Randomized trial demonstrates improved motion continuity in actuator networks, suggesting effective control under disturbances.
This study focuses on the development of a sensor-informed motion-continuity control method for shared-return electro-hydraulic actuator networks subject to neighboring-branch disturbances. The objective is to reduce the local velocity fluctuations induced by return-line pressure transients while retaining explicit hydraulic and valve constraints. A control-oriented shared-return disturbance model is established to map neighboring-valve action, T-port replenishment, accumulator buffering, common return-line pressure, net driving pressure difference, and local actuator motion. On this basis, sensor-derived motion and pressure states together with neighboring-action prior information are used to reconstruct the objective of a constrained predictive controller according to the disturbance stage. Soft Actor–Critic is restricted to bounded objective-weight inference, whereas the valve command remains generated by locally linearized receding-horizon optimization; bounded mapping, smoothing update, and soft pressure constraints preserve positive weighting matrices and online quadratic programming solvability. Co-simulation, simulation-based ablation and baseline comparisons, timing evaluation, and scaled dual-branch experiments show that the proposed framework improves motion continuity, reduces disturbance-induced pressure-difference excursions, maintains smoother valve execution, and completes each tested online update within the sampling period. These findings support feasibility-preserving sensor-driven objective reconstruction under the investigated shared-return disturbance scenarios.
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Wu et al. (2026) studied this question.
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