Applied Design of Optimal PID-with-Feedforward Control Using Two-Parameter Behavior Models

This paper proposes a two-parameter method for adjusting and tuning control systems in order to explore trade-offs in light of real-world objectives and constraints; the user-friendly mechanism draws parallels between robot and human behavior easily understood at an intuitive level. Firstly, the general behavior model enables a designer to adjust weightings in a cost function using two behavior traits, potentially to create 3D plots that illustrate trade-offs. Secondly, the specific behavior model allows someone to explore trade-offs or tune the control gains in real time, for a specific situation or for personal preference, again using only two intuitive behavior traits. Both methods also facilitate a simple strategy of just choosing between a few distinctive behavior types. Moreover, the framework provides a possible model for understanding how some behavior qualities might arise due to the natural constraint of feedback in systems, with implications for programming relatable behaviors into robots. A nonlinear optimal quadratic tracking design for the PID-with-feedforward control of a robot link demonstrates the practical design methodology.