Adaptive feedforward control of processes with parameters uncertainty

This paper investigates the design of robust controllers for such applications that could be modeled by low order dynamics with uncertainties. Lots of control applications fall into this category such as industrial processes (e.g. level, flow, pressure, etc.) and some automotive applications (e.g. active suspension). The design technique is based on using a combination of state feedback and Lyapunov-based techniques. The proposed controller has the advantage of being applicable to both linear and nonlinear models. The key issue in the design is arriving at the best parameter update law that guarantees both stability and satisfactory transient performance. Trade offs between stability and performance are carefully studied. A simulated level process and one degree of freedom robot arm are used to exemplify the suggested technique. Finally a conclusion is submitted with comments regarding real-time compatibility of the proposed controller.