Despite the theoretical advances in optimal control, satellite attitude control is still predominantly performed by standard controllers, such as PD laws, which are easier to implement. A switched controller is proposed, based on inverse optimal control theory, which circumvents the complex task of numerically solving online the Hamilton Jacobi Bellman (HJB) partial differential equation of the global nonlinear optimal control problem. The inverse optimization problem consists of minimizing the norm of the control torque subject to a constraint on the convergence rate of a parameterized Lyapunov function, under the effect of the benchmark controller, which is chosen to be a PD law without loss of generality. The controller is then modified by gain scheduling to achieve a tradeoff enhancement compared to the benchmark controller, while maintaining torque saturation limits. The extent to which performance can be enhanced is shown to be dependent on the controller parameters. A controller tuning analysis shows how a design settling time limit can be achieved, within the problem's constraints on the maximum torque and the total integrated torque. The proposed optimization approach is globally stabilizing and presents low implementation complexity, which is highly desirable given the limited resources onboard satellites.