垃圾焚烧发电厂自动控制系统

本文重点介绍应用于垃圾焚烧发电厂的自动控制系统，并对主要控制功能进行详细的叙述。

机电控制系统自动控制技术与一体化设计

随着国家经济和科学技术快速的发展,机电控制系统自动控制技术越来越得到推广和普及,并在现代工业生产中发挥着越来越不可替代的作用。基于机电控制系统自动控制技术的重要作用性,该文以机电控制系统自动控制技术为研究对象,剖析机电系统自动控制与机电一体化技术,研讨机电一体化设计。

八甲口供水工程自动化控制系统的探讨

探讨了八甲口供水工程自动化控制系统的优越性及组成，论述了系统设计时应遵循的原则、系统中心站的技术要求，阐明了其水源控制系统的主要功能，指出该系统是整个工程的重要环节。

DCS控制系统在过滤机中的应用

过滤机区别于以往的PLC控制,现在使用浙江中控的ECS-700 DCS控制系统更能完成精确的操作和控制。

基于PAC的MPS供料单元控制系统设计

利用PAC设计了MPS供料单元控制系统,给出了MPS供料单元控制系统设计方案,分析了供料单元的结构与功能、气动控制回路,给出了供料单元的I/O地址分配表和I/O电气接口图,编写了程序框图及梯形图程序,最后上机调试,验证了基于PAC的MPS供料单元控制系统的设计与实现的可行性。

AC800F在济钢化工厂脱硫系统改造中的应用

介绍了AC800F DCS控制系统在济钢化工厂脱硫系统改造中的应用的过程,阐述了软硬件配置,程序编制,改造实施过程以及改造效果等情况。

A HOLONIC FRAMEWORK OF RECONFIGURABLE SHOP FLOOR CONTROL SYSTEMS IN AUTOMATED MANUFACTURING SYSTEMS

The agility and the flexibility of the current shop floor control systems have been limited so far, owing to the lack of structural flexibility and agility in its control software layer. Most of them are based on traditional hierarchical architecture and the top down approach and depend structurally on their specific configuration and job scheduling. Not only can they hardly satisfactorily adapt to these increasing changes and disturbances, but also make the redevelopment and maintenance of shop floor control system (SFCS) to need high cost and much time. And SFCS based on the heterarchical architecture don′t provide a predictable and high performance system, especially not in the heterogeneous environments, where the resources are scarce and the current decisions have serious repercussions on the future performances. For this reason, the heterarchical control is hardly applied in industry. Obviously, it is necessary to develop a new structural framework of reconfigurable SFCS to improve their agility, flexibility and maintainability. This paper presents a holonic framework of reconfigurable SFCS based on holonic manufacturing concepts. The framework is composed of resource holons, product holons and other staff holons. The model of each holon and the co operative mechanisms of holons are described. To verify the proposed approach experimentally, a prototype reconfigurable SFCS for a flexible manufacturing shop floor producing discrete parts is implemented.

New development of longwall mining equipment based on automation and intelligent technology for thin seam coal

The paper introduced complete sets of automatic equipment and technology used in thin seam coal face, and proposed the comprehensive mechanization and automation of safe and high efficiency mining models based on the thin seam drum shearer. The key technology of short length and high power thin seam drum shearer, and new type roof support with big extension ratio and plate canopy were introduced. The new research achievement on automatic control system of complete sets of equipment for the thin seam coal, which composed of electronic-hydraulic system, compact thin seam roof supports, high effective shearer with intelligent control system, and characterized by automatical follow-up and remote control technology, was described in this paper..

Improved Smith prediction monitoring AGC system based on feedback-assisted iterative learning control

The performance of Smith prediction monitoring automatic gauge control(AGC) system is influenced by model mismatching greatly in strip rolling process. Aiming at this problem, a feedback-assisted iterative learning control strategy, which learned unknown modeling error by using previous control information repeatedly, was introduced into Smith prediction monitoring AGC system. Firstly, conventional Smith predictor and improved Smith predictor with PI-P controller were analyzed. Secondly, on the basis of establishing of feedback-assisted iterative learning control strategy for improved Smith predictor, process control signal update law and control error were deduced, then convergence condition of this strategy was put forward and proved. Finally, after modeling the automatic position control system, the PI-P Smith prediction monitoring AGC system with feedback-assisted iterative learning control was researched through simulation. Simulation results indicate that this system remains stable during model mismatching. The robustness and response of monitoring AGC is improved by development of feedback-assisted iterative learning control strategy for PI-P Smith predictor.

Design of a modern automatic control system for the activated sludge process in wastewater treatment

The Activated Sludge Process(ASP) exhibits highly nonlinear properties. The design of an automatic control system that is robust against disturbance of inlet wastewater flow rate and has short process settling times is a challenging matter. The proposed control method is an I-P modi fied controller automatic control system with state variable feedback and control canonical form simulation diagram for the process. A more stable response is achieved with this type of modern control. Settling times of 0.48 days are achieved for the concentration of microorganisms,(reference value step increase of 50 mg·L-1) and 0.01 days for the concentration of oxygen(reference value step increase of 0.1 mg·L-1). Fluctuations of concentrations of oxygen and microorganisms after an inlet disturbance of5 × 103m3·d-1are small. Changes in the reference values of oxygen and microorganisms(increases by 10%, 20% and 30%) show satisfactory response of the system in all cases. Changes in the value of inlet wastewater flow rate disturbance(increases by 10%, 25%, 50% and 100%) are stabilized by the control system in short time. Maximum percent overshoot is also taken in consideration in all cases and the largest value is 25% which is acceptable. The proposed method with I-P controller is better for disturbance rejection and process settling times compared to the same method using PI controller. This method can substitute optimal control systems in ASP.

Mixed-Weights Least-Squares Stable Predictive Control Algorithm with Soft and Hard Constraints

Mixed-weight least-squares (MWLS) predictive control algorithm, compared with quadratic programming (QP) method, has the advantages of reducing the computer burden, quick calculation speed and dealing with the case in which the optimization is infeasible. But it can only deal with soft constraints. In order to deal with hard constraints and guarantee feasibility, an improved algorithm is proposed by recalculating the setpoint according to the hard constraints before calculating the manipulated variable and MWLS algorithm is used to satisfy the requirement of soft constraints for the system with the input constraints and output constraints. The algorithm can not only guarantee stability of the system and zero steady state error, but also satisfy the hard constraints of input and output variables. The simulation results show the improved algorithm is feasible and effective.

Dynamical Correction of Control Laws for Marine Ships’ Accurate Steering

The objective of this work is the analytical synthesis problem for marine vehicles autopilots design. Despite numerous known methods for a solution, the mentioned problem is very complicated due to the presence of an extensive population of certain dynamical conditions, requirements and restrictions, which must be satisfied by the appropriate choice of a steering control law. The aim of this paper is to simplify the procedure of the synthesis, providing accurate steering with desirable dynamics of the control system. The approach proposed here is based on the usage of a special unified multipurpose control law structure that allows decoupling a synthesis into simpler particular optimization problems. In particular, this structure includes a dynamical corrector to support the desirable features for the vehicle＇s motion under the action of sea wave disturbances. As a result, a specialized new method for the corrector design is proposed to provide an accurate steering or a trade-off between accurate steering and economical steering of the ship. This method guaranties a certain flexibility of the control law with respect to an actual environment of the sailing;its corresponding turning can be realized in real time onboard.

Observer-based Iterative and Repetitive Learning Control for a Class of Nonlinear Systems

In this paper, both output-feedback iterative learning control(ILC) and repetitive learning control(RLC) schemes are proposed for trajectory tracking of nonlinear systems with state-dependent time-varying uncertainties. An iterative learning controller, together with a state observer and a fully-saturated learning mechanism, through Lyapunov-like synthesis, is designed to deal with time-varying parametric uncertainties. The estimations for outputs, instead of system outputs themselves, are applied to form the error equation, which helps to establish convergence of the system outputs to the desired ones. This method is then extended to repetitive learning controller design. The boundedness of all the signals in the closed-loop is guaranteed and asymptotic convergence of both the state estimation error and the tracking error is established in both cases of ILC and RLC. Numerical results are presented to verify the effectiveness of the proposed methods.

A closed-loop particle swarm optimizer for multivariable process controller design

Design of general multivariable process controllers is an attractive and practical alternative to optimizing design by evolutionary algorithms (EAs) since it can be formulated as an optimization problem. A closed-loop particle swarm optimization (CLPSO) algorithm is proposed by mapping PSO elements into the closed-loop system based on control theories. At each time step, a proportional integral (PI) controller is used to calculate an updated inertia weight for each particle in swarms from its last fitness. With this modification, limitations caused by a uniform inertia weight for the whole population are avoided, and the particles have enough diversity. After the effectiveness, efficiency and robustness are tested by benchmark functions, CLPSO is applied to design a multivariable proportional-integral-derivative (PID) controller for a solvent dehydration tower in a chemical plant and has improved its performances.

Linear and nonlinear control of a robotic excavator

Various control systems for a robotic excavator named LUCIE (Lancaster University Computerized and Intelligent Excavator),were investigated. The excavator is being developed to dig trenches autonomously. One stumbling block is the achievement of adequate,accurate,quick and smooth movement under automatic control. Here,both classical and modern approaches are considered,including proportional-integral-derivative (PID) control tuned by conventional Zigler-Nichols rules,linear proportional-integral-plus (PIP) control,and a novel nonlinear PIP controller based on a state-dependent parameter (SDP) model structure,in which the parameters are functionally dependent on other variables in the system. Implementation results for the excavator joint arms control demonstrate that SDP-PIP controller provides the improved performance with fast,smooth and accurate response in comparison with both PID and linearized PIP control.

Permission and role automatic assigning of user in role-based access control

Role mining and setup affect the usage of role-based access control(RBAC).Traditionally,user's role and permission assigning are manipulated by security administrator of system.However,the cost is expensive and the operating process is complex.A new role analyzing method was proposed by generating mappings and using them to provide recommendation for systems.The relation among sets of permissions,roles and users was explored by generating mappings,and the relation between sets of users and attributes was analyzed by means of the concept lattice model,generating a critical mapping between the attribute and permission sets,and making the meaning of the role natural and operational.Thus,a role is determined by permission set and user's attributes.The generated mappings were used to automatically assign permissions and roles to new users.Experimental results show that the proposed algorithm is effective and efficient.

Improved Voltage Control Strategy for Photovoltaic Grid-Connected System Based on DoubleLayer Coordination Control

An improved automatic voltage coordination control strategy （AVCCS） based on ;automatic voltage control （AVC） and battery energy storage control （BESC） is proposed for photovoltaic grid-connected system （PVGS） to mitigate the voltage fluctuations caused by environmental disturbances. Only AVC is used when small environ- mental disturbances happen, while BESC is incorporated with AVC to restrain the voltage fluctuations when large disturbances happen. An adjustable parameter determining the allowed amplitudes of voltage fluctuations is introduced to realize the above switching process. A benchmark low voltage distribution system including ]？VGS is established by using the commercial software Dig SILENT. Simulation results show that the voltage under AVCCS satisfies the IEEE Standard 1547, and the installed battery capacity is also reduced. Meanwhile, the battery＇s service life is ex- tended by avoiding frequent charges/discharges in the control process.

Adaptive Anti-Synchronization Between Different Chaotic/Hyperchaotic Systems with Fully Unknown Parameters

The anti-synchronization between different chaotic/hyperchaotic systems with fully unknown parameters is considered in detail. Based on Lyapunov stability theory, the adaptive control schemes and parameter update rules are designed in this paper. Two numerical examples show the effectiveness and feasibility of the proposed method.

A New Remote and Automated Control System for the Vineyard Hail Protection Based on ZigBee Sensors, Raspberry-Pi Electronic Card and WiMAX

A new inexpensive vineyard protection against hailstorm has been realized and tested. The system has been designed and organized in such a way to perform autonomously local activities to physically control the protection of the vineyard but also to transmit information toward a remote control. Each row has an ＂umbrella＂ designed by the authors which, unlike other commercial solutions, protects the product without hindering all the mechanical activities typical of a modem vineyard. Locally the single umbrella uses an electronic card for the management and a ZigBee mesh telecommunication network to transmit data to a central control unit which manages the protection. Because of its efficiency, a Raspberry-Pi control card has been chosen as central unit. Finally, a WiMAX connection was chosen to remotely control the system, thus allowing the authors to overcome distance limitations of commercial Wi-Fi networks. The system has been realized and tested for some months in field also during a hailstorm. The results of these tests proved how the system is easy to use and effectively protects against hail; moreover the authors proved the high reliability of the mechanical components which allow the authors to lower the maintenance costs.

Robust Continuous-time Generalized Predictive Control for Large Time-delay System

A simple delay-predictive continuous-time generalized predictive controller with filter (F-SDCGPC) is proposed. By using modified predictive output signal and cost function, the delay compensator is incorporated in the control law with observer structure, and a filter is added for enhancing robustness. The design of filter does not affect the nominal set-point response, and it is more flexible than the design of observer polynomial. The analysis and simulation results show that the F-SDCGPC has better robustness than the observer structure without filter when large time-delay error is considered.