Human-Simulating Intelligent PID Control

Towards intelligent PID control

Event driven intelligent PID controllers with applications to motion control

A novel type of reduced complexity controller is proposed. It is the combination of model free control and event triggered control. The robustness of model free control, especially for badly known dynamics, is added to the event based scheme. The performances of the proposed method are illustrated in two motion controls, vehicular longitudinal control and quadrotor control. Comparisons with exi...

Robust intelligent tracking control with PID-type learning algorithm

This paper proposes a robust intelligent tracking controller (RITC) for a class of unknown nonlinear systems. The proposed RITC system is comprised of a neural controller and a robust controller. The neural controller is designed to approximate an ideal controller using a proportional–integral–derivative (PID)-type learning algorithm in the sense of Lyapunov function, and the robust controller ...

Modeling and Simulating Human Teamwork Behaviors Using Intelligent Agents

Among researchers in multi-agent systems there has been growing interest in using intelligent agents to model and simulate human teamwork behaviors. Teamwork modeling is important for training humans in gaining collaborative skills, for supporting humans in making critical decisions by proactively gathering, fusing, and sharing information, and for building coherent teams with both humans and a...

Model-free control and intelligent PID controllers: towards a possible trivialization of nonlinear control?

We are introducing a model-free control and a control with a restricted model for finite-dimensional complex systems. This control design may be viewed as a contribution to"intelligent"PID controllers, the tuning of which becomes quite straightforward, even with highly nonlinear and/or time-varying systems. Our main tool is a newly developed numerical differentiation. Differential algebra provi...