Multivariable Control of Solar Battery Power by Extremum Seeking with Hessian-driven Gradient Flows

We presented some development results of novel extremum seeking controller based on Nesterov's gradient flows for solar tracking systems that achieves convergence to an arbitrarily small neighborhood of the set of optimizers of the cost function. Our results establish that for arbitrarily large compact sets of initial conditions, and arbitrarily small neighborhoods of the optimizer, the controller can be tuned to guarantee convergence taking into account the influence of the Hessian, as well as with tuning parameters that have a fairly clear physical meaning. Taking into account the influence of the Hessian, considered as a vector field that distorts transient processes in the system, is an urgent task, since allows to increase the speed of transient processes, and due to the endowment of the system with some damping and smoothing properties, also to improve their quality.