Disturbance-Compensation-Based Predictive Sliding Mode Control for Aero-Engine Networked Systems With Multiple Uncertainties

This paper investigates the compound control problem of aero-engine networked systems with multiple uncertainties and saturation constraints. To address these challenges, a novel sliding mode controller (SMC) with extended state observer (ESO) is first designed to implement anti-disturbance control, which can alleviate the chattering phenomenon without sacrificing robustness by two parallel ways: adaptive switching term and disturbance compensation. Then, the predictive control strategy is introduced to further optimize the reaching phase, and two disturbance-compensation-based predictive SMC schemes are proposed to coordinate diverse control requirements in the presence and absence of system constraints. When there are no saturation limits, the optimization problem is formulated as a convex one, and its analytic solution is derived explicitly. Furthermore, both state and control limits are considered in the system synthesis, and a standard prediction problem with multiple constraints is established. For high-frequency sampling needs, the Laguerre function is designed to reconstruct the input variables of the prediction sequence, which can effectively reduce the calculation complexity without compromising the dynamic performance. The experiment simulations show that the proposed compound schemes have strong robustness to multiple uncertainties and saturation constraints, and achieve promising control performance in both transient and steady-state phases. Note to Practitioners-As the heart of aircraft, aero-engine system is developing towards networked and intelligent. Subsequently, some new challenges are exposed to be addressed, such as communication delays, saturation constraints, electromagnetic disturbances, etc., which make the existing linear schemes fail to guarantee diverse requirements. Although SMC owns good robustness against multiple uncertainties, most relevant results still face some challenges, such as high switching gain, known disturbance boundary assumption, and sufficient control period. To address these difficulties, we propose two disturbance-compensation-based predictive SMC schemes to coordinate diverse control requirements with and without system constraints. The proposed schemes do not rely on excessive computing resources and are applicable to high-frequency sampling systems. The results of this paper can also provide guidance for the design of robust compound strategies for other networked systems with multiple uncertainties.