Consider the design and implementation of an electro-hydraulic control system for a robotic excavator, namely the Lancaster University computerized and intelligent excavator (LUCIE). The excavator was developed to aut...Consider the design and implementation of an electro-hydraulic control system for a robotic excavator, namely the Lancaster University computerized and intelligent excavator (LUCIE). The excavator was developed to autonomously dig trenches without human intervention. One stumbling block is the achievement of adequate, accurate, quick and smooth movement under automatic control, which is difficult for traditional control algorithm, e.g. PI/PID. A gain scheduling design, based on the true digital proportional-integral-plus (PIP) control methodology, was utilized to regulate the nonlinear joint dynamics. Simulation and initial field tests both demonstrated the feasibility and robustness of proposed technique to the uncertainties of parameters, time delay and load disturbances, with the excavator arm directed along specified trajectories in a smooth, fast and accurate manner. The tracking error magnitudes for oblique straight line and horizontal straight line are less than 20 mm and 50 mm, respectively, while the velocity reaches 9 m/min.展开更多
This paper presents an advanced control strategy for DC-DC buck converters utilizing Non-Minimal State Space (NMSS) representation combined with Proportional-Integral-Plus (PIP) control, optimized through Linear Quadr...This paper presents an advanced control strategy for DC-DC buck converters utilizing Non-Minimal State Space (NMSS) representation combined with Proportional-Integral-Plus (PIP) control, optimized through Linear Quadratic Regulator (LQR) design. The proposed approach leverages NMSS to eliminate the need for state observers, enhancing robustness against model mismatch and improving overall system performance. The PIP controller extends traditional PI control by incorporating additional dynamic feedback. Experimental results demonstrate that the NMSS-PIP-LQR controlled buck converter achieves excellent dynamic performance. The design procedure is fully documented, and microcontroller implementation issues are discussed.展开更多
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 autonomou...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.展开更多
Various control systems for a robotic excavator named LUCIE (Lancaster University Computerized and Intelligent Excavator),were investigated. The excavator is being developed to dig trenches autonomously. One stumbling...Various control systems for a robotic excavator named LUCIE (Lancaster University Computerized and Intelligent Excavator),were investigated. The excavator is being developed to dig trenches autonomously. One stumbling block is the achievement of adequate,accurate,quick and smooth movement under automatic control. Here,both classical and modern approaches are considered,including proportional-integral-derivative (PID) control tuned by conventional Zigler-Nichols rules,linear proportional-integral-plus (PIP) control,and a novel nonlinear PIP controller based on a state-dependent parameter (SDP) model structure,in which the parameters are functionally dependent on other variables in the system. Implementation results for the excavator joint arms control demonstrate that SDP-PIP controller provides the improved performance with fast,smooth and accurate response in comparison with both PID and linearized PIP control.展开更多
基金Project(K5117827)supported by Scientific Research Foundation for the Returned Overseas Chinese ScholarsProject(08KJB510021)supported by the Natural Science Research Council of Jiangsu Province,China+1 种基金Project(Q3117918)supported by Scientific Research Foundation for Young Teachers of Soochow University,ChinaProject(60910001)supported by National Natural Science Foundation of China
文摘Consider the design and implementation of an electro-hydraulic control system for a robotic excavator, namely the Lancaster University computerized and intelligent excavator (LUCIE). The excavator was developed to autonomously dig trenches without human intervention. One stumbling block is the achievement of adequate, accurate, quick and smooth movement under automatic control, which is difficult for traditional control algorithm, e.g. PI/PID. A gain scheduling design, based on the true digital proportional-integral-plus (PIP) control methodology, was utilized to regulate the nonlinear joint dynamics. Simulation and initial field tests both demonstrated the feasibility and robustness of proposed technique to the uncertainties of parameters, time delay and load disturbances, with the excavator arm directed along specified trajectories in a smooth, fast and accurate manner. The tracking error magnitudes for oblique straight line and horizontal straight line are less than 20 mm and 50 mm, respectively, while the velocity reaches 9 m/min.
文摘This paper presents an advanced control strategy for DC-DC buck converters utilizing Non-Minimal State Space (NMSS) representation combined with Proportional-Integral-Plus (PIP) control, optimized through Linear Quadratic Regulator (LQR) design. The proposed approach leverages NMSS to eliminate the need for state observers, enhancing robustness against model mismatch and improving overall system performance. The PIP controller extends traditional PI control by incorporating additional dynamic feedback. Experimental results demonstrate that the NMSS-PIP-LQR controlled buck converter achieves excellent dynamic performance. The design procedure is fully documented, and microcontroller implementation issues are discussed.
基金supported by the Lancaster University (UK)SooChow University, China+2 种基金the UK Engineering and Physical Sciences Research CouncilUniversities’ Natural Science Research Council of Jiangsu Universities, China(Grant No. 08KJB510021)Scientific Research Foundation for the Returned Overseas Chinese Scholars, Ministry of Education of China
文摘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.
基金Work supported by the Lancaster University,UK and Jiangsu Provincial Laboratory of Advanced Robotics,SooChow University,ChinaProject(BK2009509) supported by the Natural Science Foundation of Jiangsu Province,China+1 种基金Project(K5117827) supported by the Scientific Research Foundation for the Returned Scholars,Ministry of Education of ChinaProject(Q3117918) supported by the Scientific Research Foundation for Young Teachers of Soochow University,China
文摘Various control systems for a robotic excavator named LUCIE (Lancaster University Computerized and Intelligent Excavator),were investigated. The excavator is being developed to dig trenches autonomously. One stumbling block is the achievement of adequate,accurate,quick and smooth movement under automatic control. Here,both classical and modern approaches are considered,including proportional-integral-derivative (PID) control tuned by conventional Zigler-Nichols rules,linear proportional-integral-plus (PIP) control,and a novel nonlinear PIP controller based on a state-dependent parameter (SDP) model structure,in which the parameters are functionally dependent on other variables in the system. Implementation results for the excavator joint arms control demonstrate that SDP-PIP controller provides the improved performance with fast,smooth and accurate response in comparison with both PID and linearized PIP control.
