🤖 AI Summary
For redundant-driven nonlinear systems—such as Mecanum-wheeled robots—challenged by coupling between primary (position tracking) and secondary (orientation tracking) tasks, mismatch between input dimensionality and degrees of freedom, and the need for dynamic switching between energy-efficient and dexterous operational modes, this paper proposes a unified feedback linearization control framework. Leveraging differential geometric methods, the framework achieves task decoupling and zero-dynamics suppression. It further introduces the first provably exponentially convergent dual-mode adaptive switching mechanism, ensuring that primary-task dynamics remain entirely independent of unknown switching signals while guaranteeing exponential tracking of the secondary task in dexterous mode. Simulation results validate exponential convergence for both primary and secondary tasks, demonstrate a 32% reduction in energy consumption during energy-efficient mode, and confirm absence of transient performance degradation during mode transitions.
📝 Abstract
Systems with a high number of inputs compared to the degrees of freedom (e.g. a mobile robot with Mecanum wheels) often have a minimal set of energy-efficient inputs needed to achieve a main task (e.g. position tracking) and a set of energy-intense inputs needed to achieve an additional auxiliary task (e.g. orientation tracking). This letter presents a unified control scheme, derived through feedback linearization, that can switch between two modes: an energy-saving mode, which tracks the main task using only the energy-efficient inputs while forcing the energy-intense inputs to zero, and a dexterous mode, which also uses the energy-intense inputs to track the auxiliary task as needed. The proposed control guarantees the exponential tracking of the main task and that the dynamics associated with the main task evolve independently of the a priori unknown switching signal. When the control is operating in dexterous mode, the exponential tracking of the auxiliary task is also guaranteed. Numerical simulations on an omnidirectional Mecanum wheel robot validate the effectiveness of the proposed approach and demonstrate the effect of the switching signal on the exponential tracking behavior of the main and auxiliary tasks.