The above image and the following text were generated by AI based on my own ideas and critical perspective, with the AI assisting only in language polishing and structural organisation.

The question of how to understand the gap between control theory and applications is not one that can be answered in just a few sentences.

Historically, major developments in control theory were largely driven by real-world engineering problems. However, as the theoretical system matured, a different kind of activity began to emerge, particularly in academia. In the process of making the theory more complete and general, many researchers started creating problems that are not really motivated by practical needs. In my view, this has gradually widened the gap between theory and applications.

From my own experience as a frequent reviewer, the situation is, in fact, quite severe. A large number of papers do nothing more than simple stacking of existing theories, or parallel extensions of known methods. For example, take method A and method B and put them together, or move from a deterministic system to a fuzzy/delayed/stochastic setting without any new control insight.

Genuinely novel problems or truly original theories are extremely rare. Most of the work I see is essentially reheating old ideas, cleverly repackaged, but without real conceptual progress.

This is not to say that all theory must have immediate application, or that generalization and synthesis are never valuable. The problem is that the academic ecosystem increasingly rewards manufactured problems, problems that exist only because a previous theory existed, not because there is any engineering or scientific need for them. As a result, the gap between control theory and applications is not just a natural byproduct of theoretical depth; it is, to a significant extent, a product of low-quality academic production.

If we are serious about bridging this gap, we need to be honest about what counts as a meaningful contribution. Not every combination of existing ideas is a contribution. Not every parallel extension is a step forward. And not every mathematically elegant problem deserves to be called a control problem.

This is my personal view, formed largely from reviewing many papers over the years. I share it here not to dismiss theory, but to invite a more honest discussion about where the real gap lies, and how we might stop making it wider.