Virtual decomposition control is a new non-linear model-based (that is, based on the kinematics and dynamics of rigid bodies) control approach for controlling multiple degrees of freedom robots. It has been successfully applied to control several different hydraulic robots. On the other hand, hydraulic rotary actuators are types of actuator used when high power-to-size ratio and compact space utilization are required. They come in different types; the helical spline type often introduces backlash nonlinearity into control systems because of gear the transmission involved. Therefore, in order to achieve good reference tracking performance and guaranteed stability of systems in which they are applied, their backlash has to be somewhat accounted for by incorporating backlash compensation into their main controller structure. Thus, the essence of this research was to design a virtual decomposition controller with the capability to reduce or eliminate the effect of backlash in an application where helical type hydraulic rotary actuators is applied and compare the system performance with that obtained by applying the traditional Proportional- Integral- Differential controller. A general overview of robot control is presented, followed by the definition of basic terms related to virtual decomposition control. Thereafter, hydraulic rotary actuator is described, focusing on the helical gear type. Finally, backlash and its inverse are presented in graphical and mathematical forms to show their characteristics. A combination of the aforementioned concepts was used in the development and implementation of effective control approach for a manipulator actuated by a hydraulic rotary actuator. Based on recently proposed normalizing performance indicator μ, comparison of the three different controller algorithms presented were made. The results obtained indicated that the designed nonlinear model based controller, without and with backlash compensation significantly outperformed the classical Proportional-Integral-Derivative controller. However, the experimental results show that much work still need to be done in the future to implement parameter adaptation algorithm portion of the control equations.