This paper addresses an uncertain nonlinear control system problem with complex state constraints and mismatched uncertainties.A novel Gaussian Mixture Model(GMM)based adaptive PID-Nonsingular Terminal Sliding Mode Co...This paper addresses an uncertain nonlinear control system problem with complex state constraints and mismatched uncertainties.A novel Gaussian Mixture Model(GMM)based adaptive PID-Nonsingular Terminal Sliding Mode Control(NTSMC)(GMM-adaptive-PID-NTSMC)method is proposed.It is achieved by combining a GMM based adaptive potential function with a novel switching surface of PID-NTSMC.Next,the stability of the closed-loop system is proved.The main contribution of this paper is that the GMM method is applied to obtain the analytic description of the complex bounded state constraints,ensuring that the states'constraints are not violated with GMM-based adaptive potential function.The developed potential function can consider the influence of uncertainties.More importantly,the GMM-adaptive-PID-NTSMC can be generalized to control a more representative class of uncertain nonlinear systems with constrained states and mismatched uncertainties.In addition,the proposed controller enhances the robustness,and requires less control cost and reduces the steady state error with respect to the Artificial Potential Function based Nonsingular Terminal Sliding Mode Control(APF-NTSMC),GMM-NTSMC and GMM-adaptive-NTSMC.At last,numerical simulation is performed to validate the superior performance of the proposed controller.展开更多
Usually the equation of state （EoS） of dark matter is zero when it is cold, however there exists the possibility of a （effective） nonzero EoS of dark matter due to its decay and interaction with dark energy. In th...Usually the equation of state （EoS） of dark matter is zero when it is cold, however there exists the possibility of a （effective） nonzero EoS of dark matter due to its decay and interaction with dark energy. In this work, we try to constrain the EoS of dark matter/JAdm using the currently available cosmic observations which include the geometrical and dynamical measurements. For the geometrical measurements, the luminosity distance of type Ia supernovae, the angular diameter distance and comoving sound horizon from baryon acoustic oscillations and the cosmic microwave background radiation will be employed. The data points from the redshift-space distortion and weak gravitational lensing will be taken as dynamical measurements. Using the Markov chain Monte Carlomethod, we obtain a very tight constraint on the-EoS of dark matter：wdm=0.0000532 ＋0.000692＋0.00136＋0.00183 -0.000686-0.00136-0.00177.展开更多
This paper presents an algorithm for identifying desirable multiple targets in an intracellular regulation network. The algorithm is based on constrained state feedback and Monte-Carlo simulations. The computational c...This paper presents an algorithm for identifying desirable multiple targets in an intracellular regulation network. The algorithm is based on constrained state feedback and Monte-Carlo simulations. The computational complexity of the algorithm increases linearly with increasing the number of species in a gene regulation system. An estimate is derived for the confidence level of the predicted minimum required perturbation strength when targets are prescribed a priori. The algorithm has been used to analyze the cell cycle of Xenopus frog eggs. The results agree well with available results for single target perturbations, and multitarget interference is usually not equal to the summation of the single-target interferences.展开更多
基金supported by the National Natural Science Foundation of China(Nos.61690210,61690213,12002383)。
文摘This paper addresses an uncertain nonlinear control system problem with complex state constraints and mismatched uncertainties.A novel Gaussian Mixture Model(GMM)based adaptive PID-Nonsingular Terminal Sliding Mode Control(NTSMC)(GMM-adaptive-PID-NTSMC)method is proposed.It is achieved by combining a GMM based adaptive potential function with a novel switching surface of PID-NTSMC.Next,the stability of the closed-loop system is proved.The main contribution of this paper is that the GMM method is applied to obtain the analytic description of the complex bounded state constraints,ensuring that the states'constraints are not violated with GMM-based adaptive potential function.The developed potential function can consider the influence of uncertainties.More importantly,the GMM-adaptive-PID-NTSMC can be generalized to control a more representative class of uncertain nonlinear systems with constrained states and mismatched uncertainties.In addition,the proposed controller enhances the robustness,and requires less control cost and reduces the steady state error with respect to the Artificial Potential Function based Nonsingular Terminal Sliding Mode Control(APF-NTSMC),GMM-NTSMC and GMM-adaptive-NTSMC.At last,numerical simulation is performed to validate the superior performance of the proposed controller.
基金Supported by the National Natural Science Foundation of China under Grant No 11275035
文摘Usually the equation of state （EoS） of dark matter is zero when it is cold, however there exists the possibility of a （effective） nonzero EoS of dark matter due to its decay and interaction with dark energy. In this work, we try to constrain the EoS of dark matter/JAdm using the currently available cosmic observations which include the geometrical and dynamical measurements. For the geometrical measurements, the luminosity distance of type Ia supernovae, the angular diameter distance and comoving sound horizon from baryon acoustic oscillations and the cosmic microwave background radiation will be employed. The data points from the redshift-space distortion and weak gravitational lensing will be taken as dynamical measurements. Using the Markov chain Monte Carlomethod, we obtain a very tight constraint on the-EoS of dark matter：wdm=0.0000532 ＋0.000692＋0.00136＋0.00183 -0.000686-0.00136-0.00177.
基金Supported in part by the Basic Research Foundation of Tsinghua National Laboratory for Information Science and Technology (TNList)the National Natural Science Foundation of China (Nos. 60625305 and 60574008)the National High-Tech Research and Development (863) Program of China (No. 2006AA2Z311)
文摘This paper presents an algorithm for identifying desirable multiple targets in an intracellular regulation network. The algorithm is based on constrained state feedback and Monte-Carlo simulations. The computational complexity of the algorithm increases linearly with increasing the number of species in a gene regulation system. An estimate is derived for the confidence level of the predicted minimum required perturbation strength when targets are prescribed a priori. The algorithm has been used to analyze the cell cycle of Xenopus frog eggs. The results agree well with available results for single target perturbations, and multitarget interference is usually not equal to the summation of the single-target interferences.
