Abstract
Instead of establishing mathematical hydraulic system models from physical laws usually done with the problems of complex modelling processes, low reliability and practicality caused by large uncertainties, a novel modelling method for a highly nonlinear system of a hydraulic excavator is presented. Based on the data collected in the excavator’s arms driving experiments, a data-based excavator dynamic model using Simplified Refined Instrumental Variable (SRIV) identification and estimation algorithms is established. The validity of the proposed data-based model is indirectly demonstrated by the performance of computer simulation and the real machine motion control experiments.
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Jun GU (Ph.D., Lancaster University, 2004; B.Sc., University of Science & Technology of China, 2000) lecturer at the School of Mechanical & Electronic Engineering, Soochow University. Member of The Institution of Engineering and Technology (MIET), UK. His current research interests include robotics, intelligent control and mechatronics.
James TAYLOR (Ph.D.) senior lecturer at the Engineering Department, Lancaster University (UK). His research interests mainly lies in linear and nonlinear non-minimal state space methods for control system design, with its applications in the fields of construction robotics, environmental control, marine energy and motorway traffic.
Derek SEWARD (Ph.D.) professor in Engineering Department, Lancaster University (U.K.). He is a board director of the International Association for Automation and Robotics at the Construction, a member of the U.K. construction expert panel who contributed to the ‘Action for Foresight’ review carried out by EPSRC (Engineering and Physical Sciences Research Council, U.K.). His research interests include robotics, construction automatics and safety engineering.
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Gu, J., Taylor, J. & Seward, D. Modelling of an hydraulic excavator using simplified refined instrumental variable (SRIV) algorithm. J. Control Theory Appl. 5, 391–396 (2007). https://doi.org/10.1007/s11768-006-6180-2
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DOI: https://doi.org/10.1007/s11768-006-6180-2