Biological nervous systems usually perform the con-trol of numerous degrees of freedom limbs in insects and mam-mals. Neuromorphic engineers study these systems by emulatingthem for a deeper understanding and its possible application tosolve complex problems in engineering, such as robotics. Central-Pattern-Generator (CPG) is part of the neuro-controllers at theirlast steps to produce rhythmic patterns for limbs movement.Different patterns and gaits typically compete through winner-take-all (WTA) circuits to produce the right movements. Inthis work, a WTA circuit has been implemented in a Spiking-Neural-Network (SNN) processor to produce such patterns forcontrolling a robotic arm in real-time. The robot uses spike-basedproportional-integrative-derivative (SPID) controllers to keep acommanded joint position from the winner population of neuronsof the WTA circuit. Experiments demonstrate the feasibility ofthe system.