Design and simulation of adaptive PID control for DC motors based on adaptive boosting

The application fields of proportional-integral-derivative (PID) are very extensive, such as automation, aerospace, autonomous driving, and other fields. More specifically, it can be applied to tasks such as temperature, pressure, tension, precision positioning, etc. However, PID parameter adjustment has always been an important and troublesome task. There are many directions and methods for the self-tuning research of PID parameters, and there are many different algorithms based on different scenarios. Among them, there are relatively few PID controls using the Adaptive Boosting algorithm (AdaBoost), and although there are similarities between various algorithms, each algorithm still has a unique advantage interval. Compared to other algorithms, such as mainstream fuzzy gain algorithms, the AdaBoost algorithm has strong adaptive ability, simple implementation, and a wide range of applications. Therefore, this article designs an AdaBoost algorithm logic and applies it to PID control, with DC motors as the target object for research. By designing a PID control for DC motors that can reasonably self-tuning parameters, the application and influence of the AdaBoost algorithm in PID control are studied. In short, this study designed the potential of the AdaBoost algorithm to improve the performance and adaptability of PID controllers in various industrial applications. With these advanced optimization technologies, more intelligent and autonomous control systems can be developed to meet the requirements of modern engineering challenges.