Due to the low efficiency of internal combustion engine (ICE) and throttling losses of load-sensing (LS) system, conventional excavators which employed ICE with LS system as power source have high energy waste. To avoid this problem, a distributed independent electro-hydraulic actuator (iEHA) that directly driven by a electric motor is designed for excavators. And a speed control strategy based on mode switching and pump map is proposed. The results of proposed control strategy are carried out to verify the velocity stability. Besides, different signal delays for switching valve are explored to obtain better control characteristics. Furthermore, the influence of different precharged pressure of accumulator is explored when boom and arm share an accumulator. Results demonstrate that the energy efficiency of iEHA system improves from 19.19% to 59.56% compared to load-sensing system, the comprehensive response performance is better when signal delay time is 0.1s and response speed of system increases by 16.6% compared to no delay, the system can achieve good results when the precharged pressure is set to 20 bar.

Distributed independent pump-controlled systems enhance excavator energy efficiency by reducing throttling losses, but sustained high-load and high-speed operation often forces a single pump into low-efficiency regions. To overcome this limitation, this study proposes a dual-pump load-sharing architecture that enables load sharing and dynamic cooperative operation of two pumps within the high-efficiency region. An adaptive closed-loop GOA-SQP optimization strategy is also developed for real-time pump speed distribution. The proposed strategy combines the global exploration capability of the Grasshopper Optimization Algorithm (GOA) with the rapid local convergence characteristics of Sequential Quadratic Programming (SQP). Unlike conventional serial hybrid optimization methods, a bidirectional efficiency-feedback mechanism is introduced to dynamically coordinate global exploration and local refinement processes in real time. Furthermore, a local perturbation and re-explosion mechanism is incorporated to suppress premature convergence, enhance population diversity, and reduce redundant iterations. Experimental validation on an excavator test platform under four-quadrant conditions shows that the proposed system improves mechanical, volumetric, and overall pump efficiencies by 14.22, 4.57, and 18.79 percentage points, respectively, and reduces total energy consumption by 8.83%. Compared with GOA, SQP, GA-SQP, and PSO-SQP, the proposed GOA-SQP algorithm reduces solution time by 39.15% and improves optimization accuracy by 0.5%. The proposed architecture and optimization strategy offer a novel and effective solution for further improving the energy efficiency of distributed independent pump-controlled excavator systems.

Distributed electro-hydraulic pump-controlled excavators offer significant potential for improving energy efficiency by eliminating throttling losses and decoupling multi-actuator interactions. However, the highly nonlinear dynamics, time-varying loads, and parameter uncertainties inherent in excavator operations pose substantial challenges to achieving high-precision trajectory control in such systems. This paper proposes a distributed independent electro-hydraulic servo pump-controlled excavator and develops a unified adaptive robust trajectory control framework to address these challenges. An adaptive robust backstepping controller is constructed by explicitly incorporating hydraulic driving force dynamics into the trajectory tracking loop, enabling coordinated regulation of displacement, velocity, and force. To further enhance robustness against time-varying operating conditions, a novel feedforward compensation strategy is introduced by experimentally identifying the mapping relationships between hydraulic cylinder displacement and both load force and inertial mass. The feedforward mechanism is integrated with a projection-based adaptive law, forming a unified parameter adaptation scheme capable of handling strong nonlinearities and uncertain dynamics. In addition, a quadrant-identification mechanism is incorporated to ensure consistent control performance across different operating modes of the pump-controlled excavator. Comprehensive experimental studies, including step response tests, trajectory tracking of boom and arm cylinders, and practical leveling operations, are conducted to validate the proposed method. The results demonstrate that the proposed strategy significantly improves tracking accuracy, dynamic response, and disturbance rejection capability compared with conventional PID and non-adaptive robust control approaches.