Mem-adaptive computing — Part I: Theory

In this two-part paper we present an innovative bio-inspired approach to control the lift of a limb of a humanoid robot called Myon from the stable rest state to the unstable upright position. The proposed paradigm outperforms the state-of-the art approach in terms of time- and energy-efficiency, while maintaining a good degree of adaptability to changes to the nominal operating conditions. This Part I paper introduces the theory behind the novel three-phase control strategy, while the companion Part II manuscript derives its circuit implementation, and analyses its performance to validate the theoretic findings. The critical steps in the proposed strategy are the determination of an estimate for the time duration of the first phase, the storage of the result of this computation over the time interval between two consecutive applications of the control action, and the adaptation of this calculation to changes to the nominal operating conditions. All these three tasks may be successfully accomplished by leveraging the computing, memory, and learning capabilities of a single non-volatile memristor.