Proportional–integral–derivative controllers are applied for solving a wide range of problems in industrial processes. They are preferred over computational techniques because of their implementation simplicity, low cost, and robustness against noise. In this paper, a novel iterative feedback tuning method is proposed using fuzzy logic, where the design parameters proposed by the user are the desired plant overshoot and settling time. In contrast to classical methods, the proposed technique does not require a precise and complex mathematical model for tuning the proportional–integral–derivative controllers through the plant, nor does it need an expert who knows the precise behavior of the system as in methods based on computational techniques. Furthermore, unlike iterative feedback tuning methods that use cost functions and require several experiments to perform the iterations, this proposal uses fuzzy logic to update the controller parameters, which facilitates its implementation in programmable hardware. The proposed method can be easily implemented in software considering three main stages: pre-processing, fuzzy logic system, and post-processing. The simulation and experimental results demonstrate the effectiveness of the proposed method for proportional–integral–derivative controller tuning; moreover, according to the performed comparison, the proposed method provides a trade-off between performance and robustness in comparison with other tuning techniques.