After a recursive multi-step-ahead predictor for nonlinear systems based on local recurrent neural networks is introduced, an intelligent FID controller is adopted to correct the errors including identified model erro...After a recursive multi-step-ahead predictor for nonlinear systems based on local recurrent neural networks is introduced, an intelligent FID controller is adopted to correct the errors including identified model errors and accumulated errors produced in the recursive process. Characterized by predictive control, this method can achieve a good control accuracy and has good robustness. A simulation study shows that this control algorithm is very effective.展开更多
Research on a servo tracking system mounted with a small arm for robot fighting platform based on multi-body system dynamics and intelligent control theory is presented.A multi-body dynamic model which can accurately ...Research on a servo tracking system mounted with a small arm for robot fighting platform based on multi-body system dynamics and intelligent control theory is presented.A multi-body dynamic model which can accurately express dynamic performances of the system is built in ADAMS.In addition,an intelligent PID control model is built with MATLAB/Simulink,and the two models are integrated and co-simulated by the interface of ADAMS/Controls.Simulation experiments indicate that co-simulation technique used for design of the servo tracking system mounted with a small arm can effectively improve its design efficiency,and can also provide theoretical bases for the motion control and performance improvement of the servo tracking system mounted with a small arm.展开更多
This article has the objective of presenting our method to develop and test a motion control system for a heavy-duty hydraulically actuated manipulator,which is part of a newly developed prototype featuring a fully-au...This article has the objective of presenting our method to develop and test a motion control system for a heavy-duty hydraulically actuated manipulator,which is part of a newly developed prototype featuring a fully-autonomous unmanned forestry machine.This control algorithm is based on functional analysis and differential algebra,under the concepts of a new type of approach known as model-free intelligent PID control(iPID).As it can be unsafe to test this form of control directly on real hardware,our main contribution is to introduce a framework for developing and testing control software.This framework incorporates a desktop-size mockup crane equipped with comparable hardware as the real one,which we design and manufactured using 3D-printing.This downscaled mechatronic system allows to safely test the implementation of control software in real-time hardware directly on our desks,prior to the actual testing on the real machine.The results demonstrate that this development framework is useful to safely test control software for heavy-duty systems,and it helped us present the first experiments with the world’s first unmanned forestry machine capable of performing fully autonomous forestry tasks.展开更多
基金This project was supported by the National Natural Science Foundation of China(60174021)Natural Science Foundation Key Project of Tianjin(013800711).
文摘After a recursive multi-step-ahead predictor for nonlinear systems based on local recurrent neural networks is introduced, an intelligent FID controller is adopted to correct the errors including identified model errors and accumulated errors produced in the recursive process. Characterized by predictive control, this method can achieve a good control accuracy and has good robustness. A simulation study shows that this control algorithm is very effective.
基金Sponsored by the Independent Research Foundation of State Key Laboratory(ZDKT08-05)the Ministerial Level Research Foundation(06104040)
文摘Research on a servo tracking system mounted with a small arm for robot fighting platform based on multi-body system dynamics and intelligent control theory is presented.A multi-body dynamic model which can accurately express dynamic performances of the system is built in ADAMS.In addition,an intelligent PID control model is built with MATLAB/Simulink,and the two models are integrated and co-simulated by the interface of ADAMS/Controls.Simulation experiments indicate that co-simulation technique used for design of the servo tracking system mounted with a small arm can effectively improve its design efficiency,and can also provide theoretical bases for the motion control and performance improvement of the servo tracking system mounted with a small arm.
文摘This article has the objective of presenting our method to develop and test a motion control system for a heavy-duty hydraulically actuated manipulator,which is part of a newly developed prototype featuring a fully-autonomous unmanned forestry machine.This control algorithm is based on functional analysis and differential algebra,under the concepts of a new type of approach known as model-free intelligent PID control(iPID).As it can be unsafe to test this form of control directly on real hardware,our main contribution is to introduce a framework for developing and testing control software.This framework incorporates a desktop-size mockup crane equipped with comparable hardware as the real one,which we design and manufactured using 3D-printing.This downscaled mechatronic system allows to safely test the implementation of control software in real-time hardware directly on our desks,prior to the actual testing on the real machine.The results demonstrate that this development framework is useful to safely test control software for heavy-duty systems,and it helped us present the first experiments with the world’s first unmanned forestry machine capable of performing fully autonomous forestry tasks.
