This paper deals with the use of artificial neural networks employed as an on-line trained controller for a real process and simulation model control. Well-known back-propagation method is used as a learning algorithm intended to minimize the difference between the plant’s actual response and the desired reference signal. The influence of neural network’s parameters on a controlled plant output...

Compliance is a strong requirement for human–robot interactions. Soft-robots provide an opportunity to cover the lack of compliance in conventional actuation mechanisms, however, control them very challenging given their intrinsic complex motions. Therefore, soft-robots require new approaches e.g., modeling, control, dynamics, and planning. One strategies that ensures impedance control. During ...

We present a reactive controller that is able to displace a legged robot along an arbitrary trajectory with a high degree of accuracy. We designed the different modules of our controller so that they can deal with arbitrary leg configurations. In this way, any leg movement necessary to overcome unexpected terrain irregularities can be correctly compensated by the controller, while still followi...

| This autonomous biped walking control system is based on the reactive force interaction at the foothold. The precise 3D (three dimensional) dynamic simulation presented includes: 1) a posture controller which accommodate the physical constraints of the reactive force/torque on the foot by quadratic programming. 2) a real-time COM (center of mass) tracking controller for foot placement, with a...