This chapter studies the decentralized robot arm cooperation problem with a star control topology. The problem is formulated as a constrained quadratic program and then a recurrent neural network with independent modules is presented to solve the problem in a distributed manner. Each module in the neural network controls a single manipulator in real time without explicit communication with others and all the modules together collectively solve the common task. The global stability of the presented neural network and the optimality of the neural solution are proven in theory. Application orientated simulations demonstrate the effectiveness of the method.