首页|University of Science and Technology Beijing Researcher Updates Knowledge of Rob otics (Event-triggered sliding mode control for trajectory tracking of robotic s ystem with signal quantization)
University of Science and Technology Beijing Researcher Updates Knowledge of Rob otics (Event-triggered sliding mode control for trajectory tracking of robotic s ystem with signal quantization)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators publish new report on robotics. Acc ording to news reporting from Beijing, People’s Republic of China, by NewsRx jou rnalists, research stated, “This paper deals with robotic systems trajectory tra cking problems by designing a new event-triggered sliding mode control (ET-SMC) algorithm with signal quantization.” Financial supporters for this research include Major Project of The New Generati on of Artificial Intelligence. Our news journalists obtained a quote from the research from University of Scien ce and Technology Beijing: “More precisely, an event-triggered control strategy is introduced to the sliding mode control algorithm with robustness to reduce th e controller update frequency, so as to reduce the network communication resourc es consumption and maintain the control accuracy. In addition, the dynamic quant ization method is adopted between the controller and the actuator for more commu nication efficiency. Unlike periodic time-triggered control strategy, a novel ev ent triggering condition which requires no statedependent variables is discusse d for less triggering threshold computations. Furthermore, the minimum interval of adjacent triggering instant based on the new triggering condition can be obta ined to avoid the Zeno phenomenon.”
University of Science and Technology Bei jingBeijingPeople’s Republic of ChinaAsiaAlgorithmsEmerging Technologi esMachine LearningRoboticsRobots
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