The purpose of this paper is the design of neural network-based adaptive sliding mode controller for uncertain unknown nonlinear systems. A special architecture adaptive neural network, with hyperbolic tangent activat...The purpose of this paper is the design of neural network-based adaptive sliding mode controller for uncertain unknown nonlinear systems. A special architecture adaptive neural network, with hyperbolic tangent activation functions, is used to emulate the equivalent and switching control terms of the classic sliding mode control （SMC）. Lyapunov stability theory is used to guarantee a uniform ultimate boundedness property for the tracking error, as well as of all other signals in the closed loop. In addition to keeping the stability and robustness properties of the SMC, the neural network-based adaptive sliding mode controller exhibits perfect rejection of faults arising during the system operating. Simulation studies are used to illustrate and clarify the theoretical results.展开更多
The real-time capability of integrated flight/propulsion optimal control （IFPOC） is studied. An appli- cation is proposed for IFPOC by combining the onboard hybrid aero-engine model with sequential quadratic pro- gr...The real-time capability of integrated flight/propulsion optimal control （IFPOC） is studied. An appli- cation is proposed for IFPOC by combining the onboard hybrid aero-engine model with sequential quadratic pro- gramming （SQP）. Firstly, a steady-state hybrid aero-engine model is designed in the whole flight envelope with a dramatic enhancement of real-time capability. Secondly, the aero-engine performance seeking control including the maximum thrust mode and the minimum fuel-consumption mode is performed by SQP. Finally, digital simu- lations for cruise and accelerating flight are carried out. Results show that the proposed method improves real- time capability considerably with satisfactory effectiveness of optimization.展开更多
Power efficiency and link reliability are of great impor- tance in hierarchical wireless sensor networks （HWSNs）, espe- cially at the key level, which consists of sensor nodes located only one hop away from the sink...Power efficiency and link reliability are of great impor- tance in hierarchical wireless sensor networks （HWSNs）, espe- cially at the key level, which consists of sensor nodes located only one hop away from the sink node called OHS. The power and admission control problem in HWSNs is comsidered to improve its power efficiency and link reliability. This problem is modeled as a non-cooperative game in which the active OHSs are con- sidered as players. By applying a double-pricing scheme in the definition of OHSs＇ utility function, a Nash Equilibrium solution with network properties is derived. Besides, a distributed algorithm is also proposed to show the dynamic processes to achieve Nash Equilibrium. Finally, the simulation results demonstrate the effec- tiveness of the proposed algorithm.展开更多
随着电力系统中可再生能源比重逐渐增加,电力系统频率波动的风险增大。飞轮和锂电池可以优势互补,作为混合储能应用于电网一次调频中,有效解决系统频率波动问题。为了充分发挥飞轮和锂电池各自的调频优势,提出基于自适应荷电状态(state ...随着电力系统中可再生能源比重逐渐增加,电力系统频率波动的风险增大。飞轮和锂电池可以优势互补,作为混合储能应用于电网一次调频中,有效解决系统频率波动问题。为了充分发挥飞轮和锂电池各自的调频优势,提出基于自适应荷电状态(state of charge,SOC)的电池-飞轮混合储能一次调频控制策略。首先,建立含正、负虚拟惯性控制和虚拟下垂控制的权重分配一次调频模型;然后,利用飞轮和锂电池SOC对一次调频模型参数进行修正,提高混合储能在SOC阈值附近的一次调频能力;最后,仿真对比各调频场景下文中控制策略与其他控制策略的调频能力及SOC恢复效果。研究结果表明,文中控制策略下储能系统SOC波动范围最小,电池不会发生过充过放,且系统频率波动不超过±0.2 Hz,可以提高电网频率稳定性。展开更多
输电系统的暂态稳定性极易受到不确定参数和未知扰动的影响,而基于某一工作点的线性化模型的控制方法无法解决这些不确定因素带来的问题。因此,提出了一种晶闸管控制串联补偿装置TCSC(thyristor con-trolled series compensation)与发...输电系统的暂态稳定性极易受到不确定参数和未知扰动的影响,而基于某一工作点的线性化模型的控制方法无法解决这些不确定因素带来的问题。因此,提出了一种晶闸管控制串联补偿装置TCSC(thyristor con-trolled series compensation)与发电机励磁的自适应鲁棒协调控制方法,将自适应反步(adaptive backstepping)算法和L2增益控制相结合。首先对系统进行降阶;然后递推地构造每个子系统的耗散不等式,通过自适应律和子系统控制律的设计,让子系统满足耗散性,从而保证子系统的鲁棒扰动抑制能力;最后,对装设TCSC的单机无穷大输电系统模型故障情况进行仿真。结果表明,所设计的ARCC方法可以明显改善发电机功角和TCSC接入点电压的动态响应,从而提高电力输电系统的暂态稳定性。展开更多
文摘The purpose of this paper is the design of neural network-based adaptive sliding mode controller for uncertain unknown nonlinear systems. A special architecture adaptive neural network, with hyperbolic tangent activation functions, is used to emulate the equivalent and switching control terms of the classic sliding mode control （SMC）. Lyapunov stability theory is used to guarantee a uniform ultimate boundedness property for the tracking error, as well as of all other signals in the closed loop. In addition to keeping the stability and robustness properties of the SMC, the neural network-based adaptive sliding mode controller exhibits perfect rejection of faults arising during the system operating. Simulation studies are used to illustrate and clarify the theoretical results.
基金Supported by the Aeronautical Science Foundation of China(2010ZB52011)the Funding of Jiangsu Innovation Program for Graduate Education(CXLX11-0213)the Nanjing University of Aeronautics and Astronautics Research Funding(NS2010055)~~
文摘The real-time capability of integrated flight/propulsion optimal control （IFPOC） is studied. An appli- cation is proposed for IFPOC by combining the onboard hybrid aero-engine model with sequential quadratic pro- gramming （SQP）. Firstly, a steady-state hybrid aero-engine model is designed in the whole flight envelope with a dramatic enhancement of real-time capability. Secondly, the aero-engine performance seeking control including the maximum thrust mode and the minimum fuel-consumption mode is performed by SQP. Finally, digital simu- lations for cruise and accelerating flight are carried out. Results show that the proposed method improves real- time capability considerably with satisfactory effectiveness of optimization.
基金supported by the National Natural Science Foundation of China (7070102571071105)+2 种基金the Program for New Century Excellent Talents in Universities of China (NCET-08-0396)the National Science Fund for Distinguished Young Scholars of China (70925005)the Program for Changjiang Scholars and Innovative Research Team in University (IRT/028)
文摘Power efficiency and link reliability are of great impor- tance in hierarchical wireless sensor networks （HWSNs）, espe- cially at the key level, which consists of sensor nodes located only one hop away from the sink node called OHS. The power and admission control problem in HWSNs is comsidered to improve its power efficiency and link reliability. This problem is modeled as a non-cooperative game in which the active OHSs are con- sidered as players. By applying a double-pricing scheme in the definition of OHSs＇ utility function, a Nash Equilibrium solution with network properties is derived. Besides, a distributed algorithm is also proposed to show the dynamic processes to achieve Nash Equilibrium. Finally, the simulation results demonstrate the effec- tiveness of the proposed algorithm.
文摘随着电力系统中可再生能源比重逐渐增加,电力系统频率波动的风险增大。飞轮和锂电池可以优势互补,作为混合储能应用于电网一次调频中,有效解决系统频率波动问题。为了充分发挥飞轮和锂电池各自的调频优势,提出基于自适应荷电状态(state of charge,SOC)的电池-飞轮混合储能一次调频控制策略。首先,建立含正、负虚拟惯性控制和虚拟下垂控制的权重分配一次调频模型;然后,利用飞轮和锂电池SOC对一次调频模型参数进行修正,提高混合储能在SOC阈值附近的一次调频能力;最后,仿真对比各调频场景下文中控制策略与其他控制策略的调频能力及SOC恢复效果。研究结果表明,文中控制策略下储能系统SOC波动范围最小,电池不会发生过充过放,且系统频率波动不超过±0.2 Hz,可以提高电网频率稳定性。
文摘输电系统的暂态稳定性极易受到不确定参数和未知扰动的影响,而基于某一工作点的线性化模型的控制方法无法解决这些不确定因素带来的问题。因此,提出了一种晶闸管控制串联补偿装置TCSC(thyristor con-trolled series compensation)与发电机励磁的自适应鲁棒协调控制方法,将自适应反步(adaptive backstepping)算法和L2增益控制相结合。首先对系统进行降阶;然后递推地构造每个子系统的耗散不等式,通过自适应律和子系统控制律的设计,让子系统满足耗散性,从而保证子系统的鲁棒扰动抑制能力;最后,对装设TCSC的单机无穷大输电系统模型故障情况进行仿真。结果表明,所设计的ARCC方法可以明显改善发电机功角和TCSC接入点电压的动态响应,从而提高电力输电系统的暂态稳定性。
