A novel predictor based optimal integral sliding-mode-based attitude tracking control of spacecraft under actuator's uncertainties and constraints

This work introduces a novel predictor-based integral sliding mode control scheme, designed for spacecraft attitude control. By leveraging Taylor series expansion, we develop predictor dynamics for the sliding surface and its integral, along with the corresponding reaching laws. Subsequently, we formulate a constrained quadratic optimization problem to derive the optimal control input. A notable aspect of the proposed method is the integration of the sliding surface's integral into the control design, which significantly enhances robustness. Additionally, the proposed approach ensures optimality, fault tolerance capability, fixed-time convergence, computational efficiency, and effective constraint management. In this work, we perform a closed-loop stability analysis to confirm system stability in the presence of external perturbations, and constraints. Comparison results with existing method demonstrate that the proposed approach enhances performance while maintaining satisfactory precision. To validate the practical applicability of our algorithm, we conduct hardware-in-the-loop simulations, demonstrating the proposed method's seamless integration with real-world hardware.