This paper addresses the energy-inefficiency problem of four-degrees-of-freedom (4-DOF) hydraulic manipulators through redundancy resolution in robotic closed-loop controlled applications. Because conventional methods typically are local and have poor performance for resolving redundancy with respect to minimum hydraulic energy consumption, global energy-optimal redundancy resolution is proposed at the valve-controlled actuator and hydraulic power system interaction level. The energy consumption of the widely popular valve-controlled load-sensing (LS) and constant-pressure (CP) systems is effectively minimised through cost functions formulated in a discrete-time dynamic programming (DP) approach with minimum state representation. A prescribed end-effector path and important actuator constraints at the position, velocity and acceleration levels are also satisfied in the solution. Extensive field experiments performed on a forestry hydraulic manipulator demonstrate the performance of the proposed solution. Approximately 15-30% greater hydraulic energy consumption was observed with the conventional methods in the LS and CP systems. These results encourage energy-optimal redundancy resolution in future robotic applications of hydraulic manipulators.
Model-based condition monitoring methods are widely used in condition monitoring. They usually rely on ad hoc approaches to verify the system model and then best practices are reported to detect the given set of faults. This first part of a two-piece paper introduces a generic Global Sensitivity Analysis-based approach that can be applied systematically to verify the model parameter sensitivities used for the model-based fault detection. The case study is a generic servo valve-controlled hydraulic cylinder with unknown loading condition which is then systematically analyzed with Global Sensitivity Analysis. The method shows valuable insight into systematic model verification and resulting fault detection in terms of showing the dominant sensitivity of the nominal flow rate and nominal pressure difference, and the exact sensitivities of 0 -1 dm 3 /min external and internal leakages on cylinder chamber pressures and velocity. In the second paper, an Unscented Kalman Filter-based Fault Detection and Isolation scheme for leakage and valve faults of a generic servo valve-controlled hydraulic cylinder is devised and fault patterns are presented.
Hydraulic manipulators on mobile machines, whose hydraulic actuators are usually controlled by mobile hydraulic valves, are being considered for robotic closed-loop control. A feed-forward-based strategy combining position and velocity feedback has been found to be an effective method for the motion control of pressure-compensated mobile hydraulic valves that have a significant dead zone. The feed-forward can be manually identified. However, manually identifying the feed-forward models for each valve-actuator pair is often very time-consuming and error-prone. For this practical reason, we propose an automated feed-forward learning method based on velocity and position feedback. We present experimental results for a heavy-duty hydraulic manipulator on a forest forwarder to demonstrate the effectiveness of the proposed method. These results motivate the automated identification of velocity feed-forward models for motion control of heavy-duty hydraulic manipulators controlled by pressure-compensated mobile hydraulic valves that have a significant input dead zone.
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