Reasons and realities such as being non-linear of dynamical equations,being lightweight and unstable nature of quadrotor,along with internal and external disturbances and parametric uncertainties,have caused that the ...Reasons and realities such as being non-linear of dynamical equations,being lightweight and unstable nature of quadrotor,along with internal and external disturbances and parametric uncertainties,have caused that the controller design for these quadrotors is considered the challenging issue of the day.In this work,an adaptive sliding mode controller based on neural network is proposed to control the altitude of a quadrotor.The error and error derivative of the altitude of a quadrotor are the inputs of neural network and altitude sliding surface variable is its output.Neural network estimates the sliding surface variable adaptively according to the conditions of quadrotor and sets the altitude of a quadrotor equal to the desired value.The proposed controller stability has been proven by Lyapunov theory and it is shown that all system states reach to sliding surface and are remaining in it.The superiority of the proposed control method has been proven by comparison and simulation results.展开更多
By numerically solving the Sch6dinger equation of a three-nuclear-spin system, the effects of the non-uniform nearest-neighbor （NN） interaction on the fidelity of a quantum controlled-controlled-no （CCN） gate are...By numerically solving the Sch6dinger equation of a three-nuclear-spin system, the effects of the non-uniform nearest-neighbor （NN） interaction on the fidelity of a quantum controlled-controlled-no （CCN） gate are investigated for a digital initial state and a superposition initial state respectively. It is found from our simulation that the ratio of the deviation of the NN coupling δJ to the NN coupling J should be smaller than 0.0005 to ensure a high fidelity of the quantum CCN gate.展开更多
A new chaotic particle swarm algorithm is proposed in order to avoid the premature convergence of the particle swarm optimization and the shortcomings of the chaotic optimization, such as slow searching speed and low ...A new chaotic particle swarm algorithm is proposed in order to avoid the premature convergence of the particle swarm optimization and the shortcomings of the chaotic optimization, such as slow searching speed and low accuracy when used in the multivariable systems or in large search space. The new algorithm combines the particle swarm algorithm and the chaotic optimization, using randomness and ergodicity of chaos to overcome the premature convergence of the particle swarm optimization. At the same time, a new neural network feedback linearization control system is built to control the single-machine infinite-bus system. The network parameters are trained by the chaos particle swarm algorithm, which makes the control achieve optimization and the control law of prime mover output torque obtained. Finally, numerical simulation and practical application validate the effectiveness of the method.展开更多
Controller area networks （CANs） have been designed for multiplexing communication between electronic control units （ECUs） in vehicles and many high-level industrial control applications. When a CAN bus is overload...Controller area networks （CANs） have been designed for multiplexing communication between electronic control units （ECUs） in vehicles and many high-level industrial control applications. When a CAN bus is overloaded by a large number of ECUs connected to it, both the waiting time and the error probability of the data transmission are increased. Thus, it is desirable to reduce the CAN frame length, since the duration of data transmission is proportional to the frame length. In this paper, we present a CAN message compression method to reduce the CAN frame length. Experimental results indicate that CAN transmission data can be compressed by up to 81.06% with the proposed method. By using an embedded test board, we show that 64-bit engine management system （EMS） CAN data compression can be performed within 0.16 ms; consequently, the proposed algorithm can be successfully used in automobile applications.展开更多
This paper concerns the stabilization of switched dynamical networks with logarithmic quantization couplings in a settling time.The switching sequence is constrained by hybrid dwell time. Controller is designed by usi...This paper concerns the stabilization of switched dynamical networks with logarithmic quantization couplings in a settling time.The switching sequence is constrained by hybrid dwell time. Controller is designed by using limited information. Due to the quantization and switching, traditional finite-time analysis methods cannot be utilized directly. By designing multiple Lyapunov functions and constructing comparison systems, a general criterion formulated by matrix inequalities is first given. Then specific conditions in terms of linear matrix inequalities are established by partitioning the dwell time and using convex combination technique. An optimal algorithm is proposed for the estimation of settling time. Numerical simulations are given to verify the effectiveness of the theoretical results.展开更多
基金authorities of East Tehran Branch,Islamic Azad University,Tehran,Iran,for providing support and necessary facilities
文摘Reasons and realities such as being non-linear of dynamical equations,being lightweight and unstable nature of quadrotor,along with internal and external disturbances and parametric uncertainties,have caused that the controller design for these quadrotors is considered the challenging issue of the day.In this work,an adaptive sliding mode controller based on neural network is proposed to control the altitude of a quadrotor.The error and error derivative of the altitude of a quadrotor are the inputs of neural network and altitude sliding surface variable is its output.Neural network estimates the sliding surface variable adaptively according to the conditions of quadrotor and sets the altitude of a quadrotor equal to the desired value.The proposed controller stability has been proven by Lyapunov theory and it is shown that all system states reach to sliding surface and are remaining in it.The superiority of the proposed control method has been proven by comparison and simulation results.
基金Supported by National Science Foundation of China under Grant Nos. 10874021 and 10774107Science Foundation of Education Committee of Jiangsu Province under Grant No. 07KJB140002
文摘By numerically solving the Sch6dinger equation of a three-nuclear-spin system, the effects of the non-uniform nearest-neighbor （NN） interaction on the fidelity of a quantum controlled-controlled-no （CCN） gate are investigated for a digital initial state and a superposition initial state respectively. It is found from our simulation that the ratio of the deviation of the NN coupling δJ to the NN coupling J should be smaller than 0.0005 to ensure a high fidelity of the quantum CCN gate.
基金This work is supported by National Natural Science Foundation of China （50776005）.
文摘A new chaotic particle swarm algorithm is proposed in order to avoid the premature convergence of the particle swarm optimization and the shortcomings of the chaotic optimization, such as slow searching speed and low accuracy when used in the multivariable systems or in large search space. The new algorithm combines the particle swarm algorithm and the chaotic optimization, using randomness and ergodicity of chaos to overcome the premature convergence of the particle swarm optimization. At the same time, a new neural network feedback linearization control system is built to control the single-machine infinite-bus system. The network parameters are trained by the chaos particle swarm algorithm, which makes the control achieve optimization and the control law of prime mover output torque obtained. Finally, numerical simulation and practical application validate the effectiveness of the method.
基金Project supported by the Information Technology R&D Program of MOTIE/KEIT(No.10044092)Research Funds of Chonbuk National University in 2013
文摘Controller area networks （CANs） have been designed for multiplexing communication between electronic control units （ECUs） in vehicles and many high-level industrial control applications. When a CAN bus is overloaded by a large number of ECUs connected to it, both the waiting time and the error probability of the data transmission are increased. Thus, it is desirable to reduce the CAN frame length, since the duration of data transmission is proportional to the frame length. In this paper, we present a CAN message compression method to reduce the CAN frame length. Experimental results indicate that CAN transmission data can be compressed by up to 81.06% with the proposed method. By using an embedded test board, we show that 64-bit engine management system （EMS） CAN data compression can be performed within 0.16 ms; consequently, the proposed algorithm can be successfully used in automobile applications.
基金supported by the National Natural Science Foundation of China(Grants Nos.61673078,61573096,61273220&61472257)
文摘This paper concerns the stabilization of switched dynamical networks with logarithmic quantization couplings in a settling time.The switching sequence is constrained by hybrid dwell time. Controller is designed by using limited information. Due to the quantization and switching, traditional finite-time analysis methods cannot be utilized directly. By designing multiple Lyapunov functions and constructing comparison systems, a general criterion formulated by matrix inequalities is first given. Then specific conditions in terms of linear matrix inequalities are established by partitioning the dwell time and using convex combination technique. An optimal algorithm is proposed for the estimation of settling time. Numerical simulations are given to verify the effectiveness of the theoretical results.
