Position Errors and Interference Prediction-Based Trajectory Tracking for Snake Robots

This work presents a trajectory tracking control method for snake robots.This method eliminates the influence of time-varying interferences on the body and reduces the offset error of a robot with a predetermined trajectory.The optimized line-of-sight(LOS)guidance strategy drives the robot’s steering angle to maintain its anti-sideslip ability by predicting position errors and interferences.Then,the predictions of system parameters and viscous friction coefficients can compensate for the joint torque control input.The compensation is adopted to enhance the compatibility of a robot within ever-changing environments.Simulation and experimental outcomes show that our work can decrease the fluctuation peak of the tracking errors,reduce adjustment time,and improve accuracy.

Manufacturing task data chain-driven production logistics trajectory analysis and optimization decision making method

Production logistics(PL)is considered as a critical factor that affects the efficiency and cost of production operations in discrete manufacturing systems.To effectively utilize manufacturing big data to improve PL efficiency and promote job shop floor economic benefits,this study proposes a PL trajectory analysis and optimization decision making method driven by a manufacturing task data chain(MTDC).First,the manufacturing task chain(MTC)is defined to characterize the discrete production process of a product.To handle manufacturing big data,the MTC data paradigm is designed,and the MTDC is established.Then,the logistics trajectory model is presented,where the various types of logistics trajectories are extracted using the MTC as the search engine for the MTDC.Based on this,a logistics efficiency evaluation indicator system is proposed to support the optimization decision making for the PL.Finally,a case study is applied to verify the proposed method,and the method determines the PL optimization decisions for PL efficiency without changing the layout and workshop equipment,which can assist managers in implementing the optimization decisions.

实现铁路货运跨越式发展相关建议

铁路货物运输实现跨栽式发展,必须在建设方面实现思想观念领先,快速化、规模化、信息化建设同步进行。

Stochastic Programming Model for Discrete Lotsizing and Scheduling Problem on Parallel Machines

In recent years, it has been difficult for manufactures and suppliers to forecast demand from a market for a given product precisely. Therefore, it has become important for them to cope with fluctuations in demand. From this viewpoint, the problem of planning or scheduling in production systems can be regarded as a mathematical problem with stochastic elements. However, in many previous studies, such problems are formulated without stochastic factors, treating stochastic elements as deterministic variables or parameters. Stochastic programming incorporates such factors into the mathematical formulation. In the present paper, we consider a multi-product, discrete, lotsizing and scheduling problem on parallel machines with stochastic demands. Under certain assumptions, this problem can be formulated as a stochastic integer programming problem. We attempt to solve this problem by a scenario aggregation method proposed by Rockafellar and Wets. The results from computational experiments suggest that our approach is able to solve large-scale problems, and that, under the condition of uncertainty, incorporating stochastic elements into the model gives better results than formulating the problem as a deterministic model.

Wolfe-Type Duality for Mathematical Programs with Equilibrium Constraints

This paper considers the mathematical programs with equilibrium constraints(MPEC).It is well-known that,due to the existence of equilibrium constraints,the Mangasarian-Fromovitz constraint qualification does not hold at any feasible point of MPEC and hence,in general,the developed numerical algorithms for standard nonlinear programming problems can not be applied to solve MPEC directly.During the past two decades,much research has been done to develop numerical algorithms and study optimality,stability,and sensitivity for MPEC.However,there are very few results on duality for MPEC in the literature.In this paper,we present a Wolfe-type duality for MPEC and,under some suitable conditions,we establish various duality theorems such as the weak duality,direct duality,converse duality,and strict converse duality theorems.We further show that a linear MPEC is equivalent to a linear programming problem in some sense.

On Iteration Complexity of a First-Order Primal-Dual Method for Nonlinear Convex Cone Programming

Nonlinear convex cone programming(NCCP)models have found many practical applications.In this paper,we introduce a flexible first-order primal-dual algorithm,called the variant auxiliary problem principle(VAPP),for solving NCCP problems when the objective function and constraints are convex but may be nonsmooth.At each iteration,VAPP generates a nonlinear approximation of the primal augmented Lagrangian model.The approximation incorporates both linearization and a distance-like proximal term,and then the iterations of VAPP are shown to possess a decomposition property for NCCP.Motivated by recent applications in big data analytics,there has been a growing interest in the convergence rate analysis of algorithms with parallel computing capabilities for large scale optimization problems.We establish O(1/t)convergence rate towards primal optimality,feasibility and dual optimality.By adaptively setting parameters at different iterations,we show an O(1/t2)rate for the strongly convex case.Finally,we discuss some issues in the implementation of VAPP.

Governance of social responsibility in international infrastructure megaprojects

1 Introduction Megaprojects are a critical aspect of socio-economic development that can have huge effects on local communities,the environment,society,politics,or locals9 way of life(Zeng et al.,2015;Denicol et al.,2020).Megaproject social responsibility(MSR)refers to “the policies and practices of stakeholders through the whole project lifecycle that reflect responsibilities for the well-being of the wide society”(Zeng et al.,2015).MSR governance refers to socially responsible actions of relevant stakeholders to alleviate and eliminate a megaprojecfs negative effects on socio-economic and environmental outcomes during the megaprojecfs entire lifecycle(Lin et al.,2017;Ma et al.,2017).

以简单方式管理复杂项目

当规划一个涉及超过15个国家和地区的CEO、副总裁、执行董事，不同的全球重要客户经理，没有说明书的未知计算机系统和不满意的重要客户的项目时，人们也许立即会考虑使用某些十分复杂的项目管理工具。同时，管理层可能决定雇佣行业和职能经验丰富的资深经理作为项目经理，来增加获得较好结果的机会。而本文介绍了一个在实践中可行的简单方法。