Fuzzy logic is the weaker choice. It would make the robot no longer working. The better idea is to stay within the classical pid control paradigm which is based on mathematics and is teached in universities. Fuzzy logic was only a period in AI history which was restricted to japan in the 1990s and then it was forgotten, because the engineers have recognized that they need a different kind of controller in their robots.
For a classical pid controlled line follower, the current situation is compared with the desired state. This is done by calculating the error value. The algorithm has to minimize the error value which is equal to move the robot closer to the line. This can be done with policy iteration which is a heuristic search technique in the state space. Another option is a neural network which can learn the policy with trial and error. That means the distance to the line is used as the error value, and the weights of the neural networks have to adjust to provide better control signals. This kind of neural network pid control is state of the art in robotics and will result into good results in professional robotics competitions.