Sensor scheduling is essential to collaborative target tracking in wireless sensor networks （WSNs）. In the existing works for target tracking in WSNs, such as the information-driven sensor query （IDSQ）, the taskin...Sensor scheduling is essential to collaborative target tracking in wireless sensor networks （WSNs）. In the existing works for target tracking in WSNs, such as the information-driven sensor query （IDSQ）, the tasking sensors are scheduled to maximize the information gain while minimizing the resource cost based on the uniform sampling intervals, ignoring the changing of the target dynamics and the specific desirable tracking goals. This paper proposes a novel energy-efficient adaptive sensor scheduling approach that jointly selects tasking sensors and determines their associated sampling intervals according to the predicted tracking accuracy and tracking energy cost. At each time step, the sensors are scheduled in alternative tracking mode, namely, the fast tracking mode with smallest sampling interval or the tracking maintenance mode with larger sampling interval, according to a specified tracking error threshold. The approach employs an extended Kalman filter （EKF）-based estimation technique to predict the tracking accuracy and adopts an energy consumption model to predict the energy cost. Simulation results demonstrate that, compared to a non-adaptive sensor scheduling approach, the proposed approach can save energy cost significantly without degrading the tracking accuracy.展开更多
本文针对无人车在复杂工况下,非线性程度增加和动力学约束导致的轨迹跟踪控制精度差和求解效率低的问题,提出一种高效的非线性模型预测控制(nonlinear model predictive control,NMPC)算法。首先考虑车辆模型的非线性因素,建立动力学和...本文针对无人车在复杂工况下,非线性程度增加和动力学约束导致的轨迹跟踪控制精度差和求解效率低的问题,提出一种高效的非线性模型预测控制(nonlinear model predictive control,NMPC)算法。首先考虑车辆模型的非线性因素,建立动力学和魔术轮胎模型,并将无人车终端状态整合到性能指标中,添加稳定性范围内多约束条件,通过障碍罚函数法处理非线性不等式约束,保证了求解过程的平滑性。然后为减轻求解非线性优化问题带来的计算负担,提出了一种新颖的连续/广义最小残差算法(improved continuation/generalized minimal residual,improved-C/GMRES),与传统的C/GMRES算法相比,通过引入连续增加的惩罚因子加快了数值计算的求解效率,降低算法的计算负担。最后通过Simulink和CarSim的联合仿真,在双移线工况和蛇行工况条件下验证跟踪精度和求解效率,结果表明与传统的C/GMRES方法相比,所提控制方法明显提升轨迹跟踪的控制精度和改善行驶稳定性,并加快数值求解效率。展开更多
This work deals with the estimation of solar radiation through a solar tracker aimed at evaluating the effect of solar tracking on the solar deposit in Burkina Faso. Using a two-axis solar tracking system, we experime...This work deals with the estimation of solar radiation through a solar tracker aimed at evaluating the effect of solar tracking on the solar deposit in Burkina Faso. Using a two-axis solar tracking system, we experimentally measured solar radiation at our Joseph KI-ZERBO University site and compared it with that obtained by a numerical simulation run using Fortran programming software based on a mathematical model by Brichambaut. The results obtained from the mathematical and experimental studies show that, with a solar tracker, on a clear-sky day, solar irradiation is between 800 W·m−2 and 1000 W·m−2 between about 8 a.m. and 4 p.m., i.e. a duration of 8 hours of insolation. Analysis of the numerical and experimental results shows very good quantitative and qualitative agreement, with an average relative error of 18%.展开更多
基金partly supported by the Agency for Science,Technology and Research(A*Star)SERC(No.0521010037,0521210082)
文摘Sensor scheduling is essential to collaborative target tracking in wireless sensor networks （WSNs）. In the existing works for target tracking in WSNs, such as the information-driven sensor query （IDSQ）, the tasking sensors are scheduled to maximize the information gain while minimizing the resource cost based on the uniform sampling intervals, ignoring the changing of the target dynamics and the specific desirable tracking goals. This paper proposes a novel energy-efficient adaptive sensor scheduling approach that jointly selects tasking sensors and determines their associated sampling intervals according to the predicted tracking accuracy and tracking energy cost. At each time step, the sensors are scheduled in alternative tracking mode, namely, the fast tracking mode with smallest sampling interval or the tracking maintenance mode with larger sampling interval, according to a specified tracking error threshold. The approach employs an extended Kalman filter （EKF）-based estimation technique to predict the tracking accuracy and adopts an energy consumption model to predict the energy cost. Simulation results demonstrate that, compared to a non-adaptive sensor scheduling approach, the proposed approach can save energy cost significantly without degrading the tracking accuracy.
文摘This work deals with the estimation of solar radiation through a solar tracker aimed at evaluating the effect of solar tracking on the solar deposit in Burkina Faso. Using a two-axis solar tracking system, we experimentally measured solar radiation at our Joseph KI-ZERBO University site and compared it with that obtained by a numerical simulation run using Fortran programming software based on a mathematical model by Brichambaut. The results obtained from the mathematical and experimental studies show that, with a solar tracker, on a clear-sky day, solar irradiation is between 800 W·m−2 and 1000 W·m−2 between about 8 a.m. and 4 p.m., i.e. a duration of 8 hours of insolation. Analysis of the numerical and experimental results shows very good quantitative and qualitative agreement, with an average relative error of 18%.
