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In this chapter, we demonstrate how to use a nonlinear polyhedral con- strained optimization solver called the Polyhedral Active Set Algorithm (PASA) for solving a general singular control problem. We present a method for discretizing a general optimal control problem involving the use of the gradient of the Lagrangian for computing the gradient of the cost functional so that PASA can be applied. When a numerical solu- tion contains artifacts that resemble “chattering,” a phenomenon where the control oscillates wildly along the singular region, we recommend a method of regularizing the singular control problem by adding a term to the cost functional that measures a scalar multiple of the total variation of the control, where the scalar is viewed as a tuning parameter. We then demonstrate PASA’s performance on three singular control problems that give rise to different applications of mathematical biology. We also provide some exposition on the heuristics that we use in determining an appropriate size for the tuning parameter.