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For discrete automation systems, certain human operations may violate desired safety requirements and result in catastrophic failure. For such humanin-the-loop systems, this paper proposes a systematic approach to developing supervisory agents which guarantee that manual operations meet required safety specifications. In the present approach, Petri nets (PN) are applied to construct a system model and synthesize a desired supervisor. Applications to 1) a rapid thermal process (RTP) in semiconductor manufacturing controlled over the Internet (Lee and Hsu, 2003) and 2) a two-robot remote surveillance system (Lee et al., 2005) are provided to demonstrate the practicability of the developed supervisory control approach. The technique developed in this paper is significant in industrial applications. 1.1 General Review Basically, an automated process is inhe rently a discrete event system (DES). The Petri net (PN) has been developed as a powerful tool for modelling, analysis, simulation, and control of DES. PN was named after Carl A. Petri (1962), who created a net-like mathematical tool for describing relations between the conditions and the events. PN was further developed to meet the need in specifying process synchronization, asynchronous events, concurrent operations, and conflicts or resource sharing for a variety of industrial automated systems at the discrete-event level. Starting in the late of 1970’s, researchers investigated possible industrial applications of PN in discrete-event systems as in the survey/tutorial papers of Murata (1989), Zurawski and Zhou (1994), David and Alla (1994), and Zhou and Jeng (1998).

Static friction compensation is usually required to reduce friction in precision motion control and manufacturing processes. Micro-motion control is a current trend for precision machining in the electronics industry. Dynamic friction plays an important role in systems using micro-scale motion at high-speed and high-frequency command. The Lund–Grenoble (LuGre) friction model is suitable for coping with the dynamic friction effect. However, the parameters of this model are difficult to accurately identify to ensure satisfactory control performance in miniature machining. This paper proposes an efficient and systematic three-step parameter estimation method for LuGre modeling. The friction compensation of the proposed approach was successfully demonstrated on a 400W AC servo motor. Furthermore, under a peck drilling command on DYNA 1007 CNC machine, the LuGre model also improved motion precision by 72.0% in the maximum peak error.

The computerized numerical control machine tool is a highly integrated mechatronic system in manufacturing processes. However, uncertainties degrade its motion accuracy. These include modeling errors, parameter variation, friction, and measurement errors that are present in either linear or nonlinear nature. In this paper, a state-space disturbance observer was successfully applied to servomotors to estimate and compensate for the uncertainties of parameter variation and current measurement problems, in the velocity and current loops, respectively. Furthermore, an autotuning procedure was developed accordingly to identify the varied parameters of the motor. Furthermore, by implementing the present servomotor systems in high-precision machine tools, the nonlinear friction compensation was adopted to reduce the slip-stick effect in contouring motion. Experimental results indicate that the roundness error has been significantly reduced from 13.3 to 2.0 ?m by applying the proposed approaches.

The error resources of precise motion control systems are basically categorized into linear and nonlinear effects. To realize the precise motion of industrial computer numerical control (CNC) machines, this paper presents an integrated motion control structure with modular algorithms, including both the linear control and the nonlinear compensation. In the linear control design, this study applies three algorithms: (1) feedforward control to address the tracking errors, (2) cross-coupled control to reduce the contouring errors, and (3) digital disturbance observer to lessen the effects of modeling errors and disturbances in real applications. The results indicate that the linear motion controller achieves greatly improved accuracy in both tracking and contouring by reducing the servo lags and mismatched dynamics of the different axes. However, the adverse effect due to friction still exists and cannot be eliminated by applying the linear motion controller only. This study further integrates the nonlinear compensator and develops friction estimation and compensation rules for CNC machines. The digital signal processors are suitable to implement all the developed linear and nonlinear algorithms, and the present controllers have been successfully applied to industrial CNC machines. Experimental results on a vertical machining center indicate that, under different feed rates, the CNC machine with the integrated motion controller significantly reduces the maximum contouring error by 135% on average.

Recently, modeling and simulation of hybrid dynamic systems (HDSs) have attracted much attention. However, since simultaneously dealing with the discrete and continuous variables is very difficult, most of the models result in a unified but more complicated and unnatural format. Moreover, design engineers cannot be allowed to use their preferred domain models. Based on the multiparadigm modeling concept, this correspondence proposes a Petri net framework with associated state equations to model the HDSs. In the presented approach, modeling schemes of the hybrid systems are separated but combined in a hierarchical way through specified interfaces. Designers can still work in their familiar domain-specific modeling paradigms, and the heterogeneity is hidden when composing large systems. An application to a rapid thermal process in semiconductor manufacturing is provided to demonstrate the practicability of the developed approach.

Convenience stores generally consume energy higher than other retailing merchants. As the problem of energy shortage becomes more serious during summer, almost all convenience stores sign a contract with power plants, which provides for fines if demand limiting occurs in Taiwan and many other countries. Therefore, a reliable and effective method to reduce their utility consumption is required for modern business and industry. This research integrates the remote sensors, the control network, and the embedded system technologies to construct a distributed energy management control system for dedicated convenience stores. Energy consumption can thus be reasonably managed with demand limits by measuring and analyzing the power consumption sources in four major subsystems of convenience stores, namely, (1) air-conditioning, (2) lighting, (3) heating, and (4) refrigeration. By applying the proposed demand prediction and control method, the demand limiting condition can be properly predicted, and the possible peak load can thus be eliminated via the network control mechanism. Moreover, by integrating the LonWork fieldbus and the WinCE operating system (OS), the proposed system has been successfully applied to a convenience store. The experimental results indicate that the proposed distributed energy management system suitably predicts the peak loading condition and successfully prevents its occurrence by switching the air-conditioning system without affecting the indoor temperature regulation.

In a semiconductor manufacturing system, particular human operations may violate desired requirements and lead to destructive failure. For such human-in-the-loop systems, this paper proposes a supervisory framework which guarantees that manual operations meet required specifications so as to prevent human errors in operation using Petri nets. Moreover, a modular technique with an intersection mechanism is proposed in order to cope with the state-space explosion problem of large-scale systems. A rapid thermal process in semiconductor manufacturing systems is provided to show the practicability of the proposed approach. Note to Practitioners - This work was motivated by the requirement of remote monitoring and supervision of semiconductor manufacturing systems. In such human-in-the-loop and large-scale systems, certain human operations may violate desired safety requirements and result in catastrophic failure. Moreover, the overall complexity of most existing Petri net modeling and analysis approaches significantly increases with the size of the considered systems. This paper suggests a modular supervisory scheme for modeling and synthesis of supervisory agents using Petri nets. The proposed method contributes a promising tool for preventing abnormal operations from being carried out to semiconductor manufacturing systems which, if appropriately modified, may be also applied to other types of discrete event systems.

For remote control systems, certain human operations may violate desired requirements and result in catastrophic failure. For such human-in-the-loop systems, this paper implements a hierarchical supervision system to guarantee that remote human-issued commands meet required specifications. In the presented scheme, Petri nets are applied to model, design, and verify both the local controller and the remote supervisor. Then, the agent technology is adopted to implement the supervisor as an intelligent agent for an online supervision of the remote control system. Hence, undesired resource conflicts and deadlock states can be avoided. An application to a flexible manufacturing system controlled over the Internet is provided to illustrate the developed approach. Implementation results show that by applying the presented hierarchical scheme, the supervisor has a more compact model with fewer states. Moreover, fewer request/response transmissions are consumed so that the effects of time delays and packet losses across the Internet could be moderated

In a distributed robotic system, both human-controlled (semi-autonomous) and computer-controlled (fully autonomous) robots may simultaneously exist. From the global system's point of view, supervisory control for the interactions between the human and computer are important and necessary. For such human-computer interactive systems, this paper proposes a supervisory framework to guarantee that both human and computer commands meet collision-free and deadlock-free requirements. In the presented approach, Petri nets are applied to construct a system model and synthesize a desired supervisor. An application to a two-robot remote surveillance system is provided to demonstrate the practicability of the developed supervisory control approach. It is believed that the technique developed in this paper is significant in the industrial practice.

This paper presents a systematic approach for the design and implementation of the sequence controller in manufacturing systems. By employing the IDEF0, we construct the simplified Petri net controller (SPNC) through the material flow diagram and the information flow diagram. Then, the ladder logic diagram (LLD) can be transformed from the SPNC through the token passing logic (TPL). The proposed approach, including the IDEF0, SPNC, and TPL tools, leads to the standard IEC1131-3 LLD for PLC implementation. Finally, an application of a stamping process is provided to illustrate the design procedure of the developed approach .

The quadratic constraint equation error (QCEE) method was proposed by Ho and Chan (see ibid., vol.43, no.1, p.51-62, 1995) to achieve bias removal for the equation error adaptive IIR filters. However, this approach is limited to slow convergence in estimation when a small step size is used; large step sizes lead to significant misadjustment. This article presents a variable step size (VSS) technique to greatly improve the QCEE under its quadratic constraint to achieve both fast convergence and reduced misadjustment for adaptive IIR filters.

This paper presents a real-time intelligent supervision system for IC ion implantation processes. A hardware interface is developed, to extract the features directly from the 2-D analog image signals of a beam map. A qualitative model for the beam scanning is then obtained, and the symptoms of abnormal operations can be analyzed to achieve on-line diagnosis. Furthermore, a fuzzy expert system is developed to advise operators on making appropriate adjustments for the beam scanning. This supervisory system has been implemented on Eaton NV-6200 A/AV ion implanters at the Taiwan Semiconductor Manufacturing Company.

Recently, feedforward controllers like zero phase error tracking controllers (ZPETC) and cross-coupled controllers (CCC) have been developed to effectively reduce tracking error and contouring error, respectively. This paper proposes an integrated controller which combines ZPETC and CCC to achieve both tracking and contouring accuracy. Furthermore, studies indicate that ZPETC and CCC can be designed separately in the present integrated control design. In the provided experimental setup with a servo table, an optimal ZPETC and a robust CCC based on the contouring error transfer function (CETF) were designed to achieve desirable frequency responses and stability. Experimental results show that the proposed integrated controller renders significantly improved accuracy in both tracking and contouring.

Unlike cases where only a single failure occurs, fault detection and isolation of multiple sensor and actuator failures for engines are difficult to achieve because of the interactive effects of the failed components. If faults all appear either in sensors only or in actuators only, many existing residual generators which provide decoupled residual signals can be employed directly to obtain proper fault detection and isolation. However, when both sensor and actuator failures occur at the same time, their mutual effects on residuals make fault isolation particularly difficult. Under such circumstances, further decision logic is required. In the paper, the authors propose a hexadecimal decision table to relate all possible failure patterns to the residual code. The residual code is obtained through simple threshold testing of the residuals, which are the output of a general scheme of residual generators. The proposed diagnostic system incorporating the hexadecimal decision table has been successfully applied to automotive engine sensors and actuators in both simulation and experimental analyses. Enhancement of the present diagnostic performance by implementing an additional sensor is also described. >

Missing commands from the interpolator caused by the dropout effect of network transmission will cause motion error in motion plants implemented on network-based control systems (NCSs). Dropout data can be properly recovered by applying different message estimators to improve motion contouring accuracy. This study shows that the dropout rate and the distribution of missing commands dominate the motion error, and that more centralized missing commands result in a higher maximum contouring error. The short-window dropout quantity (SDQ) is proposed in this paper to estimate the network quality based on the dropout rate and its distribution of the missing data. Furthermore, according to the condition of missing data based on the SDQ, the switching least-square estimator (LSE) is proposed to compensate for missing motion commands. Simulation and experimental results on the two-axis AC servo motor NCS indicate that motion contouring accuracy is greatly improved by applying the proposed estimator.

Most successful applications of parameter adaptive control to obtain constant cutting forces in machining processes have been limited to laboratory environments. This paper presents a methodology for realizing efficient adaptive control algoritms in industrial CNC machines. Experimental results concerning the fixed gain integral control and variable gain MRAC show that the present set-up in a heavy-duty CNC machining center leads to predictable control behavior. Furthermore, two effective algorithms—a deadbeat self-tuning control with increased order and a PID-type self-tuning control based on the pole-placement method—are implemented to obtain more effective cutting control performance. In this study, repeatable and satisfactory experimental results show that the technique developed here for real manufacturing processes is feasible.

Sequence controller designs play a key role in advanced manufacturing systems. Traditionally, the ladder logic diagram (LLD) has been widely applied to programmable logic controllers (PLC), while recently the Petri net (PN) has emerged as an alternative tool for the sequence control of complex systems. The evaluation of both approaches has become crucial and has thus attracted attention. The “basic element” approach was developed to evaluate the complexity and flexibility for LLD and PN design approaches [1, 2, 3, 4]. However, the basic elements of these two designs are inherently different and hence that approach may lead to unreliable results. Since sequence control here naturally implies the use of logic rules, a rule-based approach is proposed in this paper to provide unified measures for both LLD and PN designs. To illustrate the proposed approach, it is applied to five control sequences with increasing complexity for a stamping process. Results indicate that the proposed approach is more suitable for real applications and, furthermore, PN is increasingly superior to LLD as the control sequence becomes more complex.

Stress-corrosion tests are conducted on aligned short-fibre composites to assess their performance in both air and 1 N H2SO4 environments. The materials used are 3 mm E-glass, AS4 carbon, and their hybrid fibre reinforced epoxy composites. Several crack propagation models are developed to describe different cracking behaviour; the observed composite fracture modes verify these proposed models. Pre-immersion has significant effects onKl-tf and crack arrest of hybrid composites. A comparison of theoretical and experimentalKl-tf curves indicates good agreement of time to failure. The present research has quantified the susceptibility of these composites to environmental attack.