Purpose Large supply and computer networks contain heterogeneous information correlation among their components, are distributed across a large geographical region. This paper aims to investigate develop generic knowledge integration framework that can handle the challenges posed in complex network management. It also seeks examine this various applications of essential management tasks different infrastructures. Design/methodology/approach Efficient technologies key capably handling...

Security management of modern supply systems raise challenges to various aspects Supply Chain Management (SCM) researches, demanding an integrated and holistic solution framework. In this paper, we concentrate on two fundamental instruments support the pursuit a centric (SecSCM) mission. Firstly, security taxonomy within SCM context provides comprehensive knowledge map relevant artifacts issues for players communicate collaborate in special field. Ultimately, it supplies building blocks...

In this paper, the equivalence is established between linear active disturbance rejection control (LADRC) and two-degree of freedom (2-DOF) proportional-integral-derivative (PID) with lead-lag compensators. This allows advantage LADRC, particularly its bandwidth-parameterization strategy, to be incorporated into run-of-mill PID controllers. Specifically, competing design objectives in rejection, tracking, noise sensitivities can now handled ease.

This paper considers the problem of autonomous cooperative hunting in an unknown dynamic environment, where a group mobile agents collaborate to capture moving target. Due decentralized decision-making nature multi-agent systems and presence real-world constraints, it is challenging task. To solve this problem, artificial rule based algorithm (AR-HA) firstly developed on principles attraction repulsion with heading adjustment, each agent controlled by designed rules. Then, further enhance...

This paper proposes a new data-driven control (DDC) based on SPSA(simultaneous perturbation stochastic approximation). Inheriting the essence of PID controller: simple and practical, an IMC-PID controller is conducted as Function Approximator in SPSA tuning. All parameters this polynomial are tuned online simultaneously directly via system I/O data, rather than only filter coefficients off-line. IMC concept introduced into DDC structure help provide initial value, range random disturbance...

Inspired by Active Disturbance Rejection based Iterative Learning Control (ADR-ILC) and Data-Driven Optimal (DDOILC), this paper proposes a simplified data-driven optimal iterative control method on extended state observer (IESO). Accurate estimation of the system uncertainties is observed IESO during process. Though considering dynamic linearization method, it not needed to deduce new form original pseudo partial derivative (PPD). IESO, undertaking as tool estimate whole uncertainties,...

As outsourcing and globalization increase the number of supply chain participants, a collaborative product development will enable companies to speed up decision-making chains trusted partners, employees, suppliers, customers. The first phase new is conceptual design. Eighty percent costs are determined during this phase. Due continuous changes in design projects, delays developments not rare. Thus, change control workflow needed among participants for especially development. A distributed...

The problem of iterative learning control is studied for a class discrete singular systems with fixed initial shift. Based on the equivalent restrict decomposition form systems, original are transformed into difference-algebraic systems. Then algorithm constructed and corresponding state limiting trajectory presented. Under action algorithm, system can converge to trajectory. In order eliminate effect shift, rectifying strategy applied By using strategy, track desired within pre-specified...

A discrete active disturbance rejection iterative learning control method based on dynamic linearization is proposed for a class of discrete-time, nonlinear and non-affine system that run repeatedly within finite time. The controlled dynamically linearized into an affine form related to the input iteration domain. gain initialized through pseudo partial derivative model when needed then fixed. estimated errors parameter, uncertainty external are compacted term as total system. Via sliding...

Soft sensors are especially required in lots of advanced process control applications. The ANN based soft sensor widely studied recently. But the is an uncertain method nature. In view complexity industrial processes, robustness important criterion to evaluate a model. generalization capability another factor affect applicability Aiming at improving and system, two-level architecture MNN model proposed for modeling. our model, multiple networks combined with Bayesian fuzzy C-means (FCM)...