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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.

Available model-based networked control system (NCS) design approaches are basically formulated from the known system model and the information of the networked-induced delay time. Because the delay in remote control systems is significant and time-varied as commercial networks involved, available model- based NCS design approaches may thus become impractical. The increase of time delay due to the limited communication bandwidth usually induces data dropout to make NCS design even more difficult.Inthispaper,theschemeoftheperfectdelaycompensation (PDC) is proposed by introducing the butterfly-shaped inner feed- back loop in NCS to deal with the unknown network-induced time delay. Furthermore, analytical results indicate that the controller obtained in general control systems can be directly implemented on NCS with the proposed PDC scheme. Both simulation and experi- mental results were successfully carried out on an ac servo motor at a distance of 15 km through Ethernet to maintain a stable remote control system.

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, several model-based control designs have been proposed for motion systems and computerized numerical control (CNC) machines to improve motion accuracy. However, in real applications, their performance is seriously degraded when significant disturbances or cutting forces are applied. In this paper, we derive straightforward design procedures for a generalstructured unknown input observer (UIO) which perfectly decouples the effect of the external disturbance from the state estimation. Furthermore, we derive the optimal UIO by minimizing the estimation errors for both the state and the disturbance via the Riccati equation. Experimental results show that the performance of all advanced motion controllers suffers when external loads are applied. By compensating for the disturbance of a servo motor using the proposed optimal-UIO, the original contouring accuracy, which is degraded by the external loading, can be successfully recovered.

The networked control system (NCS) in industrial applications, such as computerized numerical control (CNC) machine tools and robots, possess advantages of simple wiring, expansion flexibility, and easy maintenance. However, the introduced network delay is unavoidable. Moreover, in real-time synchronized multi-axis NCS, all motion messages transmitted through the network are required to be received in time to meet specifications of the deadline. However, the data dropout may occur in NCS due to its time delay in a stochastic nature, and it also may results in degradation of motion accuracy. In this paper, a motion message estimator is proposed to construct the real-time networked industrial applications to reduce the data-dropout effect. Analytical results indicate that a 3 rd -order message estimator based on the Taylor expansion successfully suppresses the uncertainties in NCS due to the dropout effect. Furthermore, this paper also proposes the networked cross-coupled control (CCC) structure to improve the contouring accuracy of the multi-axis NCS. Results indicate that the variation of the contouring error in the multi-axis NCS is suppressed greatly by applying the proposed networked CCC. Finally, experimental results indicate the proposed motion message estimator leads to improved accuracy on an industrial CNC machine tool with the NCS implementation.

The time-delay effect in network systems is unavoidable because of its limited transmission bandwidth. In real-time network control systems (NCS), all messages are required to be transmitted or received to meet specifications of the deadline. Therefore, the data dropout may thus occur in NCS due to its time delay in a stochastic nature. In this paper, a motion message estimator is proposed to construct a real-time motion NCS to significantly reduce the data-dropout effect. Both simulation and experimental results indicate that a 3rd-order message estimator based on the Taylor expansion can be properly implemented in NCS for industrial motion control systems. Furthermore, since the uncertainties of the NCS estimator are greatly suppressed by applying the message, experimental results indicate that its integration with the feedforward control leads to significantly improved accuracy for the NCS implemented on an industrial computerized numerical control (CNC) machine tool.

The linear matrix inequality (LMI) method is generally adopted to obtain the Takagi-Sugeno (TS) fuzzy control design with guaranteed system stability only. However, in real implementations, control specifications, like the damping ratio, the natural frequency or the bandwidth, are crucial to system design. In this paper, a feasible T-S fuzzy control design approach is proposed for the nonlinear motion systems with control redundancy, like in robots and satellites with input freedom to obtain the desirable position and orientation. In this paper, by applying the T-S fuzzy modeling and the inverse of the input matrix, a feasible T-S fuzzy controller is obtained to directly meet both system stability and design specifications. The proposed controller design method has been successfully applied to an omindirectional mobile robot (ODMR) system. Both simulation and experimental results indicate that the obtained system performance and stability directly meet the control design specifications. Results also indicate that the effect of the Coriolis force is effectively suppressed by the proposed approach and it leads to improved accuracy in both tracking and contouring precision especially in high-speed motions.

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 industrial applications servo motors are applied to different loads and varied control performance is thus unavoidable. Under such circumstances, engineers usually re-design or re-tune controller parameters to meet certain design specifications without reliable and consistent control performance or motion precision. In robust controller design, the quantitative feedback theory (QFT) is adopted by applying both the loop-shaping design and the feedforward controller in its feedback loop with a suitable order determined from experience. On the other hand, H ∞ controller is designed in frequency domain but is directly calculated in time domain with the controller type without restriction in selecting its order. However, H ∞ controller only deals with sensitivity without meeting control performance as in QFT design. In this study, the combined approach by using both the H ∞ algorithm and the QFT controller with better robustness is applied to the servo motor control design; in addition, the QFT feedforward controller in loop-shaping is included to lead to desirable control performance. Experimental results show that by applying the present H ∞ /QFT approach, the similar system responses under different external loading on the CNC servo motor can be successfully obtained to prove the feasibility of the present method in industrial automation.

To pursue high-speed motion control for robots, applications of servo motors with appropriate controllers may render fast responses with satisfactory precision. However, the current coupling effect on the servo motor control unavoidably downgrades stability and contouring precision as the operation speed increases in practice. This paper proposes a control structure simply by adding a decoupling gain Kc to significantly improve stability of motor control systems under high-speed operations. Simulation results on the joints of a Delta robot indicate that the present decoupling control structure effectively leads to satisfactory performance and precision under high-speed operations.

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 .

For motion systems with multiple axes, the approach of matched direct current gains has been generally adopted to improve contouring accuracy under low-speed operations. To achieve high-speed and high-precision motion in modern manufacturing, a perfectly matched feedback control (PMFBC) design for multiaxis motion systems is proposed in this paper. By applying stable pole-zero cancellation and including complementary zeros for uncancelled zeros for all axes, matched dynamic responses across the whole frequency range for all axes are achieved. Thus, contouring accuracy for multiaxis systems is guaranteed for the basic feedback loops. In real applications, the modeling error is unavoidable and the degradation and limitations of the model-based PMFBC exist. Therefore, a newly designed digital disturbance observer is proposed to be included in the proposed PMFBC structure for each axis to compensate for undesirable nonlinearity and disturbances to maintain the matched dynamics among all axes for the PMFBC design. Furthermore, the feedforward control loops zero phase error tracking controller are employed to reduce tracking errors. Experimental results on a three-axis CNC machining center indicate that both contouring accuracy and tracking accuracy are achieved by applying the present PMFBC design. @DOI: 10.1115/1.1789970#

In modern manufacturing, the design of multi-axis motion controllers for high-speed/high-precision and complex machining is becoming more critical. In the past, controllers for each axis were, in general, designed individually to obtain desirable tracking accuracy. Although some advanced motion control algorithms have been developed recently, they are mostly applicable to single-axis or biaxial systems. In particular, the design of two-axis integrated control, which includes: 1) feedback loops; 2) feedforward loops; and 3) the cross-coupled control (CCC), achieves significantly improved performance. However, its applications are limited to basic linear and circular contour commands for two-axis systems only. In this paper, system analysis for the multi-axis integrated control structure is proposed in order to achieve tracking and contouring accuracy simultaneously. With the derived contouring error transfer function (CETF), the integrated control design for multi-axis motion systems can be formulated simply as a single-input-single-output (SISO) design. Thus, a robust design with desirable performance for multi-axis motion systems can then be achieved straightforwardly. Moreover, by estimating the contouring error vector, the proposed multi-axis integrated control can be widely applied to general contour commands. Experimental results on a three-axis CNC machining center indicate that both tracking and contouring accuracy are simultaneously improved by applying the proposed control design.

In biaxial motion systems, applying the cross-coupled control (CCC) significantly improves contouring accuracy for linear and circular contours. As geometrical and parametric curves become more popular in modern manufacturing, machining processes with multiaxis motion systems are required, however, the available biaxial CCC cannot be directly applied to arbitrary contours with multiaxis machining systems. In this paper, we propose a novel approach for arbitrary contours by estimating the contouring error vector to efficiently determine the variable gains for CCC. Experimental results for a biaxial motion system indicate that the proposed approach efficiently yields variable gains similar to those in traditional CCC. Furthermore, results on a three-axis CNC machining center show that the present approach significantly improves motion accuracy in multiaxis motion systems.

Micro-motion control on the peak drilling, particularly in 3C industry processing, is difficult for the spindle to precisely follow the high-frequency commands, mainly because the repetitive motion distance is very small and it passes through zero velocity frequently to cause serious problems of friction. Experimental results indicate that the axis is nearly unmoved by applying traditional controllers in practice. By applying the static friction compensation constructed under constant-speed operations, results indicate that it is suitable only when the motion command is slowly-varying in a low frequency range. In this paper, the LuGre model is adopted and a systematic approach is proposed to obtain corresponding modeling coefficients. Results indicate that by applying the controller with the LuGre model, the bandwidth of the velocity loop is greatly improved from 394Hz to 663.7Hz, and the position loop is greatly improved from 9.5 Hz to 113.8 Hz. The LuGre model has also been realized on a DYNA 1007 CNC machine to prove its feasibility. Moreover, the tracking error of its peck drilling is improved 67.5% in RMS and the maximum peak error improvement is 72.0%.Copyright © 2014 by ASME

As messages and nodes over a network increase, delay time in a networked control system (NCS) increases and results in frequent dropout, thereby seriously degrading the performance and stability of NCS. Therefore, effective methods are urgently needed to handle the time delay and dropout effects of NCS. In this paper, a real-time transition probability estimator for the two-state Markov chain model is proposed for online monitoring of the dropout condition by using a short-window technique. Furthermore, under time-varied dropout conditions, the most suitable least-square estimator can be determined in real time by applying intelligent message estimator (IME), and missing data from NCS can be efficiently estimated and restored.

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.

The cross-coupled control (CCC) has been recognized as an efficient motion controller that reduces contouring errors, but theoretical analysis of it is lacking, and there is no systematic design approach for obtaining a CCC system with guaranteed control performance. Consequently, the compensators C in CCC are commonly implemented in a PID structure and their contouring accuracy is usually degraded in real applications under different operating conditions. In an attempt to overcome the CCC design limitations described above, this paper introduces a robust CCC design based on a novel formulation: the contouring error transfer function (CETF), leading to an equivalent formulation as in the feedback control design problem. Then, methods in robust control design can be readily employed to achieve robust CCC with specified stability margins and guaranteed contouring performance. Furthermore, the proposed design has been verified as being internally stable. All provided experimental results indicate that the proposed robust CCC design consistently renders satisfactory contouring accuracy under different operating conditions.

Modern CNC systems are designed with the function of machining arbitrary parametric curves to save massive data communication between CAD/CAM and CNC systems and improve their machining quality. Although available CNC interpolators for parametric curves generally achieve contouring position accuracy, the specified feedrate, which dominates the quality of the machining processes, is not guaranteed during motion. Recently, some approximation results concerning motion speed have been reported [Shpitalni M, Koren Y, Lo CC. Computer-Aided Design 1994;26(11):832–838; Bedi S, Ali I, Quan N. Trans ASME J Engng Industry 1993;115:329–336; Chou JJ, Yang DCH. Trans. ASME J Engng Industry 1991;113:305–310; Chou JJ, Yang DCH. Trans ASME J Engng Industry 1992;114:15–22]. In this paper, by deriving a compensatory parameter, the proposed interpolation algorithm has significantly improved curve speed accuracy. In real applications, the proposed algorithm results in: (1) constant speed; and (2) specified acceleration and deceleration (ACC/DEC) to meet the feedrate commands. The motion accuracy and feasibility of the present interpolator have been verified with a provided non-uniform rational B-spline (NURBS) example.

The zero phase error tracking controller (ZPETC) in motion control, as proposed by Tomizuka (1987) , renders the desirable zero phase error, but with a limited gain response. Moreover, a ZPETC, which is basically in a feedforward control structure, is very sensitive to modeling error. To improve the tracking accuracy of the ZPETC, this paper presents an optimal ZPETC design with a concise polynomial digital prefilter (DPF). The parameters of this well-designed DPF are obtained through the derived L/sub 2/-norm optimization. By cascading the developed DPF to the ZPETC, the resultant optimal ZPETC greatly improves the bandwidth of the tracking control systems while maintaining the zero phase error. Compared with other optimal approaches, the present design leads to much simpler procedures and fewer computations. Furthermore, the proposed optimal ZPETC can be adequately implemented as an adaptive ZPETC by including real-time estimation technique to cope with the external load perturbation and parameter variation. Compared with the other adaptive approaches, the optimal concept is used in the present adaptive ZPETC, and it also renders more accurate results because of its improved magnitude response. Experimental results on a DC servo table with different controllers indicate that when there is no loading, the present optimal ZPETC achieves the best tracking performance. Moreover, the adaptive ZPETC achieves the most satisfactory results when an external load is applied.

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.

The robust diagnostics design has gained more attentions recently in real applications. It is known that the freedom in eigenstructure assignment leads to the well-conditioned design which is robust to unstructured uncertainties (Shen et al., 1995, 1998). Moreover, the unknown input fault detection observer (UIFDO) decouples the known inputs, the structured uncertainties, from the diagnostic residuals. In this paper, we present an unknown input fault isolation observer (UIFIO) based on the UIFDO by using the eigenstructure assignment. It achieves robust fault isolation subject to both structured and unstructured uncertainties. Moreover, the optimal gain matrix of the present diagnostic observer is obtained to improve its robustness without degrading diagnostic performance. Experimental results of an automotive engine show the validity and applicability of the proposed robust UIFIO design.

By using the unknown input decoupling technique, this paper presents a robust fault detection and isolation (FDI) system design for a supersonic wind tunnel. A decoupled fault/residual map is designed in the sensor FDI system to achieve multiple fault isolation for principal sensors. Since the relations between actuator faults and the generated residuals are insignificant, a decoupled fault/residual map for actuator is not achievable. Nevertheless, based on the fault specific directions, single fault isolation can still be achieved for actuators with the proposed FDI system.

A numerical implementation is presented for the eigenstructure assignment approach to the design of a robust fault detection and isolation observer. By formulating the problem of multiple fault isolation in an eigenstructure, wedevelopaparametriccharacterizationofallallowableeigenspaces,whichprovidesadiagnosticobservercapable ofmultiplefaultisolation.Inaddition,awell-conditioneddesignoftheallowableeigenvectorsisshowntoreducethe effectofthesystem unstructured uncertainty.Theresulting diagnosticobserverisrobustto unstructuredmodeling errorswithoutlosingfaultdetectionsensitivity.Aprocedureforthesynthesisofareduced-orderdiagnosticobserver is also presented to increase the computational efe ciency of the proposed observer.

This paper proposes a robust proportional−integral (PI) controller design for multivariable complex processes to achieve both well-decoupled and well-damped output behavior. By reformulating PI-controlled processes in a way similar to the LQG/LTR control design problem, the proposed model matching technique in the first design stage successfully results in the robust PI controller with well-decoupled output behavior and sufficient stability. Moreover, control performance can be further improved to achieve well-damped responses by applying gain modification in a second design stage. Both simulated results using chemical processes and experimental results using a wind tunnel have proven the feasibility of the proposed PI controller design in real applications.

Using the framework of the general structured (GS) observer, we present a straightforward procedure for designing an unknown input observer (UIO) for a linear system subject to unknown inputs or uncertain disturbances. The set of all GS observers insensitive to unknown inputs is derived in this paper. Moreover, an extension of the UIO, called the extended UIO, is developed to estimate both the system state and the unknown input simultaneously. We show the existence conditions of a stable UIO are the same as those of a stable left inverse system. In addition, well-conditioned designs for both the state and unknown input estimations are also explored. Conditions of transmission zeros reveal that to achieve a stable UIO, the uncertain system should be minimum-phase. To overcome this restriction, we adopt a two-delay output stabilized method to design the stabilized UIO without implementing extra sensors. Experimental results for a DC servo motor system demonstrate the applicability of the proposed methodologies.

Based on a development for the unknown input observer (VIO) design, this paper presents a straightforward method of designing a robust fault detection and isolation (FDI) system for uncertain systems with unknown inputs. By exploiting the properties of a nominal model structure, we form a basic set of residuals which is independent of the unknown input but is dependent on the measurements. Then, with this basic residual set, we append a dynamic weighting matrix to the residuals to increase the design freedom for meeting the required detection and isolation performance. Additionally, a generalized residual generator scheme (GRGS) is proposed to synthesize the parity relations for the isolation of faulty sensors in an uncertain system. The proposed strategy is verified through simulation studies performed on the control of a vertical take-off and landing (VTOL) aircraft in the vertical plane.

When machining conditions change significantly, applying parameter-adaptive control to the cutting system by varying the table feedrate allows a constant cutting force to be maintained. Although several controller schemes have been proposed, their cutting control performance is limited especially when the cutting conditions vary significantly. This paper presents an adaptive fuzzy logic control (FLC) developed for cutting processes under various cutting conditions. The controller adopts on-line scaling factors for cases with varied cutting parameters. In addition, a reliable self-learning (SL) algorithm is proposed to achieve even better cutting performance by modifying the adaptive FLC rule base according to properly weighted performance measurements. Both simulation and experimental results show that given a sufficient number of learning cases, the adaptive SL-FLC is effective for a wide range of applications. The successful implementation of the proposed adaptive SL-FLC algorithm on an industrial heavy-duty machining center indicates that the proposed adaptive SL-FLC is feasible for use in manufacturing industries.

Enhancement of unknown input fault detection observer (UIFDO) to obtain unknown input fault isolation observer (UIFIO) is presented in this paper by eigenstructure assignment approach. Not only the unknown inputs are concerned but also the effects due to unstructured uncertainties is adopted and suppressed with well-conditioned eigenstructure assignment. Experimental results of a Nissan commercial engine is illustrated to prove the validity of theoretical derivation.

The indirect rotor field-oriented control with the optimal slip factor adjustment is exploited for the a 0.75kW induction machine (IM) control and it has been successfully implemented on an electric vehicle (EV) to provide satisfactory acceleration and efficiency. To achieve dynamic control of the flux and torque, precise synchronous angle estimation based on the rotor time constant is crucial for stator current decoupling, and thus control performance is highly dependent on the accuracy of parameter identification. Since traditional identification approaches are suffered from difficulty of implementation, a simple and accurate identification process by applying experiments to obtain the rotor time constant corresponding to the maximum acceleration is proposed in this paper. As a low-power IM implemented on EVs is usually overloaded during the acceleration period, the maximum torque per amperage (MTPA) control is thus desirable. A novel control approach by which the optimal slip factor is obtained through experiments for the maximum acceleration and efficient is proposed. Experimental results show that the proposed slip factor adjustment is more suitable to traction control of the EV because of its smooth operating performance.

In this paper, linear and nonlinear control design techniques including: (1) cross-couple control, (2) nonlinear friction compensation, and (3) disturbance observer are suitably integrated to improve control performance in synchronization. The developed controller has been applied to a two-axis motion system with an induction motor and a servo motor, in which they have very different dynamic characteristics. Experimental results indicate that the maximum synchronized error is significantly reduced from 132.1 um to 4.3 um. Moreover, the positional type cross-coupled controller has been realized on a commercial CNC tapping machine to improve the maximum synchronized error. Results of the tapping process have led to synchronization accuracy under 10 um when the spindle speed increases to the CNC maximum speed 6000 rpm to maintain satisfactory tapping processes.

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.

This paper describes the implementation of an integrated control/diagnostic system for an advanced hard disk drive (HDD) servo system. An observer-based state feedback control design with the pole placement technique has been successfully applied to achieve a bandwidth of 688 Hz, which is quite satisfactory at a 4.5 kHz sampling frequency. Experimental results indicate, however, that the performance of this high precision, high-order control system deteriorates seriously when faults occur. Therefore, a fault identification filter (FIDF) was adopted for fault detection of sensor and actuator failures and accommodation of the actuator failure. In cases where either sensor or actuator fault occurs, experimental results indicate that to maintain high precision and control performance for the HDD system, DSP implementation of the high-order integrated control/diagnostic system is necessary. >

With the rapid development and implementation of Internet technologies, well-designed/tuned controllers obtained from control design without network are desired, which can be further realized in remote control systems directly. Theoretically, available networked control system (NCS) designs are developed with a known system model and time delay. However, the nature of network-induced delay is unpredictable, which depends on network protocol and hardware, and available design approaches usually become impractical in real concerns. The study presents an NCS structure with the proposed perfect delay compensation (PDC) scheme, which is constructed with modified butterfly elements to deal with unknown delay effects without system model and delay information. Both analytical and simulation results prove that the proposed model-free PDC scheme effectively compensates for the unknown network-induced delays. Furthermore, the proposed PDC is carried out using Ethernet, and a well-tuned PI controller for the AC servo motor was directly networked to the remote control system. Experimental results indicate that the proposed PDC renders satisfactory and desirable design results in real NCS applications.

An online delay estimation algorithm is adopted for the adaptive Smith predictor in the networked control systems (NCS) design under the significant delay time. However, the Smith predictor is sensitive to parameter uncertainties within the system model and time delay. The quantitative feedback theory (QFT) controller is suitable to cope with parameter uncertainties of the Smith predictor in this paper; moreover, a template expressed in phase and gain for the QFT design has been constructed by considering the bounded variations with the time delay and the external loading. Therefore, the adaptive Smith predictor control scheme with QFT controller provides better tolerance to parameter uncertainties. Both simulation and experimental results on AC servo motor with both the hybrid controller area network (CAN) bus and the Ethernet network have proven the feasibility and improved performance of the proposed NCS.

Network motion control system because of network bandwidth restriction, the sampling period must increase to lead to degrade motion accuracy. This paper regards TCP network as network infrastructure, and the traditional linear interpolation is applied in slave system to make slave system possesses smaller sampling period than in remote system, and then maintain motion precision. About data dropout caused because of network delay, this paper utilizes TCP network guarantee characteristic that message can achieve match SDQ-based message estimator succeeding and accurate estimating the loss message to maintain good motion precision. In simulation, combine linear interpolation mechanism and SDQ-based message estimator, can improve motion NCS tracking accuracy, and under the high frequency motion position commands, there are more apparent improvement results.

This paper integrates the IEEE 802.11 g ad-hoc wireless network and the control area network (CAN) in the present network control systems (NCS) or wireless - NCS (WNCS). Both the TCP and the CAN protocols are adopted as the communication gateway in a remote control system. The time delay between the application layer of the client and the application layer of the remote control target has been measured and analyzed in this paper. Experimental results on an AC 400 W servo motor indicate that the communication jam mainly causes the instability due to the induced time delay. In this paper, by applying the adaptive Smith predictor with the switching sampling time, satisfactory control performance of WNCS can be obtained even though the time delay seriously increases. Moreover, the feasibility of the proposed WNCS has been proven through experimental results.

This paper integrates Ethernet and control area network (CAN) with the TCP/IP communication gateway. The developed system has been applied to a remote control system for an AC 400 W servo motor to verify the proposed adaptive Smith Predictor control method with the time-delay estimation algorithm. The time delay effect, defined as the round-trip time (RTT), between the application layer of the server and the application layer of the client, has been measured and analyzed. Moreover, results indicate that NCS performance is degraded, and may even become unstable mainly due to the serious network time delay in a stochastic nature mainly occurred in the Ethernet. The Smith predictor is adopted to eliminate the constant time delay. However, the delay in a commercial network is time varying and it depends on the number of end users. An adaptive Smith predictor control scheme is developed in this paper by applying the on-line estimation to further improve control performance of the proposed NCS with the integrated Ethernet and CAN buses. Experimental results indicate that the time delay is drifting in both bounded and random natures for the integrated Ethernet+CAN network and the proposed control approach significantly improves motion accuracy as in the NCS for an AC motor-based motion system.

This paper focuses on the design of T-S fuzzy path controller for improving the high-speed tracking accuracy of a four-wheel omnidirectional mobile robot (ODMR). Usually, when an ODMR moves in high speed, the adverse effects induced by Coriolis force significantly deteriorate the tracking performances. In this paper, a T-S fuzzy control designed with both the state feedback and path tracking error is proposed to meet the design specifications. Moreover, a new approach of kinematics inversion considering the nonlinear term of coordinate transform is proposed to simplify the analysis of ODMR motion. Finally, an example is provided to compare the present T-S fuzzy path controller with the well-tuned PID controller. The simulation results indicate that the proposed approach provides much better tracking performances as the speed of ODMR increases.

In network systems, the time-delay effect is unavoidable and it usually degrades system performance. Furthermore, in the real-time network control system (NCS), messages are required to be transmitted on time to meet specifications of the deadline. Otherwise, it leads to data dropout which occurs randomly in real-time NCS control. The data dropout not only degrades performance of the NCS but also causes the NCS to be unstable. In this paper, a second-order motion message estimator is proposed to compensate for the missing messages containing motion commands and measurements, since most motion systems can be described suitably by second-order Newtonian motion law. The dropout rate of the controller area network (CAN) bus has been evaluated in different transmission rate in this paper. The proposed NCS with the message estimator has been successfully implemented on a CNC machine to achieve significantly improved motion accuracy.

In this paper, the adaptive fuzzy control method [1-4] is adopted to improve the traffic network. To deal with traffic during the rush hours, fuzzy controllers commonly switch signals more frequently according to certain circumstances, but it is not practical for real traffic control. In this paper, the adaptive control is concerned to satisfy real applications. The proposed controller adopts more simplified membership functions than those in Kaur and Konga (1994) [5] through analysis of the waiting length; moreover, the number of applied fuzzy rules is also reduced from 86 to 18. To verify the proposed controller through simulation, the parameter setting interface of the software system VISSIM [6] was used to simulate a real traffic intersection and VisVAP was used to achieve the adaptive signal control logic. Given traffic flows as Light (300Veh./hr), Heavy (1000Veh./hr), and Peak (0~1200Veh./hr), simulation results indicate that the delay time of the proposed approach is significantly reduced.

For linear systems with structured uncertainties, the unknown input fault detection observer (UIFDO) provides a robust diagnostic approach by decoupling the fault signals from the unknown input term. However, in real applications, detection performance of the UIFDO degrades seriously as nonlinearities become significant in a wide dynamic operating range. In this paper, a novel UIFDO design and the Takagi-Sugeno (T-S) fuzzy model are combined to provide a T-S fuzzy UIFDO which effectively deals with nonlinear fault detection problems under structured uncertainties and input disturbance. Moreover, by applying the linear matrix inequality (LMT) technique, linear observer gains for each rule of the T-S fuzzy UIFDO can be obtained to guarantee the global stability of the system. Finally, a nonlinear benchmark example is provided to illustrate the proposed design procedures

Using the framework of the general structured observer, we present a straightforward procedure for designing an unknown input observer (UIO) for a linear system subject to unknown inputs or uncertain disturbances. Necessary and sufficient conditions in terms of the transmission zeros are provided for the existence of a full-order UIO capable of producing an asymptotic estimate of the state. Moreover, an extension of the UIO, called the extended UIO, is developed to estimate both the system state and the unknown input simultaneously. Experimental results for a DC servo motor system demonstrate the applicability of the proposed methodologies.

The error resources of precise motion control systems are basically categorized into linear and nonlinear effects. To pursue the motion precision of industrial CNC machine tools, This work proposes an integrated control structure with modular algorithms including both the linear control and the nonlinear compensation. In linear control design, This work applies three algorithms: (1) the feedforward control to deal with the tracking error, (2) the cross-coupled control (CCC) to reduce the contouring error, and (3) the digital disturbance observer (DDOB) to lessen the effects of modeling error and disturbance in real applications. Results indicate that the linear motion controller achieves both greatly improved tracking and contouring accuracy by reducing the servo lags and mismatched dynamics of different axes. However, the slip-stick effect due to friction still exists and cannot be removed by applying the linear motion controller only. This work further integrates the nonlinear compensator and develops friction estimation and compensation rules for CNC machine tools. The DSP microprocessors are suitable to implement all linear and nonlinear algorithms and the proposed controllers have been successfully applied to industrial CNC machine tools. Experimental results in various speed commands indicate that the proposed integrated controller reliably achieves 7 /spl mu/m contouring accuracy in CNC motion control.

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.

For remote-controlled multi-recipe processes, certain issued commands may lead to undesired resource conflicts and deadlock states. Moreover, as a result of the communication delay and packet loss in the Internet, remote control of a group of certain steps are recommended rather than control of each step. For these Web-based control systems, this paper proposes a three-level architecture for hierarchical supervision. In the upper supervisory level, the supervisory agent guarantees that issued commands from the remote manager, in the middle command level, satisfy the resource sharing and deadlock-free requirements when executing a number of concurrent recipes, while the local controller, in the lower control level, performs the corresponding detailed operations to meet the requested tasks. In the present approach, Petri nets (PNs) are used to model, design, and verify the supervisory agent and local controller, and then, Java technology and ladder logic diagrams (LLDs) are adopted for implementation to achieve online supervision of the remote-controlled processes. To demonstrate the practicability of the developed supervisory approach, we apply it to a three-recipe flexible manufacturing system (FMS) controlled over the Internet.

Recently, designs for the automated highway systems (AHS) to improve the safety and efficiency of highways have attracted much attention. However, such large-scale and complex dynamic systems present a number of control issues. Part of the complication comes from the hybrid nature of these systems, which consists of both time-driven and event-driven dynamics. In this paper, an object-oriented approach towards a hybrid controller design for automated vehicles in an AHS is proposed. First, the unified modeling language (UML) is extended to model the hybrid controller with a clear and natural representation of the discrete event and continuous time behaviors. Then, since the AHS is typically a multi-agent system, the simulation of which is suitable to implementation by multi-threaded programming, a Java-based library is further developed to support the implementation. In our framework, Java provides an implementation path, while the extended UML provides a reverse engineering path for the hybrid controller design.

Recently, methods have been proposed for obtaining the ladder logic diagram (LLD) based on the Petri net (PN). However, those resulting LLD are usually not in compact forms. Moreover, forming the PN structures to model manufacturing processes is not straightforward. In this paper, we propose a simplified Petri net controller (SPNC) by introducing sensor states into the PN. A compact LLD can be then obtained through the token passing logic (TPL). By employing the integration definition language 0 (IDEF0) technique, we obtain the SPNC structure sequentially through material flow diagrams and information flow diagrams. The result of an integrated IPTL (IDEF0/SPNC/TPL/LLD) algorithm, including the IDEF0, SPNC, and TPL tools, leads to the standard IEC1131-3 LLD for PLC implementation. An example of a mark stamping system is provided to illustrate the developed design approach.