Table online neural control of systems with closed kinematic chains

The neural control of robotic systems with closed kinematic chains is discussed and theorems guaranteeing the control stability of such systems are developed. The first class of systems have a single serial chain with a prescribed contact force when moving across a surface, i.e. the problem of hybrid position/force neural control. The second class of systems considered includes hexapod walking machines, which have a varying topology of closed kinematic chains during walking. The equations of motion can be solved by optimising contact forces according to a predefined cost function, and so the hybrid/position neural controller is extended to this class. A novel control structure which makes no initial assumptions about the system is also presented, using the concept of `virtual neural networks´. This approach can be applied to a large number of different systems, and it is also extended to include neural networks implemented on digital microprocessors