Design of the adaptive constraint following control for some uncertain joint modules applied to the medical robotic...

High-precision control of integrated joint modules is critical for medical robots, which demand extreme accuracy and stability. However, robustness is often compromised by rapidly time-varying uncertainties, including nonlinear friction, unmodeled parameters, electronic noise, and external disturbances, which collectively induce complex nonlinear dynamical behaviors. To address this challenge, a constrained second-order dynamical system based on angular constraints is first constructed. The Udwadia-Kalaba theory is then introduced to enforce desired constraints in deterministic systems. Furthermore, a novel recursive adaptive robust control method is proposed, explicitly incorporating multi-type uncertainties and nonlinear friction dynamics with discontinuous characteristics. Key advantages include eliminating the need for precise uncertainty boundaries and guaranteeing asymptotic error convergence via a recursive adaptive design. This ensures strict enforcement of system constraints despite nonlinearities. Simulations and experiments on a physical joint module and a real-time simulation control system high-speed controller prototype demonstrate significant reductions in tracking error and enhanced reliability under diverse uncertainties. The proposed method is validated in a joint module of medical robots, providing a generalizable framework to tackle nonlinear control problems.