In this chapter we present three nonlinear $${\mathcal{H}}_{\infty}$$ control techniques for underactuated cooperative manipulators. Two are based on a quasi-linear parameter varying (quasi-LPV) representation of the nonlinear system with solutions based on game theory. These controllers take into account a fundamental characteristic of cooperative manipulator control, namely, that squeeze force control is designed independently of position control. In these cases, only the position control problem is reflected in the $${\mathcal{H}}_{\infty}$$ performance index. The third controller uses a neural network-based adaptive control law to estimate the parametric uncertainties of the system. In this case, the $${\mathcal{H}}_{\infty}$$ performance index includes both the position and squeeze force errors of the cooperative manipulators.