Stiffness and Compliance Control in Dynamical Systems Driven by Muscle-Like Actuators

This work reports on the design and the feed forward stiffness control of bioinspired kinematic chains from a static and a dynamic point of view. While position control is clearly referred to common geometrical lagrangian coordinates for the considered system, in order to deal with the stiffness or compliance of the chain, especially in dynamic cases, global and less intuitive variables have to be defined and used. The advantage deriving from a similar control strategy can be important when the chain is part of a complex dynamic system or the computational resources are scarce. By defining and controlling stiffness or compliance for a certain position or trajectory, we can state that, even if the system is not continuously monitored in closed loop, a bounded perturbation cannot produce equilibrium point or trajectory variations greater than a fixed quantity. In a closed loop control strategy, the described methodology can be implemented during the time between two consecutive output sampling and feedback inputs. On the other hand, compliance control permits a kinematic chain to interact with objects without causing damages even if errors in position occur. In this work, the compliance and stiffness concepts, inspired to common reasoning in biological motor control theory, are generalized to a dynamic case and endowed with a mathematical architecture.