Agent-based modeling of supply chains for distributed scheduling

This paper considers a supply chain that comprises multiple independent and autonomous enterprises (project managers) that seek and select various contractors to complete operations of their project. Both the project managers and contractors jointly determine the schedules of their operations while no single enterprise has complete information of other enterprises. The centralized scheduling approach that can usually obtain good global performance but must share nearly complete information that is difficult or even impractical due to the distributed nature of real-life supply chains. This paper proposes an agent-based supply chain model to support distributed scheduling. A modified contract-net protocol (MCNP) is proposed to enable more information sharing among the enterprises than conventional CNP. Experimental simulation studies are conducted to compare and contrast the performances of the centralized [centralized heuristic (CTR)], conventional CNP, and MNCP approaches. The results show that MCNP outperforms CNP and performs comparably with CTR when project complexity is high in terms of the total supply chain operating cost. Moreover, it is found that although CTR is better than MCNP in terms of global performance, MCNP yields good schedule stability when facing unexpected disturbances.     

An integrated approach for logistic and vendor managed inventory in supply chain

In this paper, a quaternary policy system towards integrated logistics and inventory aspect of the supply chain has been proposed. A system of multi retailers and distributors, with each distributor following a unique policy, will be analysed. The first policy is continuous time replenishment policy where the retailers’ inventory is replenished in every time interval. In the next three policies, inventory of the retailers will be replenished by some definite policy factors. The vendor managed inventory (VMI) system is used for updating the inventory of the retailers. An order-up-to policy (q, Q) is used for updating the inventory of distributors. Total erstwhile demands to the retailer will be used to determine the amount of inventory acclivity. Furthermore, the distributors will be sending the delivery vehicles to few fellow retailers who are shortlisted according to the policy, followed by the retailers and associated distributors. On the basis of random demand that the retailers are facing from end customers and the total demand that has incurred in the supply chain, products are unloaded to the selected retailers from the delivery vehicle. The path of the delivery vehicle is retrieved by dynamic ant colony optimization. In addition, a framework has been developed to measure the end-customer satisfaction level and total supply chain cost incorporating the inventory holding cost, ordering cost and the transportation cost. The framework has been numerically moulded with different settings to compare the performance of the quadruplet policies.     

机器人操作器的自适应模糊滑模控制器设计

针对机器人动力学系统提出了一种基于模糊逻辑的自适应模糊滑模控制方案.根据滑模控制原理并利用模糊系统的逼近能力设计控制器,基于李雅谱诺夫方法设计自适应律,证明了闭环模糊控制系统的稳定性和跟踪误差的收敛性.控制结构简单,不需要复杂的运算.该设计方案柔化了控制信号,减轻了一般滑模控制的抖振现象.仿真结果表明了所提控制策略的有效性.     

H controller design for pure delay and other distributed systems

In this paper we consider the design of a rational stabilizing controller for a weighted two-block H problem with a distributed plant, with emphasis on the case of a pure delay plant and first order weights. The optimal controller for such a problem is, in general, distributed and requires rational approximation. We propose a simple suboptimal design procedure, which is based on Pade approximation with two crucial modifications: (i) high frequency performance is modified using a first-order approximated inverse; (ii) an additional one-point interpolation condition is imposed to restore stability at a critical imaginary unstable pole. The design trade-offs are discussed, with an example.     

无人机吊挂空运系统的自适应控制设计

针对四旋翼无人机吊挂空运系统存在的模型不确定性及欠驱动性问题,本文提出了一种基于能量耦合的自适应控制设计.首先,基于能量整形控制方法构造了一种新型的能量存储函数以处理状态耦合.然后利用神经网络对系统未建模动态特性进行在线估计,同时设计参数自适应律在线估计模型中的未知参数,并采用基于符号函数的鲁棒控制算法补偿神经网络的估计误差.本文运用李雅普诺夫方法和拉塞尔不变性原理对闭环系统的稳定性进行了证明,并且证明了负载摆动和无人机位置误差的渐近收敛性.最后,在室内实验平台上进行了飞行实验.实验结果表明,本文提出的非线性控制方法能够在有效抑制吊挂负载摆动的同时,实现无人机位置的精确控制.     

TCSC 系统的自适应minimax 干扰抑制控制器设计

针对含有未知外部干扰和不确定参数的非线性晶闸管控制串联补偿器(TCSC) 系统, 提出一种L₂增益干扰抑制算法. 将minimax 方法引入耗散Hamilton 系统, 消除了不等式假设条件的约束; 构造检验函数, 推算出系统所能承受的最大干扰程度, 降低了传统干扰处理方法的保守性; 采用参数映射方法设计自适应律, 提高了参数跟踪效率. 最后通过机械功率和对地短路故障的仿真结果表明了所提出的控制方案能够有效改善系统的暂态性能.

     

A statistical tolerancing approach for design of synchronized supply chains

Supply chain (SC) can be visualized as a means to fulfilling the customer's requirement with the objective to maximize the overall value generated. With the rapid change of world economy, firms need to deploy alternative methodologies to improve the responsiveness of SC. In this regard, one important issue is the synchronization and co-ordination of supply chain network (SCN). In order to ensure the dispatch of finished product to the customer, with in customers specified delivery window, with a fierce high probability, the delivery performance of any SCN is to be minimized by forcing the work in the system. These requirements can be achieved by SC coordination, where timing of the actions performed by each of the business entities must be perfectly synchronized in SCN.This research is first of its kind where a probabilistic model is conceptualized to allocate the tolerances on lead times of internal business processes of a SCN. Various linear and nonlinear constraints have been considered with an end goal of minimizing the total cost of given network. In the proposed approach, synchronization among the members of SC has been achieved in the similar fashion as that of tolerance allocation on mechanical assemblies.The effectiveness of the proposed model is illustrated with a case study. The probabilistic model for ensuring synchronization shows much promise for improving the entire performance of network in terms of greater profit, speed, flexibility, quality, and product development etc., in a long run manufacturing enterprise.     

Developing distributed applications for integrated product and process design

A heterogeneous computing environment characterizes today's manufacturing situation. This is a stumbling block for the efficient implementation of manufacturing concepts such as integrated product and process design (IPPD). A computing environment for IPPD would require the seamless integration of the various product and process design software systems. The exchange of information between these systems should be efficient, compatible and synchronous. This article presents an approach for developing distributed manufacturing applications that are compatible and synchronized and thus, able to support IPPD. The approach involves the use of a common manufacturing application ‘middleware’, which is distributed between a central geometric modelling server and application clients. The portability of the middleware is ensured through the use of Java for code portability and XML for data portability. The compatible product model problem is solved through the use of common data structures developed using reusable application client classes. Efficient transfer of product data is proposed using compressed model information embedded in a product data XML schema. Synchronization of design changes among all applications is achieved through the creation of relationships on an Application Relationship Manager.     

Adaptive controller design for underwater snake robot with unmatched uncertainties

Because of hydrodynamic model error of the present dynamic model, there is a challenge in controller design for the underwater snake-like robot. To tackle this challenge, this paper proposes an adaptive control schemes based on dynamic model for a planar, underwater snake-like robot with model error and time-varying noise. The adaptive control schemes aim to achieve the adaptive control of joint angles tracking and the direction of locomotion control. First, through approximation and reducibility using Taylor expansion method, a simplified dynamics model of a planar amphibious snake-like robot is derived. Then, the L1 adaptive controller based on piecewise constant adaptive law is applied on the simplified planar, underwater snake-like robot, which can deal with both matched and unmatched nonlinear uncertainties. Finally, to control the direction of locomotion, an auxiliary bias signal is used as the control input to regulate the locomotion direction. Simulation results show that this L1 adaptive controller is valid to deal with different uncertainties and achieve the joint angles tracking and fast adaptive at the same time. The modified L1 adaptive controller, in which the auxiliary bias item is added, has the ability to change the direction of locomotion, that is, the orientation angle is periodic with arbitrarily given constant on average.     

Production-inventory system controller design and supply chain dynamics

The paper deals with the modelling and control of aggregated production-inventory systems as described by differential equations. Hitherto, research in the area has been characterized by the approximation of production delays by first-order lags rather than more realistic pure delays. We demonstrate the substantial qualitative differences between these two approaches and thus generate the motivation for the rest of the paper, which tackles pure delay systems. The application of some relatively new design methodologies for delay systems yields four design choices that are tested for their performance over a range of criteria including stability robustness. The investigation is then extended to the model of a supply chain comprising many such productioninventory systems. The mechanism by which disturbances can be transmitted along the supply chain causing disruption and incurring costs to other supply chain echelons is elucidated. A heuristic feedback policy designed adaptively to tune the individual system designs in response to such disturbances is presented.     

块控非线性系统自适应神经网络控制

针对一类含有非匹配不确定性的块控型多输入多输出非线性系统,提出一种基于反演技术和RBF神经网络的控制系统设计方案.通过引入一种改进型的Lyapunov函数,避免了控制矩阵未知情况下可能出现的奇异问题.在控制系统设计过程中,充分应用鲁棒自适应控制技术,解决了多输入多输出结构不确定性所带来的设计难题,得到了系统所有状态量将全局指数收敛至原点附近一个邻域的结论.最后的仿真结果表明了设计方案的正确性.     

The design of distributed suboptimal controller for multi‐agent systems

In this paper, the design of the distributed suboptimal controller for discrete‐time multi‐agent systems is considered. The distributed controllers, which only use the state information of itself and the relative states of its neighbors, are designed based on the topological structure of the system. The suboptimal feedback gain matrices of the distributed controllers are presented by using the ‘averaged’ optimization approach. It is showed that the distributed suboptimal controller is existent and unique. The design method of the distributed controller is obtained by the iteration procedure step by step. An example is given as an illustration of the proposed results. Copyright © 2014 John Wiley & Sons, Ltd.     

Adaptive backstepping controller design using stochastic small-gain theorem

A more general class of stochastic nonlinear systems with unmodeled dynamics and uncertain nonlinear functions are considered in this paper. With the concept of input-to-state practical stability (ISpS) and nonlinear small-gain theorem being extended to stochastic case, by combining stochastic small-gain theorem with backstepping design technique, an adaptive output-feedback controller is proposed. It is shown that the closed-loop system is practically stable in probability. A simulation example demonstrates the control scheme.     

开关电源PSO-LQR控制器设计与研究

本文以开关电源为控制对象,并提出了基于PSO的开关电源LQR控制器的设计.首先,利用现代控制理论建立了开关电源的状态空间模型,而后采用粒子群算法对开关电源LQR控制器加权矩阵进行了优化,以保证该电源能够为用户的精确地提供所需的电源.仿真结果表明,该课题所采用的方法能够满足系统输出快速响应的要求,各项指标优于传统方法所得到的结果.     

Modelling and controller design for distributed parameter systems via residence time distribution

For chemical reactors with non-linear fluid dynamics, a linear model realisation is proposed. The inputs are the ingoing concentration of a certain component in the fluid, and the reaction rate. The output is the outgoing concentration. The realisation makes use of a first-order reaction equation, and the residence time distribution of the fluid particles inside the reactor. Also dead time is incorporated in the modelling. The method is tested on two non-linear models for which the residence time distributions are known analytically. The first model is a series of mixed tanks, and it is shown by simulation that the method gives an accurate approximation of the original model. The second model is a UV disinfection reactor, which has a dead time. For this model, the residence time distribution is first fitted by a form that is suitable for our realisation method. Simulations show that for realistic disturbances a high-performance linear controller can be designed. After that, the residence time distribution of a real life UV reactor (for which we have no model) is fitted by a suitable form. The fit is of the same quality as for the UV reactor model. This indicates that also for the real life UV reactor a high-performance controller can be designed.     

A computational study for common network design in multi-commodity supply chains

In this paper, we study a supply chain network design problem which consists of one external supplier, a set of potential distribution centers, and a set of retailers, each of which is faced with uncertain demands for multiple commodities. The demand of each retailer is fulfilled by a single distribution center for all commodities. The goal is to minimize the system-wide cost including location, transportation, and inventory costs. We propose a general nonlinear integer programming model for the problem and present a cutting plane approach based on polymatroid inequalities to solve the model. Randomly generated instances for two special cases of our model, i.e., the single-sourcing UPL&TAP and the single-sourcing multi-commodity location-inventory model, are provided to test our algorithm. Computational results show that the proposed algorithm can solve moderate-sized problem instances efficiently.     

Robust distributed controller design of rotational single-link smart materials beam

A dynamic modelling and controller design were presented for a single-link smart materials beam, a flexible beam bonded with piezoelectric actuators and sensors for better control performance. Taking into account bounded disturbances, a robust distributed controller was constructed based on the system model, which was described by a set of partial differential equations (PDEs) and boundary conditions (BCs) . Subsequently, a finite dimensional controller was further developed, and it was proven that this controller can stabilize the finite dimensional model with arbitrary number of flexible modes.     

An integrated approach to the design and operation for spare parts logistic systems

This paper attempts to solve a comprehensive design problem for a spare part logistic system. The design factors encompass logistic network design, part vendor selection, and transportation modes selection. Two approaches to solve the problem were proposed. In Approach 1, we simultaneously considered all the design factors and proposed two algorithms (SGA-1 and TGA-1). In Approach 2, the design problem was solved in two stages. Firstly, we aimed to find a near-optimal logistic network. Secondly, with the obtained logistic network, we proposed three algorithms (SGA-2, TGA-2, and NN-GA-Tabu) to find optimal combinations for part vendor and transportation modes selection. Numerical experiments indicate that Approach 2 outperforms Approach 1, and the NN-GA-Tabu outperforms all the other four algorithms. The proposed NN-GA-Tabu might also be a good solution architecture for solving other comprehensive space search problems.     

An integrated supply chain network design problem for bidirectional flows

Coordination among supply chains has elicited considerable attention in both academia and industry. This paper investigates an integrated supply chain network design problem that involves the determination of the locations for distribution centers and the assignment of customers and suppliers to the corresponding distribution centers. The problem simultaneously involves the distribution of products from the manufacturer to the customers and the collection of components from the suppliers to the manufacturer via cross-docking at distribution centers. The co-location of different types of distribution centers and coordinated transportation are introduced to achieve cost savings. A Lagrangian relaxation-based algorithm is then developed. Extensive computational experiments show that the proposed algorithm has stable performance and outperforms CPLEX for large-scale problems. An industrial case study is considered and sensitivity analysis is conducted to explore managerial insights. Finally, conclusions are drawn, and future research directions are outlined.