A Message-array-based Mechanism for Tracking Control Effects in Supervisory Control Software

Supervisory control is a very popular paradigm for computer-controlled systems. Knowledge and tracking the control effect of every control operation is crucial to the control tasks. In the paper, we present a message-array-based mechanism to track control effects in supervisory control software. A novel data type, message array, is designed to efficiently support this tracking mechanism. The operation algorithms, adding algorithm （AA）, removing algorithm （RA）, and scheduler algorithm （SA） are proposed to operate the tracking messages in message array, which forms the special first input X output （FIXO） strategy of message array. Automatically tracking, recording, and rolling back are the characteristics of our tracking mechanism. We implement this messagearray-based mechanism on the famous human machine interface （HMI） software platform-proficy iFix, and construct experiments to evaluate the performance of the mechanism in various cases. The results show our mechanism can be well satisfied with supervisory control software.

Fuzzy Supervisory Control and GPC Applied to a Flexible Single-Link Manipulator

This paper presents the development of a classical and intelligent control approaches applied to a flexible single-link manipulator robot and compared in terms of input tracking and vibration suppression. Lagrange＇s equations and finite elements method are combined to compute dynamic model of a flexible link manipulator with one rigid joint. Next, dynamics are itemized to explain flexible link behavior. Then a fuzzy supervisory controller is developed and introduced in the high level of the closed-loop of the flexible manipulator. A generalized predictive controller is then developed and introduced in the flexible system closed-loop to minimize end-point residual vibrations. Simulation results obtained are compared to a GPC （generalized predictive controller） in terms of end-point vibration suppression, input tracking and disturbance rejection. A conclusion encloses the paper.

Supervisory control of the hybrid off-highway vehicle for fuel economy improvement using predictive double Q-learning with backup models

This paper studied a supervisory control system for a hybrid off-highway electric vehicle under the chargesustaining(CS)condition.A new predictive double Q-learning with backup models(PDQL)scheme is proposed to optimize the engine fuel in real-world driving and improve energy efficiency with a faster and more robust learning process.Unlike the existing“model-free”methods,which solely follow on-policy and off-policy to update knowledge bases(Q-tables),the PDQL is developed with the capability to merge both on-policy and off-policy learning by introducing a backup model(Q-table).Experimental evaluations are conducted based on software-in-the-loop(SiL)and hardware-in-the-loop(HiL)test platforms based on real-time modelling of the studied vehicle.Compared to the standard double Q-learning(SDQL),the PDQL only needs half of the learning iterations to achieve better energy efficiency than the SDQL at the end learning process.In the SiL under 35 rounds of learning,the results show that the PDQL can improve the vehicle energy efficiency by 1.75%higher than SDQL.By implementing the PDQL in HiL under four predefined real-world conditions,the PDQL can robustly save more than 5.03%energy than the SDQL scheme.

Modular supervisory control for multi-floor manufacturing processes

Due to space availability limitations and high land costs,there is an increasing development of multi-floor manufacturing(MFM)systems in urban and industrial areas.The problem of coordination in a multi-floor manufacturing process,in the Ramadge Wonham framework,is introduced.The manufacturing chain of each floor and the elevator system are modeled in the form of finite deterministic automata.The models of the multi-floor manufacturing process are parametric with respect to the number of floors and the number of manufacturing machines on each floor.The coordination desired performance is formulated in the form of desired regular languages in analytic forms.The languages are realized by appropriate supervisors in the form of finite deterministic automata.The models of the supervisors are also parametric with respect to the number of floors and the number of manufacturing machines on each floor.The total control of the coordination of the multi-floor manufacturing process is accomplished via a modular supervisory control architecture.The complexity of the supervisors as well as the complexity of the total modular supervisory architecture are determined in analytic forms with respect to the number of floors and the number of manufacturing machines on each floor.The special case of a two floor manufacturing process is presented as an illustrative example.

Supervisory Control of Extended Timed Event Graphs

Abstract This paper describes the dynamic behavior of extended timed event graphs related to place delay in the dioid framework. By Cofer and Garg's supervisory control theory^|3|, we address control problems of extended timed events graphs. Supervisory control of extended timed event graphs (a class of discrete event dynamic systems) is studied in the dioid framework, a necessary and sufficient condition for the ideals of the set of firing time sequences of transitions to be controllable is presented. We prove all the strongly controllable subsets can form a complete lattice.

Designing an Intelligent Control Philosophy in Reservoirs of Water Transfer Networks in Supervisory Control and Data Acquisition System Stations

In this paper, a hybrid neural-genetic fuzzy system is proposed to control the flow and height of water in the reservoirs of water transfer networks. These controls will avoid probable water wastes in the reservoirs and pressure drops in water distribution networks. The proposed approach combines the artificial neural network, genetic algorithm, and fuzzy inference system to improve the performance of the supervisory control and data acquisition stations through a new control philosophy for instruments and control valves in the reservoirs of the water transfer networks. First, a multi-core artificial neural network model, including a multi-layer perceptron and radial based function, is proposed to forecast the daily consumption of the water in a reservoir. A genetic algorithm is proposed to optimize the parameters of the artificial neural networks. Then, the online height of water in the reservoir and the output of artificial neural networks are used as inputs of a fuzzy inference system to estimate the flow rate of the reservoir inlet. Finally, the estimated inlet flow is translated into the input valve position using a transform control unit supported by a nonlinear autoregressive exogenous model. The proposed approach is applied in the Tehran water transfer network. The results of this study show that the usage of the proposed approach significantly reduces the deviation of the reservoir height from the desired levels.

Supervisory control of concurrent discrete-event systems

Concurrency is a common feature in most industrial systems,where several components can execute different actions simultaneously.In this paper,we first introduce a new feasible nonblocking concurrent supervisory control map for a concurrent system,and subsequently,new concepts of concurrent controllability and concurrent observability.Then we present a sufficient and necessary condition for the existence of a feasible nonblocking concurrent supervisory controlmap to achieve a given concurrent language.After introducing a new concept of prefix-closed concurrent normality,we show that the supremal concurrently controllable and prefix-closed concurrently normal sublanguages exist and are computable.Our emphasis here is not to address the computational efficiency of solving concurrent supervisory control problems,which is still a technical challenge,but to show that the commonly used Ramadge–Wonham asynchronous control is simply a special case of our proposed concurrent control framework by providing an insightful treatment on compound events.

Real Time Control System for Metro Railways Using PLC & SCADA

This paper proposes to adopt SCADA and PLC technology for the improvement of the performance of real time signaling&train control systems in metro railways.The main concern of this paper is to minimize the failure in automated metro railways system operator and integrate the information coming from Operational Control Centre(OCC),traction SCADA system,traction power control,and power supply system.This work presents a simulated prototype of an automated metro train system operator that uses PLC and SCADA for the real time monitoring and control of the metro railway systems.Here,SCADA is used for the visualization of an automated process operation and then the whole opera-tion is regulated with the help of PLC.The PLC used in this process is OMRON(NX1P2-9024DT1)and OMRON’s Sysmac studio programming software is used for developing the ladder logic of PLC.The metro railways system has deployed infrastructure based on SCADA from the power supply system,and each station’s traction power control is connected to the OCC remotely which commands all of the stations and has the highest command priority.An alarm is triggered in the event of an emergency or system congestion.This proposed system overcomes the drawbacks of the current centralized automatic train control(CATC)system.This system provides prominent benefits like augmenting services which may enhance a network’s full load capacity and networkflexibility,which help in easy modification in the existing program at any time.

A Fuzzy Logic Based Supervisory Hierarchical Control Scheme for Real Time Pressure Control

This paper describes a supervisory hierarchical fuzzy controller （SHFC） for regulating pressure in a real-time pilot pressure control system. The input scaling factor tuning of a direct expert controller is made using the error and process input parameters in a closed loop system in order to obtain better controller performance for set-point change and load disturbances. This on-line tuning method reduces operator involvement and enhances the controller performance to a wide operating range. The hierarchical control scheme consists of an intelligent upper level supervisory fuzzy controller and a lower level direct fuzzy controller. The upper level controller provides a mechanism to the main goal of the system and the lower level controller delivers the solutions to a particular situation. The control algorithm for the proposed scheme has been developed and tested using an ARM7 microcontroller-based embedded target board for a nonlinear pressure process having dead time. To demonstrate the effectiveness, the results of the proposed hierarchical controller, fuzzy controller and conventional proportional-integral （PI） controller are analyzed. The results prove that the SHFC performance is better in terms of stability and robustness than the conventional control methods.

Substation Supervisory System Basedon Feeder Control Units

This paper introduces a kind of Feeder Control Units (FCUs) which treat feeders or main transformers as its objects. Being carefully designed, the FCU can separately meet the requirements such as signals’ acquisition, local control, on-time switchgear interlocking, etc. Equipped with a sort of high-speed serial communicahon interface, the FCUs can be distributively arranged near or into the switchgear, therefore a kind of distributed substation supervisory system can be formed.

A call for enhanced data-driven insights into wind energy flow physics

With the increased availability of experimental measurements aiming at probing wind resources and wind turbine operations,machine learning(ML)models are poised to advance our understanding of the physics underpinning the interaction between the atmospheric boundary layer and wind turbine arrays,the generated wakes and their interactions,and wind energy harvesting.However,the majority of the existing ML models for predicting wind turbine wakes merely recreate Computational fluid dynamics(CFD)simulated data with analogous accuracy but reduced computational costs,thus providing surrogate models rather than enhanced data-enabled physics insights.Although ML-based surrogate models are useful to overcome current limitations associated with the high computational costs of CFD models,using ML to unveil processes from experimental data or enhance modeling capabilities is deemed a potential research direction to pursue.In this letter,we discuss recent achievements in the realm of ML modeling of wind turbine wakes and operations,along with new promising research strategies.

Deadlock-free Supervisor Design for Robotic Manufacturing Cells With Uncontrollable and Unobservable Events

In this paper,a deadlock prevention policy for robotic manufacturing cells with uncontrollable and unobservable events is proposed based on a Petri net formalism.First,a Petri net for the deadlock control of such systems is defined.Its admissible markings and first-met inadmissible markings(FIMs)are introduced.Next,place invariants are designed via an integer linear program(ILP)to survive all admissible markings and prohibit all FIMs,keeping the underlying system from reaching deadlocks,livelocks,bad markings,and the markings that may evolve into them by firing uncontrollable transitions.ILP also ensures that the obtained deadlock-free supervisor does not observe any unobservable transition.In addition,the supervisor is guaranteed to be admissible and structurally minimal in terms of both control places and added arcs.The condition under which the supervisor is maximally permissive in behavior is given.Finally,experimental results with the proposed method and existing ones are given to show its effectiveness.

Control of Non-Deterministic Systems With μ-Calculus Specifications Using Quotienting

The supervisory control problem for discrete event system(DES) under control involves identifying the supervisor, if one exists, which, when synchronously composed with the DES,results in a system that conforms to the control specification. In this context, we consider a non-deterministic DES under complete observation and control specification expressed in action-based propositional μ-calculus. The key to our solution is the process of quotienting the control specification against the plan resulting in a new μ-calculus formula such that a model for the formula is the supervisor. Thus the task of control synthesis is reduced a problem of μ-calculus satisfiability. In contrast to the existing μ-calculus quotienting-based techniques that are developed in deterministic setting, our quotienting rules can handle nondeterminism in the plant models. Another distinguishing feature of our technique is that while existing techniques use a separate μ-calculus formula to describe the controllability constraint(that uncontrollable events of plants are never disabled by a supervisor), we absorb this constraint as part of quotienting which allows us to directly capture more general state-dependent controllability constraints. Finally, we develop a tableau-based technique for verifying satisfiability of quotiented formula and model generation. The runtime for the technique is exponential in terms of the size of the plan and the control specification. A better complexity result that is polynomial to plant size and exponential to specification size is obtained when the controllability property is state-independent. A prototype implementation in a tabled logic programming language as well as some experimental results are presented.

Fuzzy Variable Structure Control of Photovoltaic MPPT System

In order to reduce chattering phenomenon of variable structure control, a fuzzy variable structure control method is adopted and applied in the photovoitaic maximum power point tracking （MPPT） control system. Firstly, the electric features of PV cells and a dynamic model of photovoitaic system with a DGDC buck converter are analysed. Then a hybrid fuzzy variable structure controller is designed. The controller is composed of a fuzzy variable structure control term and a supervisory control term. The former is the main part of the controller and the latter is used to ensure the stability of the system. Finally, the conventional variable structure control method and the fuzzy variable structure control method are applied respectively. The comparing of simulation results shows the superiority of the latter.

Measurement and AFPS control of molten steel level in strip casting

The measurement and control of the molten steel level are studied, which affect the quality of strip surface in strip casting. A system of molten steel measurement with a CCD (Charge Coupled Devices) sensor is designed, real-time measured data are given and its precision is analyzed. The level fluctuation model is derived, and an adaptive fuzzy-PID controller with supervisory control (AFPS) is proposed. The stability of the system is proved using Lyapunov theorem, and the simulation results are given when the model, the casting speed and the roll gap change. It is suggested that this kind of coupled nonlinear and time varying system is stable and robust using the designed AFPS controller.

A Continuous Timed Petri Net Model and Control for a Gas Turbine

This work developed the modeling and supervisory control for gas turbine. A CTPN （continuous timed Petri Net） model of a gas turbine, using a first linear order approximation for every state of the Brayton cycle is obtained. The Brayton cycle rules the functioning of a gas turbine, and it is composed by four states： compression, combustion, expansion and cooling. The principle of the gas turbine is developed by the Brayton cycle, a thermodynamic process which intervenes in the gas turbine components. The steady-state behavior of the gas turbine has been widely investigated in engineering area. Moreover, the dynamic behavior has been studied using non-linear models of its components, leading to complicated mathematical representations. The methodology of the current work begins with a simplification of the dynamical relations in every state （excepting the cooling phase） of the Brayton cycle. Temperature and pressure are modeled as first order linear systems, therefore, every system is translated into a CTPN. Furthermore, to guarantee a safety operation, an SC （supervisory controller） is designed to ensure the combustion chamber temperature is lower than 1,000 ℃. Although the model presented is extremely simplified, it will be used as a starting point to develop more complex models.

Design method of organizational structure for MAVs and UAVs heterogeneous team with adjustable autonomy

The increasingly complex battlefield environment requests much closer connection in a team having both manned and unmanned aerial vehicles(MAVs and UAVs). This special heterogeneous team structure causes demands for effective organizational structure design solutions. Implementing adjustable autonomy in the organizational structure, the expected evaluation function is established based on the physical resource, intelligent resource, network efficiency, network vulnerability and task execution reliability. According to the above constraints, together with interaction latency, decision-making information processing capacity, and decision-making latency, we aim to find a preferential organizational structure. The proposed organizational structure includes cooperative relationships, supervisory control relationships, and decision-making authorization relationships. In addition,by considering the influence on the intelligent support capabilities and the task execution reliability created by adjustable autonomy, it helps to build the proposed organizational structure designed with certain degree of flexibility to deal with the potential changes in the unpredictable battlefield environment. Simulation is conducted to confirm our design to be valid. And the method is still valid under different battlefield environments and interventions.

Networking dual-surveillance/dual-pair-tele-paths for critical urban areas

Providing a reliable and efficient communication infrastructure for critical regions is generally a strategy used to enhance regional safety or to sustain regional development. For such purposes, the spider-web network is prototyped as a cellular telecommunication infrastructure for its advantages including being interference-free, possessing fault-tolerance, having security management, and countering radio's multipath effects. Besides, it is used to develop area-based-street-SCADA (supervisory control and data acquisition) networks composed of regular optimal degree-3 prototyped sub-networks with the concepts of dual-surveillance, operational order and Hamiltonian laceability, and it flexibly fits various circulation configurations. Moreover, it can offer integrative response capabilities even after two paths' SCADA networks have been ruined.

Three Projects of Intelligent Distribution Automation System in East Asia

Intelligent distribution automation system （IDAS） was developed based on distribution automation system that was installed in all distribution offices of Korea. IDAS was designed the combined system with the function of supervisory control and data acquisition （SCADA） and distribution automation system （DAS） for network operation from substation to high voltage customer, and it has been installed in Vietnam, China and Indonesia. This paper explains the project scope, system configuration, and the function of each sy stem.