We propose a novel methodology based on the projector-camera （ProCam） system to address the photometric compensation issue for the projection display on the patterned screen. The patterned screen is treated as the c...We propose a novel methodology based on the projector-camera （ProCam） system to address the photometric compensation issue for the projection display on the patterned screen. The patterned screen is treated as the combination of a perfect white screen and a color modulator. The perfect white screen is used to automatically and accurately characterize the ProCam system off line using the polynomial model, and the parameters of the color modulator can be efficiently recovered by employing only two gray images based on the linear reflectance model. The experimental results show that the color artifacts of the display image can be greatly improved with this methodology, which demonstrates its feasibility and validity in the photometric compensation.展开更多
In this study,an adaptive neuro-observer-based optimal control(ANOPC)policy is introduced for unknown nonaffine nonlinear systems with control input constraints.Hamilton–Jacobi–Bellman(HJB)framework is employed to m...In this study,an adaptive neuro-observer-based optimal control(ANOPC)policy is introduced for unknown nonaffine nonlinear systems with control input constraints.Hamilton–Jacobi–Bellman(HJB)framework is employed to minimize a non-quadratic cost function corresponding to the constrained control input.ANOPC consists of both analytical and algebraic parts.In the analytical part,first,an observer-based neural network(NN)approximates uncertain system dynamics,and then another NN structure solves the HJB equation.In the algebraic part,the optimal control input that does not exceed the saturation bounds is generated.The weights of two NNs associated with observer and controller are simultaneously updated in an online manner.The ultimately uniformly boundedness(UUB)of all signals of the whole closed-loop system is ensured through Lyapunov’s direct method.Finally,two numerical examples are provided to confirm the effectiveness of the proposed control strategy.展开更多
文摘We propose a novel methodology based on the projector-camera （ProCam） system to address the photometric compensation issue for the projection display on the patterned screen. The patterned screen is treated as the combination of a perfect white screen and a color modulator. The perfect white screen is used to automatically and accurately characterize the ProCam system off line using the polynomial model, and the parameters of the color modulator can be efficiently recovered by employing only two gray images based on the linear reflectance model. The experimental results show that the color artifacts of the display image can be greatly improved with this methodology, which demonstrates its feasibility and validity in the photometric compensation.
文摘In this study,an adaptive neuro-observer-based optimal control(ANOPC)policy is introduced for unknown nonaffine nonlinear systems with control input constraints.Hamilton–Jacobi–Bellman(HJB)framework is employed to minimize a non-quadratic cost function corresponding to the constrained control input.ANOPC consists of both analytical and algebraic parts.In the analytical part,first,an observer-based neural network(NN)approximates uncertain system dynamics,and then another NN structure solves the HJB equation.In the algebraic part,the optimal control input that does not exceed the saturation bounds is generated.The weights of two NNs associated with observer and controller are simultaneously updated in an online manner.The ultimately uniformly boundedness(UUB)of all signals of the whole closed-loop system is ensured through Lyapunov’s direct method.Finally,two numerical examples are provided to confirm the effectiveness of the proposed control strategy.
