Convergent nonlinear control for uncertain process plants

This paper investigates the design of nonlinear controllers for process plant applications that could be modeled by relatively low order uncertain dynamics, such as industrial processes (e.g. level, flow, pressure, etc.) and also some automotive applications (e.g. active suspension). The design technique is based on using a combination of state feedback and Lyapunov-based techniques. The key issue in this design is arriving at the best parameter update law that guarantees both stability and performance is studied. A simulated level process and simple robot arm are used to exemplify the technique.