For a class of unknown nonlinear time-delay systems, an adaptive neural network （NN） control design approach is proposed. Backstepping, domination and adaptive bounding design technique are combined to construct a r...For a class of unknown nonlinear time-delay systems, an adaptive neural network （NN） control design approach is proposed. Backstepping, domination and adaptive bounding design technique are combined to construct a robust memoryless adaptive NN tracking controller. Unknown time-delay functions are approximated by NNs, such that the requirement on the nonlinear time-delay functions is relaxed. Based on Lyapunov-Krasoviskii functional, the sem-global uniformly ultimately boundedness （UUB） of all the signals in the closed-loop system is proved. The arbitrary output tracking accuracy is achieved by tuning the design parameters. The feasibility is investigated by an illustrative simulation example.展开更多
Hierarchical adaptive bounding setting （HABS）, a novel algorithm to reduce potentially visible set, is designed to be Used for various geometry shape character in complex simulation scene to greatly improve geometry...Hierarchical adaptive bounding setting （HABS）, a novel algorithm to reduce potentially visible set, is designed to be Used for various geometry shape character in complex simulation scene to greatly improve geometry spatial storage precision. A spatial hierarchy tree is used to represent the topology of the model, and then the visibility geometry set from the viewpoint is determined by processing the hierarchy tree and frustum detection. In this process, HABS improves the viewpoint-to-region visibility detection efficiently. The algorithm is well-suited for complex models whose shape characters are various.展开更多
A high-precision fuzzy controller, based on a state observer, is developed for a class of nonlinear single-input-single-output(SISO) systems with system uncertainties and external disturbances. The state observer is i...A high-precision fuzzy controller, based on a state observer, is developed for a class of nonlinear single-input-single-output(SISO) systems with system uncertainties and external disturbances. The state observer is introduced to resolve the problem of the unavailability of state variables. Assisted by the observer, a variable universe fuzzy system is designed to approximate the ideal control law. Being auxiliary components, a robust control term and a state feedback control term are designed to suppress the influence of the lumped uncertainties and remove the observation error, respectively. Different from the existing results, no additional dynamic order is required for the control design. All the adaptive laws and the control law are built based on the Lyapunov synthesis approach, and the signals involved in the closed-loop system are guaranteed to be uniformly ultimately bounded. Simulation results performed on Duffing forced oscillation demonstrate the advantages of the proposed control scheme.展开更多
基金This project was supported by the National Natural Science Foundation of China (69974028 60374015)
文摘For a class of unknown nonlinear time-delay systems, an adaptive neural network （NN） control design approach is proposed. Backstepping, domination and adaptive bounding design technique are combined to construct a robust memoryless adaptive NN tracking controller. Unknown time-delay functions are approximated by NNs, such that the requirement on the nonlinear time-delay functions is relaxed. Based on Lyapunov-Krasoviskii functional, the sem-global uniformly ultimately boundedness （UUB） of all the signals in the closed-loop system is proved. The arbitrary output tracking accuracy is achieved by tuning the design parameters. The feasibility is investigated by an illustrative simulation example.
文摘Hierarchical adaptive bounding setting （HABS）, a novel algorithm to reduce potentially visible set, is designed to be Used for various geometry shape character in complex simulation scene to greatly improve geometry spatial storage precision. A spatial hierarchy tree is used to represent the topology of the model, and then the visibility geometry set from the viewpoint is determined by processing the hierarchy tree and frustum detection. In this process, HABS improves the viewpoint-to-region visibility detection efficiently. The algorithm is well-suited for complex models whose shape characters are various.
基金supported by National Natural Science Foundation of China(No.61074044)Basic and Cutting-edge Technology of Science and Technology Department of Henan Province(No.092300410178)
文摘A high-precision fuzzy controller, based on a state observer, is developed for a class of nonlinear single-input-single-output(SISO) systems with system uncertainties and external disturbances. The state observer is introduced to resolve the problem of the unavailability of state variables. Assisted by the observer, a variable universe fuzzy system is designed to approximate the ideal control law. Being auxiliary components, a robust control term and a state feedback control term are designed to suppress the influence of the lumped uncertainties and remove the observation error, respectively. Different from the existing results, no additional dynamic order is required for the control design. All the adaptive laws and the control law are built based on the Lyapunov synthesis approach, and the signals involved in the closed-loop system are guaranteed to be uniformly ultimately bounded. Simulation results performed on Duffing forced oscillation demonstrate the advantages of the proposed control scheme.
