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The disturbance observer is one of the useful tools for estimating the contact force between the subject body and the environment in robotic and mechatronic systems. This paper introduced a novel automatic office-based ear surgical device for the treatment of Otitis Media with Effusion (OME) under the guidance of force sensing information. Since the force sensing information must be reliable so as to ensure the safety of the device, a contact force estimation method based on the disturbance observer is proposed. The system model is built and a control strategy is proposed and developed. In the control strategy, a composite motion controller for an ultrasonic motor (USM) stage is presented, and then the design and the stability analysis of an advanced disturbance observer is given. Furthermore, a contact estimator and a failure detector, aiming to enhance the safety and reliability enhancement, are designed. Finally, the proposed control strategy is studied with both simulation and experiment. The experimental results show that the advanced disturbance observer can estimate the actual contact force correctly and precisely, and the disturbance observer based force estimation and failure detection method is feasible which can be used in force sensing, contact detection and fault diagnosis.

Rehabilitation robots, by necessity, have direct physical interaction with humans. Physical interaction affects the controlled variables and may even cause system instability. Thus, human–robot interaction control design is critical in rehabilitation robotics research. This paper presents an interaction control strategy for a gait rehabilitation robot. The robot is driven by a novel compact series elastic actuator, which provides intrinsic compliance and backdrivablility for safe human–robot interaction. The control design is based on the actuator model with consideration of interaction dynamics. It consists mainly of human interaction compensation, friction compensation, and is enhanced with a disturbance observer. Such a control scheme enables the robot to achieve low output impedance when operating in human-in-charge mode and achieve accurate force tracking when operating in force control mode. Due to the direct physical interaction with humans, the controller design must also meet the stability requirement. A theoretical proof is provided to show the guaranteed stability of the closed-loop system under the proposed controller. The proposed design is verified with an ankle robot in walking experiments. The results can be readily extended to other rehabilitation and assistive robots driven with compliant actuators without much difficulty.

In this paper, we explore the UAV loss detection and auto-replacement scheme in a multi UAV system. The developed scheme is based on the concept of cooperative multi UAV control, where the cooperation is achieved by broadcasting heartbeats (HBs) and information fusion technology. We first propose the UAV loss detection method by checking the HB time. Subsequently, we present the UAV auto-replacement which is based on a contention protocol. Next, we propose the recovery algorithm for the lost UAV rejoining the UAV group. Finally, case studies are given to demonstrate the proposed scheme.

Rehabilitation robots have direct physical interaction with human body. Ideally, actuators for rehabilitation robots should be compliant, force controllable, and back drivable due to safety and control considerations. Series Elastic Actuators (SEA) offers many advantages for these applications and various designs have been developed. However, current SEA designs face a common performance limitation due to the compromise on the spring stiffness selection. This paper presents a novel compact compliant force control actuator design for portable rehabilitation robots to overcome the performance limitations of current SEAs. Our design consists of a servomotor, a ball screw, a torsional spring between the motor and the ball screw, and a set of translational springs between the ball screw nut and the external load. The soft translational springs are used to handle the low force operation, while the torsional spring with high effective stiffness is used to deal with the large force operation. It is a challenging task to design the controller for such a novel design as the control system needs to handle both the force ranges. In this paper, we develop the force control strategy for this actuator. First, two dynamical models of the actuator are established based on different force ranges. Second, we propose an optimal control with friction compensation and disturbance rejection which is enhanced by a feedforward control for the low force range. The proposed optimal control with feedforward term is also extended to the high force range. Third, a switching control strategy is proposed to handle a transition between low force and high force control. The mathematical proof is given to ensure the stability of the closed-loop system under the proposed switching control. Finally, the proposed method is validated with experimental results on a prototype of the actuator system and is also verified with an ankle robot in walking experiments.

This paper presents the work to address the problem of student participation in a class. The work is particularly applied to a design-centric mechatronics-related classes, using web, smartphone, and mechatronics-related technology. The specific issues to be targeted on are the irregular attendance and the low participation of students during classes using on-the-spot questions and answers on design-centric subjects to improve and adaptively redirect the orientation of targeted students as well as the whole class. The approach and system have been developed with Android smartphone-based application and Apache Tomcat-based server. This allows data storage and opens up possibility for statistical analysis in the future.

The treatment of a common disease called “Otitis Media with Effusion (OME)” involves the surgeon inserting a grommet in the eardrum to bypass the Eustachian tube for draining fluid when medication fails. In this paper, a novel device for myringotomy and grommet insertion is first designed and introduced. Due to the advantages of high precision and fast response, a 2-DOF ultrasonic piezomotor (USM) stage is chosen to provide the motion sequences of the device, especially a precise path tracking during the grommet insertion. This paper briefly presents the mechanical design of the device and the configuration and control of the 2-DOF USM stage. The model of the USM consisting of a linear and nonlinear term is built. A PID controller is used as the main controller and tuned with the help of LQR technique. Since there are nonlinear dynamics caused by friction and hysteresis existing in the system, a nonlinear compensation including a sign function and sliding mode control is designed to reject the nonlinearity. Moreover, a decoupling controller is designed to eliminate the coupling effects between the two USM stages. The experimental results show that the LQR-assisted PID controller with compensation can achieve very good system performance and the decoupling controller can further improve the performance.

The aim of this paper is to develop an intelligent diagnosis method for fault detection and isolation in induction motors. We consider failures in three components of induction motor: bearing, stator winding and rotor winding. Firstly, a model-based nonlinear observer in the proposed method is designed based on available information. The fault detection decision is carried out by comparing the model-based observer speed with their signatures. Secondly, multiple state observers are constructed based on possible fault function set. The fault isolation decision is made by checking each residual generated by observer state estimation. Finally, simulation tests are given to verify the effectiveness of the proposed fault diagnosis scheme.

In-vitro fertilization (IVF) and related technologies are arguably the most challenging of all cell culture applications. This paper introduces a new design of an integrated oocyte retrieval solution before the oocytes are further put into laboratory processing during IVF treatment. It facilitates the surgery operation and addresses the temperature inaccuracy of follicular fluid during the transfer to the patient's body. The mechanical design is implemented into a medical-standard conforming platform. An accurate temperature estimation and optimization scheme is also proposed. Comparison before and after the introduction of the new prototype under various operating conditions reveals a significant improvement in performance. This yields a potential application for the medical/healthcare industry.

In this paper, we propose a control method for an air bearing motion stage complemented eddy current braking. The proposed control scheme uses two control inputs to handle the nonlinear air bearing system: one is P control plus a feedforward term and one is eddy current feedback. The stability analysis is discussed involving two cases: (1) accurate model, (2) uncertain model. The experimental results are given to further verify the effectiveness of the proposed method.

In this paper, we consider the friction compensation problem for a class of mechanical systems. The friction behavior is described by a nonlinear dynamical model. Since it is difficult to know the nonlinear parts in the frictional model accurately, two neural networks (NNs) are employed in the proposed intelligent controller. Due to the learning capability of the NNs, the designed NN controller can compensate the effects of the nonlinear friction. Stability of the thus proposed learning control system is guaranteed by a rigid proof. Simulation and experimental results are provided to verify the effectiveness of the proposed intelligent scheme.

This paper aims to identify friction-impeded servo-mechanical systems using a time-domain based approach with a multiple-relay feedback apparatus. By converting the closed-loop system into a triple-relay feedback system, switching conditions of a stable limit cycle are obtained. Following by this, stable oscillations are excited by choosing suitable relay gains. Hence, the level of Coulomb friction and other linear parameters are identified by numerically solving a set of equations with data from just a single limit cycle experiment. This method is also robust to measurement noise. Simulation and real-time experiments on a DC motor show the practical appeal of the proposed method.

In this paper, the singular value decomposition (SVD) based identification and compensation of the hysteretic phenomenon in piezo actuators are addressed using a Preisach model. First, this paper presents an SVD-based least squares algorithm and a revision approach of the identification through updating the SVD. With the identified parameters and a log of the memory curve, a Preisach-based inversion compensator is constructed which is complemented with a feedback controller to address the inevitable and residual modeling errors. Experimental results are furnished for both the identification and compensation approaches. The Preisach-based feedforward controller significantly improves the tracking performance and reduces the root-mean-square (RMS) tracking error of a PID controller by 76.7% and 89% at 1 Hz and 25 Hz, respectively. With the proposed composite controller, the percent-RMS errors at 1 Hz and 25 Hz are reduced to 0.035% and 0.31%, respectively.

In this paper, an automatic office-based ear surgical device for the treatment of Otitis Media with Effusion (OME) which overcomes the disadvantages of the conventional surgical treatment is introduced. Since the device carries out the surgery automatically under the guidance of force sensing information, this information must be reliable so that the safety of the device can be ensured. Hence, a force detection method based on the disturbance observer is proposed in this paper. To overcome the disadvantages of the conventional disturbance observer, an advanced disturbance observer is designed and its stability is analyzed. Finally, the simulation study on the disturbance observer is carried out. The results show that the advanced disturbance observer can estimate the disturbance correctly and precisely.

This paper describes the design and proof of concept for an active eddy current damper which is integrated into a single-axis linear motor. Although developments on active eddy current damper are well documented, none has been implemented in a linear motor. The advantage of such a system is two-fold. Firstly, the relative motion between the magnets and the conducting sheet produces eddy currents resulting in an electromagnetic force opposing the direction of motion; which can be utilized to suppress vibrations. Secondly, it is possible to enhance the damping effect of the system; Due to environmental noise, it is normally not possible to increase the D coefficient in a PID controller as much as desirable. The damper is thus able to supplement this damping effect to improve settling time. Here, we will present the damper design as well as the preliminary experiment results for both vibration suppression and motion damping.

The tracking performance of a motion system based on a permanent-magnet linear motor (PMLM) is greatly affected by nonlinearities present, such as force ripples and frictions. Although various identification and compensation schemes haven been reported for the PMLM, to the authors' best knowledge, no direct and unified modeling method for force ripples and friction is available till now. This paper proposes a new method to identify various linear and nonlinear parameters in PMLM, using a hysteretic relay feedback. Dual-input describing functions are imported to leverage on the biased limit cycles generated by even nonlinearities due to force ripple. The explicit formulae, derived from the harmonic balance condition, enable direct computation of model parameters with a minimum number of relay experiments. Simulation results and real-time experiments will be presented to verify the practical appeal of proposed method in precision motion control.

Linear drives (LDs) are designed to meet industrial applications like factory automation, material testing, packaging, pumping, and stamping. Because of the complexity of LDs, it is very important to analyze the dynamics and characteristics of the controlled systems before actual testing. The purpose of this paper is to build a hardware-in-the-loop (HIL) simulator that can provide an effective platform for developing and testing real-time LD systems. The HIL system comprises of a dynamical friction model, a dSPACE control system, and a human-machine interface. The developed system is tested by a proportional-integral-derivative controller.

The application of a dual-relay feedback approach toward the identification of a model of servomechanical system will be presented in this paper. The model will capture the linear dynamics of the system, as well as the frictional forces affecting the system, through a comprehensive friction model that includes static friction, Coulomb friction, viscous friction, and the boundary lubrication velocity. This friction model is able to adequately describe the friction property when the servo system runs under both low- and high-velocity modes. Properties of the oscillations induced under the dual relay will be presented, based on which insights for the selection of relay parameters can be drawn. A systematic set of procedures to derive all the parameters of the model will be furnished. The model will be directly useful in the design of the feedback controller and feedforward friction compensator. Results from the simulation and experiment will be presented to illustrate the practical appeal of the proposed method.

In this paper, we consider the monitoring and control of linear drives subject to nonlinear uncertainties. First, we propose a residual generator based on sliding mode, which can be used to monitor the linear drive. When a fault occurs, the monitoring system will generate and transmit an alert signal to the controller. Second, we design a sliding-mode control system which can work in two modes: normal control and fault-tolerant control. Finally, the proposed method is tested in a real linear drive comprising a rotary dc motor using a screw rod to translate rotation into translation.

In this paper, we consider the adaptive control problem for piezoelectric actuators with nonlinear uncertainties. The controller consists of two parts: sliding mode and adaptive component. The sliding-mode part rejects dominant uncertainties, while the adaptive component is continuously refined based on just prevailing input and output signals. The stability of the designed control system can be guaranteed by a rigorous proof. Simulation and real-time experimental results are provided to verify the effectiveness of the proposed scheme.

In this paper, a new form of Repetitive Control (RC) is proposed which is applicable to an extended class of systems, including time-delay systems. A new convergence condition which is necessary and sufficient will be derived for this RC. Simulation examples will illustrate the practical applications of the results to process control problems.

The tracking performance of motion system based on permanent magnet linear motor is greatly affected by nonlinearities present, such as force ripples and frictions. Although various identification and compensation schemes haven been reported for PMLM, to the authors’ best knowledge, no direct and unified modeling method for force ripples and friction is available till now. This paper proposes a new method to identify various linear and nonlinear parameters in PMLM, using a hysteretic relay feedback. Dual-input describing functions are imported to leverage on the biased limit cycles generated by even-nonlinearities due to force ripple. The explicit formulae, derived from the harmonic balance condition, enable direct computation of model parameters with a minimum number of relay experiments. Simulation results and realtime experiments will be presented to verify the practical appeal of proposed method in precision motion control.

In this paper, we develop a decentralized neural network control design for robotic systems. Using this design, it is not necessary to derive the robotic dynamical system (robotic model) for the control of each of the robotic components, as in traditional robot control. The advantage of the proposed neural network controller is that, under a mild assumption, unknown nonlinear dynamics such as inertia matrix and Coriolis/centripetal matrix and friction, as well as interconnections with arbitrary nonlinear bounds can be accommodated with on-line learning.

Recent developments in nuclear reprogramming and intracytoplasmic sperm injection reflect an increasing need for more advanced and automatic micromanipulation technologies. In this paper, we present an automatic cell injection system, which is capable of visually monitoring the injecting process and controlling the microactuators. Traditionally, cell injection was manually operated, and it was laborious, time consuming, of low accuracy, and prone to contamination due to the handling requirements. An automatic and efficient strategy is required to eliminate these drawbacks. In this paper, a system is developed where the injection process is monitored and controlled automatically via integration of a vision system to an injector manipulation system. The cell is located, and the pipette is positioned and driven by the algorithm to achieve effective penetration. The precision achieved is physically proven to be within a good tolerance range.

There is a need to evaluate the effectiveness of a remote sensor system for pedestrian detection in a vehicle traffic environment. For this purpose, the car-pedestrian accident scenarios were analyzed using selected data from the Swedish Traffic Accident Data Acquisition (STRADA), a database developed by collecting accident data from the police and hospitals. The two most common scenarios were identified as cars entering and leaving intersections colliding with pedestrians crossing the road. The knowledge of these two scenarios was then developed in terms of the factors such as the pedestrian's trajectory, the pedestrian's speed, the car's trajectory and the car's velocity. Based on the developed knowledge, a mathematical model was presented and the remote pedestrian sensor system was evaluated by using this model. It was found that the sensor system can detect almost all the pedestrians in these two scenarios in time, in the case where the detective angle was larger than 60 degrees.

This paper describes an adaptive control scheme developed for precision control of DC permanent magnet linear motors (PMLM). A sliding surface is defined on which a self-tuning version of robust control capable of achieving tight set-point regulation is developed, where the control gains are tuned using an adaptive algorithm. Parameter and states convergence properties of the adaptive controller are derived based on the control law formulated. Finally, simulation study and a real-time experiment are provided to evaluate the performance of the proposed control system.

This paper describes a robust adaptive control method for positioning piezoelectric actuators (ultrasonic motor) to achieve highly precise motion. The model employed to describe the motor is a second-order linear model plus a nonlinear part comprising predominantly of a dynamical hysteresis. Based on the model, the overall control algorithm uses a PID component and an adaptive robust component for estimating the parameters of the piezo motor model. The adaptive component is continuously refined based on just prevailing input and output signals. Real-time experimental results are provided to verify the effectiveness of the proposed scheme when applied to high precision motion trajectory tracking such as Intracytoplasmic Sperm Injection (ICSI).

In this paper, fault diagnosis and accommodation control are developed for robotic systems. First, a nonlinear observer in the proposed method is designed based on the available model. The fault detection is carried out by comparing the observer states with their signatures. Secondly, state observers are constructed based on possible fault function sets. Thirdly, the accommodation control design is developed using a normal controller plus a neural network compensator to capture the nonlinear characteristics of faults. Finally, if the fault isolation is completed successfully, the second fault accommodation controller is presented based on the fault information obtained by the isolation scheme.

A pedestrian contact sensor in the car bumper is a potential solution to trigger an active hood system. Because of the high level of temperature dependency for the bumper foam stiffness, the sensor output can be unstable at varying temperatures. A new contact sensor was, therefore, developed to provide a temperature-independent measurement for pedestrian impacts. This study analysed the performance of the bumper-pedestrian contact sensor system. First, a baseline finite element (FE) bumper model of a production car was developed and validated. On the basis of the baseline model, an improved bumper model was subsequently developed to meet the requirements of the lower leg form impact tests proposed by Working Group 17 of the European Enhanced Vehicle-safety Committee. Second, an FE human lower extremity model was developed. Using this model, the baseline and improved bumper models were further evaluated in terms of the predicted knee ligament raptures and long bone fractures. Finally, the new contact sensor was built into the improved bumper model. A performance study was then conducted to evaluate the sensor effectiveness. Consequently, a better diameter for the sensor tube was identified in terms of the temperature stability and mass sensitivity of the sensor output.

This paper presents the application of self-sensing actuation (SSA) to facilitate the implementation of piezoelectric actuator in an intelligent mechatronic system. SSA is a technique to employ smart materials, such as piezoelectric materials, simultaneously as a sensor and an actuator; thereby increasing the level of integration of the system. The piezoelectric actuator is equipped with an exclusive adaptive controller amidst its nonlinearities and system's disturbance. The application area to be discussed is a microdispensing system, which is an example of a micromanufacturing process, combining a fluidic system and a positioning system.

In this paper, a fault detection and accommodation scheme is designed, which is applicable to a large class of nonlinear systems. The nonlinear observer is designed to enable the detection of fault occurrences through comparison of observed states with their signatures. Under such circumstances, when a component fails, the fault accommodation control will be activated to compensate the effects of the fault function.

In metal cutting processes, an effective control system, which depends on a suitably developed scheme or set of algorithms can maintain machine tools in good condition. In this paper, an approach is developed for cutting force control of CNC machine. Several linear models are identified based on different working conditions. A dominant model plus uncertain terms is derived from these model set, to yield the necessary and key information from the system. Subsequently, it is used as a state estimator, and robust control is carried out by using the observed variables and cutting force. The developed approach is applied to a milling machine center. Examples taken from experimental tests shown that the developed approach is effective for the uncertain CNC machine.

The modeling and control of two piezoelectric actuators (PAs), with an objective application towards intracytoplasmic sperm injection (ICSI), is addressed in this paper. The PAs are used to realizing the fast and precise movements of an injector so as to penetrate an oocyte (egg cell) with precision and without causing a large deformation. Two specific PA designs are considered for this application: linear reciprocating and partially rotating. General models are presented for the purpose of control system design for both designs. To address the nonlinearities and uncertainties of the actuators, as represented in the model, an adaptive controller is proposed to yield robust control performance. Application results are presented and discussed in this paper. Successful penetration of the zona pellucida (cell membrane) of the oocyte to the ICSI problem has been achieved with both designs and the merits and demerits of both configuration are duly discussed.

While manual ICSI has been able to accomplish artificial fertilization rather satisfactorily, it has also been associated with several drawbacks inherited from its manual manner of operation. Piezo-assisted ICSI is currently gaining attention and preference because of its ability to perform sperm injection in a precise manner, which has significantly improved the result. A number of piezo-actuators for this purpose have been proposed. This paper discusses the publications and patents pertaining to this application, as well as a proposed device to further improve the result.

Railway safety is a very complicated subject, which is determined by numerous aspects including human error. Many of the railway risk assessment techniques currently used are comparatively mature tools. However, in many circumstances, the application of these tools may not give satisfactory results because the risk data are incomplete or there is a high level of uncertainty involved in the risk data. This article presents a risk assessment methodology for conducting systematic risk assessment using fuzzy reasoning approach and fuzzy analytical hierarchy decision-making process. In this method, qualitative descriptors are employed to describe frequency of occurrence, consequence severity, weight factor, and risk level. The proposed risk assessment method can evaluate both qualitative and quantitative risk data, and information associated with railway operation efficiently and effectively. The outcomes of risk assessment are represented as the risk degrees and the defined risk categories of risk levels (RLs) with a belief of percentage, which provide very useful risk information to decision makers. This will provide railway risk analysts, managers, and engineers with a method and tool to improve their safety management and set safety standards. A case study of risk assessment of shunting at Waterloo depot is used to illustrate the application of the proposed methodology.

In metal cutting processes, an effective monitoring system, which depends on a suitably developed scheme or set of algorithms can maintain machine tools in good condition and delay the occurrence of tool wear. In this paper, an approach is developed for fault detection and diagnosis based on an observer model of an uncertain linear system. A robust observer is designed, using the derived uncertain linear model, to yield the necessary and key information from the system. Subsequently, it is used as a state (tool wear) estimator, and fault detection is carried out by using the observed variables and cutting force. The developed approach is applied to milling machine center. Several linear models are identified based on different working conditions. A dominant model plus uncertain terms is derived from these model set and used as an observer. Threshold values are proposed for detecting the fault of the milling machine. Examples taken from experimental tests shown that the developed approach is effective for the fault detection. The approach can be used for fault detection of failures arising from sensor or actuator malfunction.

In this paper, a disturbance compensation scheme is incorporated into a predictive control scheme using a repetitive learning approach. It has the following contributions. First, based on the assumption of the presence of both state and output disturbances, a predictive control algorithm is derived. Secondly, to estimate the disturbances, two feedforward disturbance learning schemes are proposed. Thirdly, the rigid mathematic proof is given to guarantee the convergence of the tracking error under the proposed disturbance learning laws used in conjunction with the predictive controller formulated. Finally, simulation results are provided to illustrate the good performance achievable by the proposed control law.

The current treatment of otitis media with effusion (OME) when medication fails is to surgically insert a grommet tube in the tympanic membrane. A novel precision surgical device has been developed, which allows tube insertion to be accomplished in an office setting. The device leverages on a piezoelectric ultrasonic motor (USM) stage to facilitate the motion sequences for the procedures. The core engine of the device is in the USM motion controller to achieve the high precision, fast response, and repeatability necessary to allow these medical procedures to be efficiently and successfully done with minimum trauma to the patient. This paper focuses on the controller design for the USM to meet the unique set of specifications to apply the surgical device optimally on patient with OME. A model of the USM is first built and identified. A proportional-integral-derivative (PID) controller is used as the main tracking controller with the parameters derived optimally using an linear-quadratic regulator (LQR)-assisted tuning approach. A sign function compensator acts to remove nonlinear dynamics due mainly to friction and a sliding mode controller further rejects remnant uncertainty and disturbance. The experimental results show that the constituent control components fulfill their respective functions well, and collectively, the composite controller is effective toward delivering the level of control performance to meet the objectives for the medical procedures.

To clearly understand passenger car structure's crashworthiness in typical side impacts of pole and moving deformable barrier (MDB) impact modes, which could assist the establishment of Chinese vehicle side impact safety regulations, a full midsized car finite element model, calibrated by pole side impact test, was built and the pole side impact according to European New Car Assessment Program (EuroNCAP) and the MDB side impact according to ECE R95 regulations were simulated with LS-DYNA. The accelerations and the structure deformations from simulations were compared. It can be concluded that the pole side impact focuses primarily on side structure crashworthiness as a result of large intrusions, while the MDB side impact focuses primarily on full side structure crashworthiness. Accordingly, occupant protection strategies focus on different aspects to improve side impact safety. In the pole side impact the objective is to maintain the passenger compartment and protect the passenger's head from impacting the pole, while in the MDB side impact the objective is to protect the full human body. In the design of the car side structures, at least these two tests should be considered for assessing their side impact crashworthiness. Conducting these two side impact tests as certified tests provides insights into car safety during side impacts.

There is a growing trend in developing the wireless machine-to-machine (M2M) communication for factory automation. Currently, most wireless protocols for infrastructureless mobile ad-hoc networks focus on the mobility issue and are mainly suitable for narrowband radio devices. The mechanisms for route update and discovery that work well for wireless mobile ad-hoc networks prove to be redundant and instead add to processing overheads in a static wireless factory setting. This paper presents the development and implementation of a new wireless routing protocol, Bluewave, that caters specifically to wireless communication between machines in a factory setting. Bluewave utilizes features of Bluetooth technology when performing the route setup. The merits of the proposed protocol, in terms of shorter initialization time and route setup time, are duly discussed. A case study illustrating the application of Bluewave to an online condition-based maintenance scenario is presented. Experimental results obtained are furnished to show the viability of Bluewave in industrial automation

This paper presents a control algorithm for a platoon of vehicles. We employ the radial basis function neural networks (NNs) to approximate unknown vehicle dynamics. A direct adaptive method used to update the NN weights on-line is proposed. It is shown that the proposed controller is of the decentralized type and ensures platoon stability. The performance of the controller is illustrated by simulations.

A learning control scheme is proposed which is suitable for high-precision and repetitive motion control applications. It comprises of a self-tuning radial basis function (RBF) network operating in parallel with an iterative learning control (ILC) component. Unlike the usual ILC scheme which adapts a feedforward control signal to achieve improved tracking performance over time, the proposed scheme iteratively adjusts the reference signal. The RBF network is employed as a nonlinear function estimator to model the tracking error over a cycle, and this error model is subsequently used implicitly in the iterative adaptation of the reference signal over the next cycle. The ILC component further enhances the tracking performance, particularly over the sections of the trajectory where the RBF network is less adequate in its modeling function. Simulation examples and real-time experimental results are fully furnished to elaborate the various highlights of the proposed method.

High-precision operation in gantry systems is required to meet higher demands on positioning accuracy in a wide range of applications such as circuit assembly, precision metrology, and wafer stepping. In this paper, the experimental study of an observer-augmented composite control scheme for coordinated motion control of moving gantry stages for precision applications is presented. The scheme will be implemented and compared to other control schemes currently available for this purpose, including a master-slave and a set-point coordinated scheme. Experimental results will illustrate the enhanced performance of the fully coordinated control scheme with respect to tight trajectory tracking purposes.

This paper presents a robust control method for servo mechanical systems, based on a mixed PID/adaptive algorithm. A second-order linear dominant model is considered with an unmodeled part of dynamics that is possibly nonlinear and time-varying. The PID part of the controller is designed to stabilize the dominant model. The adaptive part of the controller is used to compensate for the deviation of the system characteristics from the dominant linear model to achieve performance enhancement. The advantage of the proposed controller is that it can cope with strong nonlinearities in the system while still using the PID control structure which is well known to many control engineers. The proposed control scheme guarantees the boundedness of the system states and parameter estimation.

In this paper, an adaptive neural network (NN) backstepping technique is developed for tracking control of a class of nonlinear systems. NNs are used to compensate for the unknown nonlinear functions in the system. A systematic backstepping approach is established to synthesize the adaptive NN control scheme that ensures the boundedness of all the signals in the closed-loop system, and yields a small tracking error. The issue of transient performance is also addressed under an analytical framework. The effectiveness of the proposed scheme is demonstrated by computer simulations. Copyright © 2004 John Wiley & Sons, Ltd.

This paper presents a new compensation technique for a time-delay friction model that captures the effect of frictional memory. The proposed control utilizes a proportional-derivative (PD) control structure and an adaptive estimate of the friction force. Specifically, a radial basis function (RBF) is used to compensate the effects of the non-linearly occurring parameters in the friction model. Simulation results verify the theory and show that the method can significantly improve the tracking performance of a control system in which it is used.

In this paper, we present a decentralized neural network (NN) adaptive technique for control of robot manipulators in the presence of unknown non-linear functions. Radial basis function NNs are used to approximate the non-linear functions to include the case of both parametric and dynamic uncertainty in each subsystem. The robustifying terms are added to the controllers to overcome the effects of the interconnections. The stability can be guaranteed by using a rigid proof. Finally, simulation is given to illustrate the effectiveness of the proposed algorithm.

In this paper, we propose a robust self-tuning PID controller suitable for nonlinear systems. The control system employs a preload relay (P_Relay) in series with a PID controller. The P_Relay ensures a high gain to yield a robust performance. However, it also incurs a chattering phenomenon. In this paper, instead of viewing the chattering as an undesirable yet inevitable feature, we use it as a naturally occurring signal for tuning and re-tuning the PID controller as the operating regime digresses. No other explicit input signal is required. Once the PID controller is tuned for a particular operating point, the relay may be disabled and chattering ceases correspondingly. However, it is invoked when there is a change in setpoint to another operating regime. In this way, the approach is also applicable to time-varying systems as the PID tuning can be continuous, based on the latest set of chattering characteristics. Analysis is provided on the stability properties of the control scheme. Simulation results for the level control of fluid in a spherical tank using the scheme are also presented.

In this paper, the development of an integrated and open-architecture precision motion control system is presented. The control system is generally applicable, but it is developed with a particular focus on direct drive servo systems based on linear motors. The overall control system is comprehensive, comprising of various selected control and instrumentation components, integrated within a configuration of hardware architecture centred around a dSPACE DS1004 DSP processor board. These components include a precision composite controller (comprising of feedforward and feedback control), a disturbance observer, an adaptive notch filter, and a geometrical error compensator. The hardware architecture, software development platform, user interface, and all constituent control components will be elaborated on in the paper.

Robotic systems are widely used in industry. Preventive maintenance of electrical machine systems plays a very important role in the industrial life. This requires monitoring their operations on-line which can detect a fault as it occurs and diagnosing the malfunction of a faulty component. In this paper, we present a fault diagnosis method for robotic systems. First, the fault monitoring is designed to enable the system to detect a fault occurrence based on the residual generator and parameter convergence. Subsequently, the fault isolation algorithm is designed based on known fault types. If the isolation scheme is not successful, the fault diagnosis incorporating neural network information is activated. Finally, case study is given to illustrate the effectiveness of the proposed method.

This paper presents for the first time, the design of an adaptive controller for the control of the ram velocity of an injection moulding machine, based on a physical nonlinear model which describes the filling phase in detail. Polynomial series are first used to simplify the mathematical model such that the system parameters and the system states are essentially separated. The errors arising from the approximation are reduced with the introduction of certain robustification terms into the control law representative of the residual effects. A sliding surface is subsequently defined and a self-tuning version of robust control capable of achieving tight set-point regulation is proposed in which the control gains are tuned by an adaptive algorithm. The convergence property of the adaptive controller is proven in the paper. Finally, simulations are provided to evaluate the performance of the proposed control system.