption control in smart grid. Since the electricity users' cost functions depend on the …

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 …

We consider the problem of distributed convergence to a Nash equilibrium in a
noncooperative game where the players generate their actions based only on online …