Methods of vendor managed inventory control in supply chain management

By inducing the typical inventory control problem - the bullwhip effect, this paper presents vendor managed inventory (VMI) control methods on the basis of traditional methods of inventory management methods, constructs a VMI mathematics model, and analyzes the influence of VMI on inventory cost and channel profit. Finally, a special case is studied to verify that VMI is an effective supply chain strategy that can not only increase channel profit of supplier and customer but also improve full channel coordination, thereby reducing the bullwhip effect.

Impact of Capacity Parameters on Flexible Inventory Control Decision Model

From the mathematical point of view,the flexible inventory control model is proved in the practical problem application and the rationality of the capacity parameter selection and calculation.The purpose is to actively respond to demand fluctuations when there is a demand forecast error or a missing part of the demand information,and to avoid the risk of passive variable demand forecasting to set the immutable inventory capacity.At the same time,the game is controlled by the flexible and variable inventory control strategy and the customer’s willingness to demand.The paper mainly studies the influence of the setting of capacity parameters on the booking-limit decision and its benefits under the control of flexible space with variable total capacity.Through the two trends of capacity increase flexibility and capacity reduction flexibility in the flexible inventory control model,the mathematical performance and marginal utility methods are introduced to change the performance of the booking-limit control decision model under different scenarios.The correlation analysis between the capacity limit level and the return under the optimal Bookinglimit decision,and the above two flexibility parameters are obtained.

A Tutorial on Quantized Feedback Control

In this tutorial paper, we explore the field of quantized feedback control, which has gained significant attention due to the growing prevalence of networked control systems. These systems require the transmission of feedback information, such as measurements and control signals, over digital networks, presenting novel challenges in estimation and control design. Our examination encompasses various topics, including the minimal information needed for effective feedback control, the design of quantizers, strategies for quantized control design and estimation,achieving consensus control with quantized data, and the pursuit of high-precision tracking using quantized measurements.

Distributed Order-Up-To Inventory Control in Networked Supply Systems With Delay

In this work, the dynamics of networked goods distribution systems subject to the control of a continuous-review order-up-to inventory policy are investigated. In the analytical study, as opposed to the earlier models constrained to the serial and arborescent interconnection structures, an arbitrary multiechelon topology is considered. This external, uncertain demand,following any distribution, may be imposed on all network nodes,not just conveniently selected contact points. As in the physical systems, stock relocation to refill the reserves is subject to nonnegligible delay, which poses a severe stability threat and may lead to cost-inefficient decisions. A state-space model is created and used as the framework for analyzing system properties. In particular, it is formally demonstrated that despite unpredictable demand fluctuations, a feasible(nonnegative and bounded)reserves replenishment signal is generated at all times, and the stock gathered at the nodes does not surpass a finite, precisely determined level. The theoretical content is illustrated with a case study of the Chinese oil supply system.

Inventory control model based on external and interior reverse logistics

To improve the inventory control strategy for enterprise and optimize inventory control parameters of existing external and interior reverse logistics, a multi-resource inventory control model is proposed to better simulate the logistics fact, which is aimed at periodic inventory checking and pull mode of inventory control strategy, based on the return product arrival time obeying Poisson distribution, the return product employing lotsize process and the nonzero lead time of manufaeturinge/remanufacturing. The rational cost function with multiple constraints is employed to describe the inventory model. The genetic algorithm is employed to solve the inventory cost function to obtain the optimal solution of inventory checking periods, safe inventory point, product lot-sizes and process lot-sizes of return product. An example is presented to prove the feasibility and validity of the proposed method. Moreover, the influence of manufacturing/remanufacturing lead time and reuse rate of return production on the inventory control strategy of enterprise is analyzed.

Seat inventory control methods for Chinese passenger railways

Railway seat inventory control strategies play a crucial role in the growth of profit and train load factor. The railway passenger seat inventory control problem in China was addressed. Chinese passenger railway operation features and seat inventory control practice were analyzed firstly. A dynamic demand forecasting method was introduced to forecast the coming demand in a ticket booking period. By clustering, passengers' historical ticket bookings were used to forecast the demand to come in a ticket booking period with least squares support vector machine. Three seat inventory control methods: non-nested booking limits, nested booking limits and bid-price control, were modeled under a single-fare class. Different seat inventory control methods were compared with the same demand based on ticket booking data of Train T15 from Beijing West to Guangzhou. The result shows that the dynamic non-nested booking limits control method performs the best, which gives railway operators evidence to adjust the remaining capacity in a ticket booking period.

Modeling and Simulation of Equipment Material Inventory Control Based on System Dynamics

The paper discusses how the inventory control of army equipment material runs sytematically under the two-level maintenance system,and establishes the inventory control model based on system dynamics.On the basis of modeling and simulation,the influence of different inventory upper limit on the whole system is studied,and the optimal inventory control mechanism under the model condition is foud.In addition,through the simulation of two replenishment strategies(s,S) and(T,s,S),the advantages and disadvantages and feasibility of each replenishment strategy are analyzed.

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

Optimal Multiperiodic Control for Inventory Coupled Systems: A Multifrequency Second-Order Test

A complex autonomous inventory coupled system is considered. It can take, for example, the form of a network of chemical or biochemical reactors, where the inventory interactions perform the recycling of by-products between the subsystems. Because of the flexible subsystems interactions, each of them can be operated with their own periods utilizing advantageously their dynamic properties. A multifrequency second-order test generalizing the p-test for single systems is described. It can be used to decide which kind of the operation (the static one, the periodic one or the multiperiodic one) will intensify the productivity of a complex system. An illustrative example of the multiperiodic optimization of a complex chemical production system is presented.

Unique influences of reboiler inventory control on the operation of totally reboiled reactive distillation columns

In this work,the dynamics and operation of the totally reboiled reactive distillation columns are visualized in terms of transfer function based process models.This kind of processes is found to be characterized by underdamped step responses due to the special topological configuration and the intricate interplay between the reaction operation and the separation operation involved.The under-dampness can be substantially alleviated through the tight inventory control of bottom reboiler and this presents beneficial effects to process dynamics and operation.Two totally reboiled reactive distillation columns,separating,respectively,a hypothetical synthesis reaction from reactants A and B to product C,and a real decomposition reaction from 1,4-butanediol to tetrahydrofuran and water,are employed to demonstrate these uncommon behaviors.The results obtained give full support to the above qualitative interpretation.Despite the strong influences of reaction kinetics and thermodynamic properties of the reacting mixtures,the totally reboiled reactive distillation columns are generally considered to present such unique behaviors and require tight inventory control of bottom reboiler to facilitate their control system development.

Study on Inventory Cost Control under JIT System

Traditional inventory control methods generally emphasize minimizing costs. Under current thinking, we not only consider cost control, but also tie inventory management directly into production scheduling. This system, called ＂Just-in-Time delivery＂, is based on having inventory arrive at the factory door just as it is needed on the assembly line. This inventory management technique of essential zero raw material inventory speeds inventory turnover rate and greatly reduces holding cost. This paper analyzes and compares all aspects related to both traditional and JIT systems, and explores ways of reducing inventory costs. The result is the elimination of waste, the speed-up of inventory turnover and the increase in productivity, all with the objective of maximizing profitability. Using advanced logistics （physical distribution methods） will enhance the business image, strengthen international competitive ability and contribute greatly to increase gross domestic product.

Inventory control techniques in medical stores of a tertiary care neuropsychiatry hospital in Delhi

Approximately 35.0% of annual hospitals budget is spent on buying materials and supplies, including medicines. We can bring about substantial improvement in the hospital inventory and expenditures by the inventory control techniques. Objective: To identify the categories of drugs which need stringent management control. Material and Method: The ABC and VED analysis of the medical store of a Neuropsychiatry hospital at Delhi, India was conducted for the year 2008-2009 to identify the categories of items needing stringent management control. Results: The total number of the drugs at the medical store was 145 drugs. The total annual drug expenditure (ADE) on these drug items was Rs. 19219594.79. ABC analysis revealed 3.45%, 6.9% and 89.65% items as A, B and C category items, respectively, accounting for 70.5%, 19.68% and 9.83% of ADE of the medical store. VED analysis showed 32.41%, 61.38% and 6.2% items as V, E, and D category items, respectively, accounting for 70.9%, 28.72% and 0.38% of ADE of the medical store. On ABC-VED matrix analysis, 33.8%, 60% and 6.2% items were found to be category I, II and III items, respectively, accounting for 92.33%, 7.29% and 0.38% of ADE of the medical store. Conclusion: It is suggested by the study that the management of Category I drugs should be done by the top management resulting in stringent control on the annual expenses. The Category II should be managed by the middle management level and Category III at lower managerial level.

Finite-time Prescribed Performance Time-Varying Formation Control for Second-Order Multi-Agent Systems With Non-Strict Feedback Based on a Neural Network Observer

This paper studies the problem of time-varying formation control with finite-time prescribed performance for nonstrict feedback second-order multi-agent systems with unmeasured states and unknown nonlinearities.To eliminate nonlinearities,neural networks are applied to approximate the inherent dynamics of the system.In addition,due to the limitations of the actual working conditions,each follower agent can only obtain the locally measurable partial state information of the leader agent.To address this problem,a neural network state observer based on the leader state information is designed.Then,a finite-time prescribed performance adaptive output feedback control strategy is proposed by restricting the sliding mode surface to a prescribed region,which ensures that the closed-loop system has practical finite-time stability and that formation errors of the multi-agent systems converge to the prescribed performance bound in finite time.Finally,a numerical simulation is provided to demonstrate the practicality and effectiveness of the developed algorithm.

Adaptive Control of a Production-Inventory Model with Uncertain Deterioration Rate

This paper studied a continuous-time model of a production maintenance system in which a manufacturing firm produces a single product selling some and stocking the remaining. The problem of adaptive control of a production-maintenance system with unknown deterioration has been presented. Using Liapunov technique, the production rate and updating rule of deterioration rate are derived as non-linear functions of inventory level perturbation. Numerical analysis for the system has been presented for a set of parameter values and demand rate.

Risk-Informed Model-Free Safe Control of Linear Parameter-Varying Systems

This paper presents a risk-informed data-driven safe control design approach for a class of stochastic uncertain nonlinear discrete-time systems.The nonlinear system is modeled using linear parameter-varying(LPV)systems.A model-based probabilistic safe controller is first designed to guarantee probabilisticλ-contractivity(i.e.,stability and invariance)of the LPV system with respect to a given polyhedral safe set.To obviate the requirement of knowing the LPV system model and to bypass identifying its open-loop model,its closed-loop data-based representation is provided in terms of state and scheduling data as well as a decision variable.It is shown that the variance of the closedloop system,as well as the probability of safety satisfaction,depends on the decision variable and the noise covariance.A minimum-variance direct data-driven gain-scheduling safe control design approach is presented next by designing the decision variable such that all possible closed-loop system realizations satisfy safety with the highest confidence level.This minimum-variance approach is a control-oriented learning method since it minimizes the variance of the state of the closed-loop system with respect to the safe set,and thus minimizes the risk of safety violation.Unlike the certainty-equivalent approach that results in a risk-neutral control design,the minimum-variance method leads to a risk-averse control design.It is shown that the presented direct risk-averse learning approach requires weaker data richness conditions than existing indirect learning methods based on system identification and can lead to a lower risk of safety violation.Two simulation examples along with an experimental validation on an autonomous vehicle are provided to show the effectiveness of the presented approach.

Quantization and Event-Triggered Policy Design for Encrypted Networked Control

This paper proposes a novel event-driven encrypted control framework for linear networked control systems(NCSs),which relies on two modified uniform quantization policies,the Paillier cryptosystem,and an event-triggered strategy.Due to the fact that only integers can work in the Pailler cryptosystem,both the real-valued control gain and system state need to be first quantized before encryption.This is dramatically different from the existing quantized control methods,where only the quantization of a single value,e.g.,the control input or the system state,is considered.To handle this issue,static and dynamic quantization policies are presented,which achieve the desired integer conversions and guarantee asymptotic convergence of the quantized system state to the equilibrium.Then,the quantized system state is encrypted and sent to the controller when the triggering condition,specified by a state-based event-triggered strategy,is satisfied.By doing so,not only the security and confidentiality of data transmitted over the communication network are protected,but also the ciphertext expansion phenomenon can be relieved.Additionally,by tactfully designing the quantization sensitivities and triggering error,the proposed event-driven encrypted control framework ensures the asymptotic stability of the overall closedloop system.Finally,a simulation example of the secure motion control for an inverted pendulum cart system is presented to evaluate the effectiveness of the theoretical results.

Practical Prescribed Time Tracking Control With Bounded Time-Varying Gain Under Non-Vanishing Uncertainties

This paper investigates the prescribed-time control(PTC) problem for a class of strict-feedback systems subject to non-vanishing uncertainties. The coexistence of mismatched uncertainties and non-vanishing disturbances makes PTC synthesis nontrivial. In this work, a control method that does not involve infinite time-varying gain is proposed, leading to a practical and global prescribed time tracking control solution for the strict-feedback systems, in spite of both the mismatched and nonvanishing uncertainties. Different from methods based on control switching to avoid the issue of infinite control gain that involves control discontinuity at the switching point, in our method a softening unit is exclusively included to ensure the continuity of the control action. Furthermore, in contrast to most existing prescribed-time control works where the control scheme is only valid on a finite time interval, in this work, the proposed control scheme is valid on the entire time interval. In addition, the prior information on the upper or lower bound of gi is not in need,enlarging the applicability of the proposed method. Both the theoretical analysis and numerical simulation confirm the effectiveness of the proposed control algorithm.

Review of Field Weakening Control Strategies of Permanent Magnet Synchronous Motors

Due to high power density,high efficiency,and accurate control performance,permanent magnet synchronous motors(PMSMs)have been widely adopted in equipment manufacturing and energy transformation fields.To expand the speed range under finite DC-bus voltage,extensive research on field weakening(FW)control strategies has been conducted.This paper summarizes the major FW control strategies of PMSMs,which are categorized into calculation-based methods,voltage closed-loop control methods,and model predictive control related methods.The existing strategies are analyzed and compared according to performance,robustness,and execution difficulty,which can facilitate the implementation of FW control.

Command filtered integrated estimation guidance and control for strapdown missiles with circular field of view

In this paper,an integrated estimation guidance and control(IEGC)system is designed based on the command filtered backstepping approach for circular field-of-view(FOV)strapdown missiles.The threedimensional integrated estimation guidance and control nonlinear model with limited actuator deflection angle is established considering the seeker's FOV constraint.The boundary time-varying integral barrier Lyapunov function(IBLF)is employed in backstepping design to constrain the body line-of-sight(BLOS)in IEGC system to fit a circular FOV.Then,the nonlinear adaptive controller is designed to estimate the changing aerodynamic parameters.The generalized extended state observer(GESO)is designed to estimate the acceleration of the maneuvering targets and the unmatched time-varying disturbances for improving tracking accuracy.Furthermore,the command filters are used to solve the"differential expansion"problem during the backstepping design.The Lyapunov theory is used to prove the stability of the overall closed-loop IEGC system.Finally,the simulation results validate the integrated system's effectiveness,achieving high accuracy strikes against maneuvering targets.

Unified Control Theory from PID to ACPID

To address the challenge of achieving unified control across diverse nonlinear systems, a comprehensive control theory spanning from PID (Proportional-Integral-Derivative) to ACPID (Auto-Coupling PID) has been proposed. The primary concept is to unify all intricate factors, including internal dynamics and external bounded disturbance, into a single total disturbance. This enables the mapping of various nonlinear systems onto a linear disturbance system. Based on the theory of PID control and the characteristic equation of a critically damping system, Zeng’s stabilization rules (ZSR) and an ACPID control force based on a single speed factor have been designed. ACPID control theory is both simple and practical, with significant scientific significance and application value in the field of control engineering.