Houshang Darabi

Survey of Wireless Indoor Positioning Techniques and Systems

Wireless indoor positioning systems have become very popular in recent years. These systems have been successfully used in many applications such as asset tracking and inventory management. This paper provides an overview of the existing wireless indoor positioning solutions and attempts to classify different techniques and systems. Three typical location estimation schemes of triangulation, scene analysis, and proximity are analyzed. We also discuss location fingerprinting in detail since it is used in most current system or solutions. We then examine a set of properties by which location systems are evaluated, and apply this evaluation method to survey a number of existing systems. Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.

A control switching theory for supervisory control of discrete event systems

In this paper, we introduce the concept of switching from one supervisory control to another one when changes in the state of an embedded sensory network occur. The sensory devices are assumed to be single functional, that is, they are programmed to observe and report only one event. The switching model is built based on the two criteria of language observability and state synchronization. Switching model is the basis for a megacontroller, which monitors the state of the sensory network embedded in the plant as well as the state of the supervisor in charge. Every time the state of this network changes, the megacontroller reconfigures the control system by finding an appropriate supervisor.

Control Reconfiguration of Discrete Event Systems With Dynamic Control Specifications

This paper defines a reconfiguration method for the class of discrete-event systems (DES) that is subject to linear constraints as their control specifications. Some existing methods for enforcing these constraints make use of Petri-net P-invariants for controller synthesis. These methods are quite appealing because their computational complexity is much more tractable than most other methods for controller synthesis. However, a common limitation of all existing P-invariant-based control architectures for DES plants is the assumption that the linear constraints defining the control specification of the plant do not change over time. Here, we relax this assumption and allow the control specifications to change during controller runtime. Under certain assumptions on DES behavior, we automatically reconfigure the DES controller after the control specification is changed. In addition, if the current state of the controlled DES has become infeasible under the new control specification, we automatically generate a so-called plant reconfiguration procedure whose execution leads the system back to a feasible state. This reconfiguration procedure is optimal in that it seeks to minimize the cost of reconfiguration actions through an Integer Programming (IP) model. The objective function of the IP model can be used to generate reconfiguration solutions that meet some desired properties. Depending on the cost of each reconfiguration action, a minimum cost reconfiguration solution may use only actions contained in the current plant configuration (an internal response), or ask for a change in the plant configuration, for instance, by adding new resources (an external response), or a combination of both strategies. Finally, we illustrate our method by applying it to a hospital control system example. Note to Practitioners-This paper proposes a dynamic reconfiguration framework that can revise the operations of systems whose control requirements change over time. The proposed framework can be applied to systems that satisfy the following two assumptions. First, the behavior of the system under study is described in terms of a set of discrete states and events. Events will cause the system to transition between states. Second, the control requirements must be expressed by linear equalities and inequalities on the system states. Under these circumstances, the proposed framework can identify an optimal transition to a new control policy that satisfies the new control requirements. Moreover, the system under consideration will continue operating while this transition is taking place. One application of this method is in modifying hospital control strategies when a hospital experiences unexpected events. In this case, the hospital operations-such as patient handling, resource assignment, and procedure scheduling-can be represented by discrete state models (e.g., Petri nets). Constraints on these operations can be modeled by linear inequalities on hospital and patient state. Upon a change in the constraints, the proposed reconfiguration method revises the hospital control strategies. For example, a shift in the hospital service demands (e.g., an increase in the flow of patients to the hospital due to a mass casualty situation) can be translated to changes in the constraints. In this case, the hospital operations must be revised to accommodate the new constraints without disrupting the operation of the hospital. The reconfiguration method of this paper provides a framework for modeling the reconfiguration steps and for calculating the least cost reconfiguration solution.

Formal Modeling of Sequential Function Charts With Time Petri Nets

Sequential function charts (SFCs) are among the standard languages for programmable logic controllers (PLCs) ubiquitous in automated manufacturing and production systems. While SFCs are quite user friendly to developers, it is not easy to guarantee the correctness of safety-critical SFC programs. Thus, methods and tools for verifying the correctness of SFC programs are highly desirable. Here we introduce a transformation technique that converts a significant subset of an SFC to a time Petri net (TPN). Thanks to a large body of literature and mature tools that can analyze TPNs, our technique will bridge the gap between a user-friendly manufacturing control programming tool, the SFC, and powerful analysis tools for TPNs.

A Modelling and Optimisation Management Tool for large-scale supply chain networks

Supply Chains (SC) can be complex, dynamic and large-scale. They can make modelling and optimisation of SC difficult tasks. This paper describes a framework of a new Modelling and Optimisation Management Tool (MOMT) for large-scale supply chain networks. A graph-based method is used to automatically generate and update optimisation models for large-scale SC networks. Graphs nodes and arcs, that define the optimisation models constraints and variables, are generated according to the SC requirements. MOMT increases accuracy and flexibility of modelling and information processing in large-scale SC models. The tool applications, advantages and disadvantages are described by real world examples from Motorola Inc. SC.

Modeling and integration of hospital information systems with Petri nets

While the use of information technologies is becoming increasingly widespread in healthcare organizations, such as large hospitals, to date these organizations lack unified information systems providing a comprehensive view of the organizations state. We define a technique for building formal models capturing the state of hospital departments and the interactions among departments during hospital operations. These models, based on Petri nets, will support a variety of management and decision-support tools, such as statistical analysis, simulation, and dynamic reconfiguration. These models are at the core of a new software prototype that we are developing for the University of Illinois Medical Center at Chicago.

Supervisory control of time Petri nets using net unfolding

We define supervisory controllers for enforcing deadlines on transition firings in time Petri nets. Given a target net transition t/sub d/, and a deadline /spl lambda/, we generate a controller that under broad assumptions forces t/sub d/ to fire every /spl lambda/ time units. Our supervisory controller is based on the notion of transition latency. The latency of a net transition is an upper bound on the time between the firing of that transition and the firing of t/sub d/. A transition is not allowed to fire when its latency is greater than the amount time left until t/sub d/ must fire. Our real-time supervisory controllers consist of two subnets, which are added to the controlled net in order to enforce deadline /spl lambda/ on the firing of t/sub d/. First, the clock subnet dynamically tracks the amount of time left until the expiration of /spl lambda/. As the deadline approaches, this subnet also indicates transitions that must be disabled because their latency has become greater than the time until the expiration of the deadline. When this happens, a supervisor subnet actually disables these transitions. These transitions are enabled again only after t/sub d/ has fired.

Enforcing transition deadlines in time Petri nets

We automatically synthesize supervisory controllers that force a system to perform a certain operation by a given deadline. The operation must be executed by a pre-specified delay lambda with respect to the previous execution of the operation. We model both the controlled system and our control supervisors as time Petri nets. Given a target transition and a deadline, our supervisors disable net behaviors in which the firing of the target transition may miss the deadline. Our method is subject to a merge exclusion assumption on the structure of paths contained in a so-called net unfolding. If a control problem does not satisfy this assumption, we abandon supervisor generation. Preliminary empirical results show that our method is both relatively general and more tractable from a computational standpoint than most other real-time analysis methods.

LSTM Fully Convolutional Networks for Time Series Classification

Fully convolutional neural networks (FCNs) have been shown to achieve the state-of-the-art performance on the task of classifying time series sequences. We propose the augmentation of fully convolutional networks with long short term memory recurrent neural network (LSTM RNN) sub-modules for time series classification. Our proposed models significantly enhance the performance of fully convolutional networks with a nominal increase in model size and require minimal preprocessing of the data set. The proposed long short term memory fully convolutional network (LSTM-FCN) achieves the state-of-the-art performance compared with others. We also explore the usage of attention mechanism to improve time series classification with the attention long short term memory fully convolutional network (ALSTM-FCN). The attention mechanism allows one to visualize the decision process of the LSTM cell. Furthermore, we propose refinement as a method to enhance the performance of trained models. An overall analysis of the performance of our model is provided and compared with other techniques.

Enforcing Periodic Transition Deadlines in Time Petri Nets With Net Unfoldings

We define a method for the automatic generation of supervisory controllers that force a plant to perform a given operation by a given deadline. The operation must be executed by a prespecified delay λ with respect to the previous execution of the operation. Although our supervisor generation occurs offline with respect to plant execution, the resulting controllers automatically take into account variable task durations in an effort to increase the flexibility of operation schedules in the controlled plant. We model both the controlled plant and control supervisors as time Petri nets. In this setting, our control supervisors must force a target transition td to fire within λ time units since the previous firing of td. Our supervisor generation is based on the concept of a transition latency. The latency of a Petri net transition t is the time interval during which t must be disabled in order for target transition td to fire by its deadline. If a transition t that may delay the firing of td has latency l(t), then t must be disabled at least l(t) time units before the expiration of the deadline on td. In this paper, we discuss in detail two algorithms for generating transition latencies, and we show an application to a maintenance system.