Inverse optimal H∞ disturbance attenuation for planar manipulators with the eye-in-hand system

Deals with an inverse optimal H_∞ disturbance attenuation for planar manipulators with an eye-in-hand system. The input-to-state stability control Lyapunov function (ISS-CLF) is constructed the full Lagrangian dynamics based on a potential function of the image feature parameter space. The ISS-CLF gives us an inverse optimal H_∞ control law. A proposed controller solves the inverse optimal H_∞ control problem by minimizing a cost functional, and the closed-loop system with the proposed controller is input-to-state stable. Further, we discuss that the inverse optimal H _∞ controller has robustness against input uncertainties