With the rapid development of modern science and technology,artificial intelligence(AI)technology is becoming more and more mature,which has brought a profound impact on every field of human society.The new era backgr...With the rapid development of modern science and technology,artificial intelligence(AI)technology is becoming more and more mature,which has brought a profound impact on every field of human society.The new era background provides a new teaching concept for ideological and political teaching in colleges and universities.Teachers in colleges and universities should adopt a positive attitude to face the teaching change brought by new technology,update the teaching ideas in time,and adjust the teaching strategy.This paper will analyze the current situation of the integrated development of AI and ideological and political teaching and put forward corresponding teaching strategies to help train well-developed socialist successors.展开更多
A partition-of-unity-based approach is proposed to derive an approximate model for a class of nonlinear systems. The precision of the approximate model is analyzed by using the modulus of continuity of continuous func...A partition-of-unity-based approach is proposed to derive an approximate model for a class of nonlinear systems. The precision of the approximate model is analyzed by using the modulus of continuity of continuous functions. The system stability of the approximate model is analyzed by using Lyapunov stability theory. A design algorithm for constructing tracking controllers with tracking performance related to tracking error is given based on the approximate model and the partition of unity method.展开更多
For the congestion problems in high-speed networks, a genetic based fuzzy Q-learning flow controller is proposed. Because of the uncertainties and highly time-varying, it is not easy to accurately obtain the complete ...For the congestion problems in high-speed networks, a genetic based fuzzy Q-learning flow controller is proposed. Because of the uncertainties and highly time-varying, it is not easy to accurately obtain the complete information for high-speed networks. In this case, the Q-learning, which is independent of mathematic model, and prior-knowledge, has good performance. The fuzzy inference is introduced in order to facilitate generalization in large state space, and the genetic operators are used to obtain the consequent parts of fuzzy rules. Simulation results show that the proposed controller can learn to take the best action to regulate source flow with the features of high throughput and low packet loss ratio, and can avoid the occurrence of congestion effectively.展开更多
Based on high order dynamic neural network, this paper presents the tracking problem for uncertain nonlinear composite system, which contains external disturbance, whose nonlinearities are assumed to be unknown. A smo...Based on high order dynamic neural network, this paper presents the tracking problem for uncertain nonlinear composite system, which contains external disturbance, whose nonlinearities are assumed to be unknown. A smooth controller is designed to guarantee a uniform ultimate boundedness property for the tracking error and all other signals in the dosed loop. Certain measures are utilized to test its performance. No a priori knowledge of an upper bound on the “optimal” weight and modeling error is required; the weights of neural networks are updated on-line. Numerical simulations performed on a simple example illustrate and clarify the approach.展开更多
This paper considers the problems of almost asymptotic stabilization and global asymptotic regulation （GAR） by output feedback for a class of uncertain nonholonomic systems. By combining the nonsmooth change of coor...This paper considers the problems of almost asymptotic stabilization and global asymptotic regulation （GAR） by output feedback for a class of uncertain nonholonomic systems. By combining the nonsmooth change of coordinates and output feedback domination design together, we construct a simple linear time-varying output feedback controller, which can universally stabilize a whole family of uncertain nonholonomic systems. The simulation demonstrates the effectiveness of the proposed controller.展开更多
文摘With the rapid development of modern science and technology,artificial intelligence(AI)technology is becoming more and more mature,which has brought a profound impact on every field of human society.The new era background provides a new teaching concept for ideological and political teaching in colleges and universities.Teachers in colleges and universities should adopt a positive attitude to face the teaching change brought by new technology,update the teaching ideas in time,and adjust the teaching strategy.This paper will analyze the current situation of the integrated development of AI and ideological and political teaching and put forward corresponding teaching strategies to help train well-developed socialist successors.
基金the National Natural Science Foundation of Guangdong Province (No.032035).
文摘A partition-of-unity-based approach is proposed to derive an approximate model for a class of nonlinear systems. The precision of the approximate model is analyzed by using the modulus of continuity of continuous functions. The system stability of the approximate model is analyzed by using Lyapunov stability theory. A design algorithm for constructing tracking controllers with tracking performance related to tracking error is given based on the approximate model and the partition of unity method.
文摘For the congestion problems in high-speed networks, a genetic based fuzzy Q-learning flow controller is proposed. Because of the uncertainties and highly time-varying, it is not easy to accurately obtain the complete information for high-speed networks. In this case, the Q-learning, which is independent of mathematic model, and prior-knowledge, has good performance. The fuzzy inference is introduced in order to facilitate generalization in large state space, and the genetic operators are used to obtain the consequent parts of fuzzy rules. Simulation results show that the proposed controller can learn to take the best action to regulate source flow with the features of high throughput and low packet loss ratio, and can avoid the occurrence of congestion effectively.
基金This work was supported by the National Natural Science Foundation of China(No.60274009)and Specialized Research Fundfor the Doctoral Program of Higher Education(No.20020145007).
文摘Based on high order dynamic neural network, this paper presents the tracking problem for uncertain nonlinear composite system, which contains external disturbance, whose nonlinearities are assumed to be unknown. A smooth controller is designed to guarantee a uniform ultimate boundedness property for the tracking error and all other signals in the dosed loop. Certain measures are utilized to test its performance. No a priori knowledge of an upper bound on the “optimal” weight and modeling error is required; the weights of neural networks are updated on-line. Numerical simulations performed on a simple example illustrate and clarify the approach.
基金This work was supported by the National Natural Science Foundation of China(No.60304003,60574007,60574080) Scholastic Youth Foundation of Qufu Normal University.
文摘This paper considers the problems of almost asymptotic stabilization and global asymptotic regulation （GAR） by output feedback for a class of uncertain nonholonomic systems. By combining the nonsmooth change of coordinates and output feedback domination design together, we construct a simple linear time-varying output feedback controller, which can universally stabilize a whole family of uncertain nonholonomic systems. The simulation demonstrates the effectiveness of the proposed controller.
