Nonlinear and adaptive control

The primary thrust of the research was to conduct fundamental research in the theories and methodologies for designing complex high-performance multivariable feedback control systems; and to conduct feasibiltiy studies in application areas of interest to NASA sponsors that point out advantages and shortcomings of available control system design methodologies

Broadcasting protocols for coordinating nonlinear network systems

We propose a new methodology to design broadcasting protocols for coordinating nonlinear network systems. Our design of the scheduling of information transmission is based on the introduction of clock variables, whose dynamics are regulated through a suitable storage function. Required clock dynamics, ensuring stability, follow then elegantly from Lyapunov like arguments. For illustrative purposes, we first consider an example of a consensus algorithm, whereafter we discuss a distributed integral controller in feedback interconnection to a network composed of output strictly incrementally passive subsystems. Finally, we show how the proposed method can be used to redesign a popular distributed controller in power grids, enabling a sampled-data implementation

Robotic Unicycle Intelligent Robust Control Pt I: Soft Computational Intelligence Toolkit

The concept of an intelligent control system for a complex nonlinear biomechanical system of an extension cableless robotic unicycle discussed. A thermodynamic approach to study optimal control processes in complex nonlinear dynamic systems applied. The results of stochastic simulation of a fuzzy intelligent control system for various types of external / internal excitations for a dynamic, globally unstable control object - extension cableless robotic unicycle based on Soft Computing (Computational Intelligence Toolkit - SCOptKBTM) technology presented. A new approach to design an intelligent control system based on the principle of the minimum entropy production (minimum of useful resource losses) determination in the movement of the control object and the control system is developed. This determination as a fitness function in the genetic algorithm is used to achieve robust control of a robotic unicycle. An algorithm for entropy production computing and representation of their relationship with the Lyapunov function (a measure of stochastic robust stability) described