Based on recent research theme of the convergence and the integration of life sciences and engineering, designing and evaluating the treatment strategies for controlling Human Immunodeficiency Virus (HIV) infection using optimal control is addressed. Higher order optimal control laws arising from comprehensive HIV models result in complex treatment plans that are difficult to be implemented in practice. This paper presents a feasible long term optimal control treatment through the application of Singular Perturbation and Time Scales (SPaTS) methods. A nonlinear HIV model is decoupled into lower order, slow and fast subsystems based on its inherent time scale behavior. Distinct slow and fast Linear Quadratic Regulator (LQR) based optimal control laws are designed and applied in a conventional long term optimal treatment plan. The simulation results manifest the effectiveness of the proposed method.