Extremum Seeking Control: Convergence Analysis

This paper summarizes our recent work on dynamical properties for a class of extremum seeking (ES) controllers that have attracted a great deal of research attention in the past decade. Their local stability properties were already investigated in [2]. We first show that semi-global practical convergence is possible if the controller parameters are carefully tuned and the objective function has a unique (global) extremum. An interesting tradeoff between the convergence rate and the size of the domain of attraction of the scheme is uncovered: the larger the domain of attraction, the slower the convergence of the algorithm. The amplitude, frequency and shape of the dither signal are important design parameters in the ES controller. In particular, we show that changing the amplitude of the dither adaptively can be used to deal with global ES in presence of local extrema. Moreover, we show that the convergence of the algorithm is proportional to the power of the dither signal. Consequently, the squarewave dither yields the fastest convergence among all dithers of the same frequency and amplitude. We consider ES of a class of bioprocesses to demonstrate our results and motivate some open research questions for multi-valued objective functions.