Hybrid Kalman-Sliding Mode Control For Accurate Speed Tracking Of DC Motors

The accurate and effective control of a DC motor’s speed is a critical challenge in a wide range of industrial applications. This study suggests a hybrid Kalman-sliding mode control (HK-SMC) that combines the Kalman filter (KF) with SMC for speed tracking of a DC motor. By combining these two control strategies, the motor’s performance is improved in terms of accuracy, durability and disruption avoidance. Speed measurements are prone to be corrupted with measurement noise. The KF is used to calculate the motor’s current speed in the existence of such noisy measurements and disturbances. This KF based estimation offers a trustworthy and accurate speed of the motor. Depending upon the speed measurement that the KF provides, the SMC is intended to adjust the motor’s speed such that it reaches the desired speed. SMC has a built-in resistance to external disruptions and parametric uncertainties. The controller ensures quick and precise tracking of the specified speed benchmark is achieved by actively guiding the system path onto a specified sliding surface. Using a DC motor structure, the suggested hybrid methodology (HK-SMC) is put into practice and put to the test. Results from simulations and experiments show how the KF can accurately estimate speed even when observations are noisy. This estimation is successfully used by the SMC to maintain precise speed monitoring even in an environment of changing loads and disruptions. To demonstrate the suggested controller’s greater performance, comparisons are made with more established control techniques like the PID controller. Overall, the combination of KF with SMC offers a viable method for improving DC motor speed regulation.