Modelling of an hydraulic excavator using simplifiedrefined instrumental variable(SRIV)algorithm

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 exoeriments.

Digital Servo Control of a Robotic Excavator

An electro-hydraulic control system is designed and implemented for a robotic excavator known as the Lancaster University Computerised and Intelligent Excavator （LUCIE）. The excavator is being developed to autonomously dig trenches without human intervention. Since the behavior of the excavator arm is dominated by the nonlinear dynamics of the hydraulic actuators and by the large and unpredictable external disturbances when digging, it is difficult to provide adequate accurate, quick and smooth movement under traditional control methodology, e.g., PI/PID, which is comparable with that of an average human operator. The data-based dynamic models are developed utilizing the simplified refined instrumental variable （SRIV） identification algorithm to precisely describe the nonlinear dynamical behaviour of the electro-hydraulic actuation system. Based on data-based model and proportional-integral-plus （PIP） methodology, which is a non-minimal state space method of control system design based on the true digital control （TDC） system design philosophy, a novel control system is introduced to drive the excavator arm accurately, quickly and smoothly along the desired path. The performance of simulation and field tests which drive the bucket along straight lines both demonstrate the feasibility and validity of the proposed control scheme.

Surface Mine System Simulation and Safety Risk Management

Modern surface mines, either mono-system or multi-systems, need a large fleet of equipment consisting of excavators, loaders, haulers and auxiliary machines. Presently, the complexity of the system, the interference between sub-systems and the lag in management skills has been a bottle neck for improving productivity of the system. Based on the fact that the traditional tools for safety analysis have been insufficient to evaluate systematically and dynamically the safety risks, this paper tries to create a virtual reality tool consisting of human, machine and mines, using Pro/E and the 3D MAX software in order to evaluate visually the operations of typical mining equipment, such as the bucket wheel excavator (BWE), the shovel, the truck and the dragline. Within this virtual world, the behavior of the system, such as interaction, interference and potential risk can be replayed and reviewed visually. The objective of the study is to identify the critical safety issues of the system and to provide a convenient and powerful tool for safety training and safety management.