科创中国

As a promising technique, surrogate-based design and optimization(SBDO) has been widely used in modern engineering design optimizations. Currently, static surrogate-based optimization methods have been successfully applied to expensive optimization problems. However, due to the low efficiency and poor flexibility, static surrogate-based optimization methods are difficult to efficiently solve practical engineering cases. At the aim of enhancing efficiency, a novel surrogate-based efficient optimization method is developed by using sequential radial basis function(SEO-SRBF). Moreover, augmented Lagrangian multiplier method is adopted to solve the problems involving expensive constraints. In order to study the performance of SEO-SRBF, several numerical benchmark functions and engineering problems are solved by SEO-SRBF and other well-known surrogate-based optimization methods including EGO, MPS, and IARSM. The optimal solutions, number of function evaluations, and algorithm execution time are recorded for comparison. The comparison results demonstrate that SEO-SRBF shows satisfactory performance in both optimization efficiency and global convergence capability. The CPU time required for running SEO-SRBF is dramatically less than that of other algorithms. In the torque arm optimization case using FEA simulation, SEO-SRBF further reduces 21% of the material volume compared with the solution from static-RBF subject to the stress constraint. This study provides the efficient strategy to solve expensive constrained optimization problems.

Epidemic算法在某些场景中具有很高的传输成功率、很小的传输延迟,但其适应性较差,在另一些场景中性能会显著下降.分析了影响Epidemic算法性能的因素,认为挤出效应是导致算法性能下降的主要原因;提出了Adaptive机制,其使节点可以根据周围节点缓存的状况调整注入网络数据包的数量,主动地抑制挤出效应的发生,进而改善Epidemic算法性能.仿真结果表明,改进后算法的传输成功率显著提高,路由开销大幅度下降.

For the Cooperative Adaptive Cruise Control(CACC)Algorithm,existing research studies mainly focus on how inter-vehicle communication can be used to develop CACC controller,the influence of the communication delays and lags of the actuators to the string stability.However,whether the string stability can be guaranteed when inter-vehicle communication is invalid partially has hardly been considered.This paper presents an improved CACC algorithm based on the sliding mode control theory and analyses the range of CACC controller parameters to maintain string stability.A dynamic model of vehicle spacing deviation in a platoon is then established,and the string stability conditions under improved CACC are analyzed.Unlike the traditional CACC algorithms,the proposed algorithm can ensure the functionality of the CACC system even if inter-vehicle communication is partially invalid.Finally,this paper establishes a platoon of five vehicles to simulate the improved CACC algorithm in MATLAB/Simulink,and the simulation results demonstrate that the improved CACC algorithm can maintain the string stability of a CACC platoon through adjusting the controller parameters and enlarging the spacing to prevent accidents.With guaranteed string stability,the proposed CACC algorithm can prevent oscillation of vehicle spacing and reduce chain collision accidents under real-world circumstances.This research proposes an improved CACC algorithm,which can guarantee the string stability when inter-vehicle communication is invalid.

Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation(RLSE) to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This paper constructs an adaptive robust controller which can compensate the friction force in the cylinder.

Cyber physical systems(CPS)recently emerge as a new technology which can provide promising approaches to demand side management(DSM),an important capability in industrial power systems.Meanwhile,the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics.DSM,integrated with CPS,is an effective methodology for solving energy optimization problems in manufacturing center.This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems.To gain prior knowledge of DSM operating results,a sparse Bayesian learning based componential forecasting method is introduced to predict24-hour electric load levels for specific industrial areas in China.From this data,a pricing strategy is designed based on short-term load forecasting results.To minimize total energy costs while guaranteeing manufacturing center service quality,an adaptive demand side energy optimization algorithm is presented.The proposed scheme is tested in a machining center energy optimization experiment.An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center.Based on the data collected from the sensing system,the load prediction-based energy optimization scheme is implemented.By employing both the PSO and the CPSO method,the problem of DSM in the manufacturing center is solved.The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5%compared with the traditional PSO optimization method.

语境顺应模型是一种能够顺应多种环境的语言课程评价模式.由于该模型结合实证主义和自然主义的评价范式,将抽象的评价概念具体为可以操纵的评价活动,从而使该模型具有控制性、过程性和动态性以及系统性、开放性和循环性的特点.为了解决传统听评课过程中的去专业化倾向,本文以高中英语听评课为例,详细介绍语境顺应模型在听评课实践活动中的方法和步骤,尝试从专业化的角度分析考察听评课范式转型的可行性和可操作性,为英语课程评价提供可借鉴的范式和模型.

创造性破坏的价值源于创新的成功商业化.此过程中所出现的技术更替、企业重组、战略联盟等行为都是围绕着价值链而展开.本文试图在价值链视角下,深入分析创造性破坏过程的价值生成条件和生成机理.通过讨论不同的价值链治理模式对创造性破坏过程产生的影响,给出价值链治理模式的选择模型,以求对创造性破坏过程有一个更加透彻的认知.