The concept of controlling vehicle comfort is a common problem that is faced in most under- and postgraduate courses in Engineering Schools. The aim of this study is to provide a simplified approach for the feedback control design and simulation of active suspension systems, which are applied in vehicles. Firstly, the mathematical model of an active suspension system (a quarter model of a car) which consists of a passive spring, a passive damper and an actuator is provided. In this study, we chose to design and compare the following controllers: (a) conventional P, PI and PID controllers that were tuned through two conventional methodologies (Ziegler−Nichols and Tyreus−Luyben); (b) an optimal PID controller that was tuned with a genetic algorithm (GA) optimization framework in terms of the minimization of certain performance criteria and (c) an internal model controller (IMC) based on the process transfer function. The controllers’ performance was assessed in a series of realistic scenarios that included set-point tracking with and without disturbances. In all cases, the IMC controller and the optimal PID showed superior performance. On the other hand, the P and PI controllers showed a rather insufficient behavior that involved persistent errors, overshoots and eventually, uncomfortable ride oscillations. Clearly, a step-by-step approach such as this, that includes modeling, control design and simulation scenarios can be applied to numerous other engineering examples, which we envisage to lead more students into the area of automatic control.