Multi-commodity flow dynamic resource assignment and matrix-based job dispatching for multi-relay transfer in complex material handling systems (MHS)

Mass management and production of customized products requires material handling systems (MHS) which are flexible and responsive enough to accommodate dynamic and real-time changes in material handling tasks. Towards this goal, we develop a novel control framework to improve the flexibility and responsiveness of material handling systems. Flexibility is achieved by using multi-commodity flow network optimization to find the most optimized job sequence in terms of minimum transfer steps. Responsiveness is achieved by the use of a matrix-based discrete event (DE) supervisory controller to dispatch equipment control commands in real-time based on real-time sensor information, according to the optimized sequence. By modeling the MHS network as multi-commodity flow network to define job routes, and using the matrix-based DE controller to implement the job routes in real-time, the users achieve a seamlessly integrated solution to control the execution of transfer jobs that covers the supervisory planning stage through the real-time actual dispatching decisions. The proposed control framework is evaluated on an industrial case study of airfreight terminal material handling and simulation results show its effectiveness.     

SCADA在机场行李处理系统中的运用

在进行分析数据采集与监视控制（SCADA）系统结构的基础上,通过文字和图表阐述SCADA在机场行李处理系统中的控制原理,并深入剖析了SCADA在民用机场行李处理系统（BHS）中的功能与应用,同时以实际应用介绍机场行李处理系统基于WinCC技术的SCADA系统解决方案.     

Bridging the gap between designed and implemented controllers via adaptive robust discrete sliding mode control

Bridging the gap between designed and implemented model-based controllers is a major challenge in the design cycle of industrial controllers. This gap is created due to (i) digital implementation of controller software that introduces sampling and quantization uncertainties, and (ii) uncertainties in the modeled plant's dynamics. In this paper, a new adaptive and robust model-based control approach is developed based on a nonlinear discrete sliding mode controller (DSMC) formulation to mitigate implementation imprecisions and model uncertainties, that consequently minimizes the gap between designed and implemented controllers. The new control approach incorporates the predicted values of the implementation uncertainties into the controller structure. Moreover, a generic adaptation mechanism will be derived to remove the errors in the nonlinear modeled dynamics. The proposed control approach is illustrated on a nonlinear automotive engine control problem. The designed DSMC is tested in real-time in a processor-in-the-loop (PIL) setup using an actual electronic control unit (ECU). The verification test results show that the proposed controller design, under ADC and model uncertainties, can improve the tracking performance up to 60% compared to a conventional controller design.     

基于WinCC的机场行李监控系统

根据机场行李处理系统的监控要求,提出机场行李监控系统的基本框架并设计基于Win CC的机场行李监控系统。     

PLC在智能装置自动测试系统的研究和应用

可编程控制器在工业控制领域应用广泛,本文从可编程控制器在电力系统智能装置自动检测系统应用出发,介绍自动检测系统设计原理和系统组成,详细介绍PLC在本系统功能和具体应用范围,并针对可编程控制器应用中出现特殊问题进行分析,并给出解决方法。实践证明,可编程控制器系统的扩展性和可编程特点可有效满足部分控制系统的特殊要求。     

Formal component-based modeling and synthesis for PLC systems

Programmable Logic Controllers (PLCs) are widely used in industry. PLC systems are reactive systems which run cyclically. In each cycle, the system state is checked and the program is executed once to determine the system behavior for a single cycle. Development of PLC systems conventionally follows the V-model, but increasing demand for efficiency and reliability requires a new rigorous and rapid design flow. In this paper, we propose a component-based formal modeling and synthesis method for cyclic execution platforms and apply it to PLC. Our method consists of three main phases: modeling, verification and code synthesis. In the modeling phase, the BIP (Behavior–Interaction–Priority) framework which is flexible and expressive is used as the modeling language. Real-time behavior, which is intensely concerned in PLC systems, can be modeled as well. In the verification phase, the system model is translated to timed automata and checked by Uppaal. Verification helps to ensure correctness of the model and further increases reliability of the implementation. In the code synthesis phase, the software part of the system model is extracted and synthesized to cyclic code. Although the PLC software runs cyclically, the software model is not necessarily given in a cyclic manner. We propose an algorithm which can generate high-performance cyclic code from a model which describes the business work-flow. This feature significantly simplifies program development. A set of tools is implemented to support our design flow and they are applied to an industrial case study for a PLC system that controls dozens of physical devices in a huge palace.     

Automatic synthesis and verification of real-time embedded software for mobile and ubiquitous systems

Currently available application frameworks that target the automatic design of real-time embedded software are poor in integrating functional and non-functional requirements for mobile and ubiquitous systems. In this work, we present the internal architecture and design flow of a newly proposed framework called Verifiable Embedded Real-Time Application Framework (VERTAF), which integrates three techniques namely software component-based reuse, formal synthesis, and formal verification. Component reuse is based on a formal unified modeling language (UML) real-time embedded object model. Formal synthesis employs quasi-static and quasi-dynamic scheduling with multi-layer portable efficient code generation, which can output either real-time operating systems (RTOS)-specific application code or automatically generated real-time executive with application code. Formal verification integrates a model checker kernel from state graph manipulators (SGM), by adapting it for embedded software. The proposed architecture for VERTAF is component-based which allows plug-and-play for the scheduler and the verifier. The architecture is also easily extensible because reusable hardware and software design components can be added. Application examples developed using VERTAF demonstrate significantly reduced relative design effort as compared to design without VERTAF, which also shows how high-level reuse of software components combined with automatic synthesis and verification increases design productivity.     

Hardware-software codesign of embedded systems

Designers generally implement embedded controllers for reactive real-time applications as mixed software-hardware systems. In our formal methodology for specifying, modeling, automatically synthesizing, and verifying such systems, design takes place within a unified framework that prejudices neither hardware nor software implementation. After interactive partitioning, this approach automatically synthesizes the entire design, including hardware-software interfaces. Maintaining a finite-state machine model throughout, it preserves the formal properties of the design. It also allows verification of both specification and implementation, as well as the use of specification refinement through formal verification     

行李处理系统设计中三维模型的研究

该文将研究行李处理系统设计中的三维模型,对比实体模型、网格模型、线框模型在BHS设计过程中的优缺点,找到满足BHS设计要求的三维模型类型及三维建模方法。     

一类非匹配不确定性非线性系统的鲁棒镇定

研究了非线性系统存在非匹配不确定性时控制器的鲁棒镇定问题. 基于对象的模糊动态模型, 提出了一种状态反馈控制器的设计, 给出控制器在建模不确定性等各种非匹配不确定性存在下仍能够镇定非线性系统的一个充分条件. 仿真结果表明了设计方法的正确性.     

SCADA system with predictive controller applied to irrigation canals

This paper applies a model predictive controller (MPC) to an automatic water canal with sensors and actuators controlled by a PLC network (programmable logic controller), and supervised by a SCADA system (supervisory control and data acquisition). This canal is composed by a set of distributed sub-systems that control the water level in each canal pool, constrained by discharge gates (control variables) and water off-takes (disturbances). All local controllers are available through an industrial network managed by the SCADA system, where the centralized predictive controller runs.In this paper a complete new platform connecting the SCADA supervisory system and the MATLAB software (named SCADA–MATLAB platform) is built, in order to provide the usual SCADA systems with the ability to handle complex control algorithms. The developed MPC-model presents a novelty in the control of irrigation canals as it allows the use of industrial PLCs to implement high complex controllers, through the new developed SCADA–MATLAB platform.Experimental results demonstrate the reliability and effectiveness of the proposed strategy in real-life typical situations, including gate malfunctioning and extreme water off-take conditions.     

Verification of distributed control systems in intelligent manufacturing

This paper presents an application of formal methods for validation of flexible manufacturing systems controlled by distributed controllers. A software tool verification environment for distributed applications (VEDA) is developed for modeling and verification of distributed control systems. The tool provides an integrated environment for formal, model-based verification of the execution control of function blocks following the new international standard IEC61499. The modeling is performed in a closed-loop way using manually developed models of plants and automatically generated models of controllers.     

A neuro-fuzzy supervisory control system for industrial batchprocesses

The automation of complex industrial batch processes is a difficult problem due to the extremely nonlinear and variable system behavior or the conflicting goals within the different process phases. The introduction of a single multiple-input multiple-output controller is not useful because of the rather high design effort and the low transparency of its complex structure. A more suitable hierarchical fuzzy-logic (FL) based supervisory control concept is proposed. It permits the decomposition of the complex control problem into a series of smaller and simpler ones. In the upper level of the hierarchy the FL-based supervisory controller classifies the actual process phase in terms of the available process sensor signals and activates dynamically the appropriate situation specific low-level controllers. The paper presents the generic concept of the FL supervisory controller that comprises both a FL process diagnosis and a control mode selection as well as experiences with the industrial application     

A Hybrid Control Approach for Non-invasive Medical Robotic Systems

In this paper, a hybrid supervisory control approach adopted for a non-invasive medical robot called Focused Ultrasound Surgical Robot—Breast Surgery (FUSBOT-BS) is elaborated. The system was built for the use in the breast surgery with high intensity focused ultrasound (HIFU) as the means of the treatment. A number of different control strategies such as PID and model-based control were incorporated into a family of controllers to create the hybrid control. Depending on the objective, the supervisory control determines the type of controller used for the specified task so as to maximize the advantages of each of the controllers. Before it was implemented into the actual robotic system the then proposed control approach was modeled and simulated using Matlab®. This control approach was developed based on a review of popular control approaches used in medical robotic systems, in order to look at the feasibility of having a uniform control strategy for a spectrum of medical robotic system. With unified control strategy it is possible to have a safety standard regulation for the medical robotic systems which is currently difficult to be done because of various control strategies adopted by each of the medical robotic systems.     

Hybrid state-space fuzzy model-based controller with dual-ratesampling for digital control of chaotic systems

We develop a hybrid state-space fuzzy model-based controller with dual-rate sampling for digital control of chaotic systems. A Takagi-Sugeno (TS) fuzzy model is used to model the chaotic dynamic system and the extended parallel-distributed compensation technique is proposed and formulated for designing the fuzzy model-based controller under stability conditions. The optimal regional-pole assignment technique is also adopted in the design of the local feedback controllers for the multiple TS linear state-space models. The proposed design procedure is as follows: an equivalent fast-rate discrete-time state-space model of the continuous-time system is first constructed by using fuzzy inference systems. To obtain the continuous-time optimal state-feedback gains, the constructed discrete-time fuzzy system is then converted into a continuous-time system. The developed optimal continuous-time control law is finally converted into an equivalent slow-rate digital control law using the proposed intelligent digital redesign method. The main contribution of the paper is the development of a systematic and effective framework for fuzzy model-based controller design with dual-rate sampling for digital control of complex such as chaotic systems. The effectiveness and the feasibility of the proposed controller design method is demonstrated through numerical simulations on the chaotic Chua circuit     

Formal modeling and synthesis of programmable logic controllers

Programmable logic controllers (PLCs) are complex cyber-physical systems which are widely used in industry. This paper presents a robust approach to design and implement PLC-based embedded systems. Timed automata are used to model the controller and its environment. We validate the design model with resort to model checking techniques. We propose an algorithm to generate PLC code from timed automata and implement this algorithm with a prototype tool. This method can condense the developing process and guarantee the correctness of PLC programs. A case study demonstrates the effectiveness of the method.     

Improving evolvability of a patient communication control system using state-based supervisory control synthesis

Supervisory control theory enables control system designers to specify a model of the uncontrolled system in combination with control requirements, and subsequently use a synthesis algorithm for automatic controller generation. The use of supervisory control synthesis can significantly reduce development time of supervisory controllers as a result of unambiguous specification of control requirements, and synthesis of controllers that by definition are nonblocking and satisfy the control requirements. This is especially important for evolving systems, where requirements change frequently.For successful industrial application, the specification formalism should be expressive and intuitive enough to be used by domain experts, who define control requirements, and software experts, who implement control requirements and synthesize controllers. This paper defines such a supervisory control specification formalism that consists of automata, synchronizing actions, guards, updates, invariants, independent and dependent variables, where the values of the dependent variables can be defined in terms of functions on the independent variables.We also show how the language enables systematic, compositional specification of a control system for a patient communication system of an MRI scanner. We show that our specification formalism can deal with both event-based and state-based interfaces. To support systematic, modular specification of models for supervisory control synthesis, we introduce state trackers that record sequences of events in terms of states. The synthesized supervisor has been successfully validated by means of interactive user guided simulation.     

Intelligent adaptive control of bioreactors

Supervised model-based self-tuning control of fermentation processes is addressed. The diversity, nonlinearity and time-varying nature of these processes make their control a challenging task. Conventional linear (PID) controllers with fixed parameters cannot meet the increasing performance requirements over the whole operating range. In the approach pursued in this research, a local linear model is identified at the current working point by using a limited amount input–output data obtained through an identification experiment. A linear controller is then tuned on the basis of this model. To minimize the intervention into the process operation, this tuning procedure is only initiated if the performance of the current controller deteriorates. To this end, a supervisory expert system is designed whose tasks are to monitor the process performance, design an appropriate identification experiment, validate the obtained model and tune the controller. The supervisory system is based on a combination of a state automaton with a rule-based fuzzy inference system. Experimental results have demonstrated the feasibility of this approach.     

Message-oriented decomposition for supervisory control in manufacturing system

Supervisory control in manufacturing systems is achieved through messages between the supervisory controller and processing devices. This paper presents a message-oriented model for supervisory control. The model supports realistic states for processing stations and some material handling devices. The major characteristics of the model are the decomposition of the system into small state models for components that cooperate via messaging as well as the algebraic manipulation for state progression. This paper also presents a definition of controllability meaningful in the design and analysis of supervisory control systems. The modeling and analysis are illustrated with a flow line example and a robotic cell example.