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This paper proposes a robotic assistance control scheme for intuitive teaching tasks by integrating the motion intention of human and real-time hand impedance compensation based upon a fuzzy RBF (Radial Basis Function) compensator. The motion intention of a human is estimated using a feedforward neural network. The parameters of the proposed fuzzy RBF hand impedance compensator are adjusted by considering hand impedance and robot dynamics. Three robotic assistance control schemes are compared: 1) robot without an impedance compensator; 2) robot with a constant-parameter impedance compensator; 3) robot with a fuzzy RBF hand impedance compensator. Several experiments have been conducted to verify the effectiveness of the proposed approach by comparing the contour error, exerted force and task time spent on teaching tasks. Experimental results indicate that the proposed fuzzy RBF hand impedance compensator has the best assistance results among the tested robotic assistance control schemes.

In the roll-to-roll manufacturing process, transmission smoothness of the substrate and positioning accuracy are two factors that may affect the product quality. As a result, when developing roll-t...

Industrial applications such as pick-and-place tasks and CNC machining often involve repetitive motions that may contain periodic disturbances. Due to the periodic nature of these applications, the idea of iterative learning control can be exploited to cope with external periodic disturbances so as to improve system performance. In addition, in order to ensure satisfactory motion accuracy for operation scenarios that may encounter significant disturbance, (e.g., machining and polishing), a robust controller is essential. In particular, iterative learning sliding mode control (ILSMC) is shown to be suitable for control applications that encounter periodic disturbances. However, when the disturbance contains high frequency components, ILSMC may become less effective in compensating for external disturbances if its velocity estimation is not accurate enough. In order to cope with the aforementioned problem, this paper develops a gradient-descent-based velocity observer with a residual displacement compensation term to provide accurate velocity feedback to be used in ILSMC. Both theoretical analysis and experimental results are provided to verify the effectiveness of the proposed approach.

A new method is proposed in this paper which designs a reduced-order observer of a non-observable-form-based dynamical system such that: (i) the eigenvalues are specified to satisfy desired convergence performance, (ii) a full-rank condition is satisfied, and (iii) a quadratic performance measurement of the deviation of the estimates from the actual states is minimized so as to reduce the large error occurring during the transient period of observation. The proposed approach combines the merits of both the orthogonal functions approach and evolutionary optimization. By solving a Sylvester equation, the proposed optimal design method can not only be used to design the reduced-order observer of a non-observable-form-based dynamical system, but also can avoid the shortcomings of approaches already existing in relevant literatures. Two examples are given to demonstrate the effectiveness and efficiency of the proposed new optimization method on the performance of state estimations. From the demonstrative examples, it can be seen that the estimated state errors asymptotically converge quickly to zero. In addition, the performance measurement values based on the proposed optimal design approach are apparently much lower than those based on the existing nonoptimal design method.

This study characterized the adaptive attentional allocation that occurs during motor preparation. The specifications of task-relevant and task-irrelevant neural processes are key processes that facilitate successful performances by skilled athletes under difficult task conditions. Previous sport psychophysiology studies have used event-related desynchronization/synchronization analysis and electroencephalography (EEG) power analysis to distinguish the types of neuroelectric activity that occur during effortful but functional performance and effortful but dysfunctional performance. However, the dynamics of cortico-cortical communication in both performance states remain unclear. This study linked the simple model of attention allocation and the psychomotor efficiency hypothesis with EEG coherence analysis to specify the dynamics of cortico-cortical communication during successful performance. A within-subjects design was used. Intersite phase coherence (ISPC) and imaginary ISPC were used to compute 8-13 Hz EEG connectivity from EEG recordings obtained before successful and unsuccessful performances (i.e., 40 skilled golfers; 40%-60% putting success rate as individual task difficulty). Successful performance was characterized by (a) lower 8-13 Hz ISPC and imaginary ISPC (imISPC) at T7-Fz in the -2,000 to -1,000 ms time window and (b) lower 8-13 Hz imISPC at T7-Cz in the -1,000 to 0 ms time window. This study suggests that successful performance is characterized by reduced communication between verbal-analytical and motor planning processes, followed by decreased communication between verbal-analytical and motor control processes before putting initiation. Our findings not only characterize the dynamic neuromotor processes between successful performance and unsuccessful performance of a difficult task, but also provide practical guidelines for interventions such as neurofeedback training.

The meshed control theory assumes that cognitive control and automatic processes work together in the natural attention of experts for superior performance. However, the methods adopted by previous studies limit their capacity to provide in-depth information on the neuromotor processes. This experiment tested the theory with an alternative approach. Twelve skilled golfers were recruited to perform a putting task under three conditions: (1) normal condition, with no focus instruction (NC), (2) external focus of attention condition (EC), and (3) internal focus of attention condition (IC). Four blocks of 10 putts each were performed under each condition. The putting success rate and accuracy were measured and electroencephalographies (EEGs) were recorded. The behavioral results showed that the NC produced a higher putting success rate and accuracy than the EC and IC. The EEG data showed that the skilled golfers’ attentional processes in the NC initially resembled those in the EC and then moved toward those in the IC just before putting. This indicates a switch from more automatic processes to cognitive control processes while preparing to putt. The findings offer support for the meshed control theory and indicate the dynamic nature of neuromotor processes for the superior performance of athletes in challenging situations.

Human robot interaction is commonly seen in the application of collaborative robots. In order to ensure the safety of the human operator, most existing approaches exploit the idea of compliance control in the design of suitable controllers. In particular, force sensors are often used to estimate the contact force that is essential in the design of the compliance control scheme. However, force sensor-based approaches are not cost-effective. In order to cope with this problem so as to facilitate the implementation of compliance control, this paper aims to compare various observer-based force-sensorless approaches for implementing impedance control of collaborative robot manipulators. Different observer-based approaches, such as the generalized momentum approach, the extended state observer, the modified extended state observer, and the closed-loop disturbance observer are used in this paper to estimate the contact force. Several impedance control experiments conducted on a 6-DOF robot manipulator are used to assess the performances of the aforementioned observer-based approaches. Experimental results indicate that the modified extended state observer exhibits the best performance on contact force estimation among all the tested observer-based approaches.

This paper focuses on active wire tension control of motor winding machines.An ILSMC scheme for wire tension control is developed.A disturbance observer is used to implement sensorless wire tension control.The estimated wire speed is exploited in designing the tension control scheme.The stability and convergence proof of the proposed approach is provided. One of the most crucial factors that affects the winding quality in an automatic motor winding process is the regulation of wire tension. Most commercial automatic motor winding machines use passive devices such as a dancer arm or a hysteresis brake to adjust the wire tension. However, as the winding speed increases, these passive devices may not be able to react quickly enough to maintain constant wire tension and may cause the enameled wire to tremble. In order to cope with the aforementioned problems, this paper conducts an in-depth study on active wire tension control of automatic motor winding machines. In particular, an iterative learning sliding mode control scheme for wire tension control is developed in this paper, while a disturbance observer is employed to estimate the wire tension for the implementation of sensorless wire tension control. Moreover, due to the fact that the motion of the unwind roll is affected by the motion of the enameled wire, the estimated wire speed information is exploited in the design of the tension control scheme to lessen the lag phenomenon. Results of the winding experiments verify the effectiveness of the proposed wire tension control scheme.

This paper proposes a new method to design the observer for state delay systems such that (i) state estimation errors converge to zero quickly and (ii), at the same time, a quadratic performance measurement of the deviation of estimates from the actual states is minimized for reducing large error during the transient period of observation. The proposed new approach fuses the merits of both the orthogonal functions approach and evolutionary optimization. One illustrative example is given to verify the effectiveness and efficiency of the proposed new optimization method on performance improvement of state estimations. From the illustrative example, in addition to the asymptotical convergence of the estimated state errors, the performance index for the proposed optimal design approach is clearly much lower than that of the nonoptimal design method.

One of the commonly used approaches to avoid the short circuit of power devices for pulse-width-modulation (PWM) inverters is to add dead-time into the control signals. The drawback of this approach is that severe distortion in phase currents and output voltages may occur. This paper proposes an adaptive-linear-neuron based nonlinearity compensation strategy to cope with the disturbance voltage caused by dead-time effects. In particular, by minimizing the feedback d-axis current error, the amplitude of disturbance compensation voltage V dead is self-tuned using the least mean square algorithm. The dead-time compensation method developed in this paper does not need any information about electric parameters and phase current polarity. Moreover, the proposed approach is also free of complex mathematical computations and additional hardware. Experimental results indicate that the proposed dead-time compensation approach is feasible.

Due to issues such as limited space, it is difficult if it is not impossible to employ a position sensor in the drive control of high-speed micro PMSMs. In order to alleviate this problem, this paper analyzes and implements a simple and robust position sensorless field-oriented control method of high-speed micro PMSMs based on the sliding-mode observer. In particular, the angular position and velocity of the rotor of the high-speed micro PMSM are estimated using the sliding-mode observer. This observer is able to accurately estimate rotor position in the low speed region and guarantee fast convergence of the observer in the high speed region. The proposed position sensorless control method is suitable for electric dental handpiece motor drives where a wide speed range operation is essential. The proposed sensorless FOC method is implemented using a cost-effective 16-bit microcontroller and tested in a prototype electric dental handpiece motor. Several experiments are performed to verify the effectiveness of the proposed method.

This paper proposes a recurrent fuzzy cerebellar model articulation controller (RFCMAC) for a dual-axis micromotion stage powered by piezoelectric actuators. The proposed RFCMAC employs an adjustable input space quantization method with a learning rate capable of self-tuning. The proposed RFCMAC is aimed at dealing with the adverse effects due to unknown hysteresis nonlinearity, modeling uncertainty, and external disturbance that are commonly found in the piezoelectric actuator systems. The proposed RFCMAC mainly focuses on overcoming the drawbacks of the conventional CMAC control scheme when used to control a piezoelectric actuator system. In particular, the adjustable input space quantization method uses a simple repartitioning decision function to determine an appropriate input space quantization. In addition, the self-tuning law for the learning rate of the proposed RFCMAC is derived based on the discrete-time Lyapunov function so that convergence and faster learning can be guaranteed. Finally, in order to validate the effectiveness of the proposed control methodology, several contour-following experiments were conducted on a dual-axis piezoelectric actuated micromotion stage. Experimental results show that the proposed control scheme is feasible, and its performance is superior to that of the conventional CMAC control scheme.

Contour following motions are commonly seen in industrial manufacturing, in which the quality of manufacturing/product closely depends on the accuracy of contour following motions. In general, contour following accuracy will be affected by factors such as dynamics incompatibility among different axes and external disturbances. In order to cope with this problem, this paper proposes a new motion control scheme that consists of a well-known cross-coupled controller (CCC) and an adaptive disturbance compensator (ADC). In particular, the proposed motion control scheme is mainly used to suppress external disturbance and also cope with the problems of modeling uncertainty and dynamics incompatibility among different axes. Moreover, in order to further enhance the effectiveness of the proposed motion control scheme, the parameter-based contour error estimation algorithm is employed in this paper to provide accurate contour error information to the cross-coupled controller. Several contour following experiments conducted on a two-axis motion stage are used to assess the effectiveness of the proposed control scheme.

The motion accuracy and performance of piezoelectric actuators (PEA) are hampered by their inherent hysteresis nonlinearity and time-varying parameters. In order to overcome these drawbacks, an integrated motion control scheme is developed in this paper. In the proposed controller scheme, for each axis of the micro motion stage, a fuzzy CMAC feedforward controller combined with a conventional proportional-integral (PI) feedback controller and a critic-based learning mechanism (FCMAC-CLM) is used to improve the tracking performance and deal with the adverse effects due to hysteresis nonlinearity and external disturbance. In addition, one of the most important issues in the contour following tasks performed by a dual-axis micro motion stage is the contour error reduction. In order to improve the contouring accuracy, a fuzzy CMAC that is capable of real-time learning and self-adjusting is exploited to develop a fuzzy CMAC cross-coupled controller (FCMAC-CCC). Several experiments have been conducted to evaluate the tracking performance and contour accuracy of the proposed approach.

One of the key issues regarding multi-axis contour following tasks in modern high-precision machining applications is how to effectively reduce contour error. Generally, among existing approaches, the Cross-Coupled Control (CCC) structure is widely used in multi-axis contour following tasks to improve contouring accuracy. However, when a servomechanism is operated in reverse or low-speed motions, the inherent friction force and external disturbance effects will degrade the CCC performance. Therefore, to cope with the aforementioned problems, this paper exploits the Karnopp friction model-based compensator and the Virtual Plant Disturbance Compensator (VPDC) to improve tracking performance as well as contouring accuracy. Moreover, an integrated motion control scheme is also developed to further improve contouring performance. The proposed scheme consists of two position loop controllers with velocity command feedforward, a modified CCC, two friction force compensators, and two disturbance compensators. To evaluate the performance of the proposed approach, several free-form contour following experiments have been conducted on an X-Y table driven by two linear motors. Experimental results verify that the proposed approach can significantly enhance contouring performance for free-form contour following tasks.

In this paper, an adaptive disturbance compensation (ADC) scheme for the speed control of a servomechanism is proposed. The idea of the proposed ADC is to adaptively adjust the compensator gains so that the output of the actual plant after compensation will faithfully follow the output of the nominal model. The major benefits of the ADC are twofold — disturbance/uncertainties attenuation and load torque estimation. The stability of the proposed ADC is verified by Lyapunov stability analysis. In addition, an integrated motion control structure consisting of the proposed ADC, a feedback controller and a friction compensator is developed to deal with the contour following problem. In this paper, the friction compensator designed based on the LuGre friction model is used to effectively reduce the large contouring error that often occurs when there is a reverse motion. Two experiments have been conducted to verify the effectiveness of the proposed approach. The test bench of the load torque estimation experiment consists of a servo motor and a hysteresis dynamometer, while the contour following experiment is conducted on an X–Y table. Experimental results show that the proposed approach exhibits satisfactory performance.

Many control problems encountered in industrial applications such as deburring, cutting, and polishing are required to simultaneously perform force control and contour following. If the mathematical model of the contour to be followed is known, then the control problem is straightforward, and many existing approaches can be used to tackle this problem. In contrast, if the mathematical model is not available, the control problem will become much more challenging. Among all possible solutions to circumvent the aforementioned difficulties, using a vision system to obtain the mathematical model of the contour to be followed is one of the best options. To this end, this paper proposes a vision-based approach, in which a vision system is employed to provide the exterior contour information of the object for machining. Subsequently, coordinate transformation between the image plane and the robot frame is performed. Based on the exterior contour information after coordinate transformation, a Pythagorean hodograph quintic spline interpolator based on S curve acceleration/deceleration is developed to generate motion commands. The fact that the arc length of a Pythagorean hodograph curve can be easily computed makes it particularly useful when performing motion planning for high-precision motion control systems. Moreover, in order to improve contour following accuracy, an integrated motion control structure consisting of an adaptive disturbance compensator, a sliding mode controller, and a friction compensator is also developed. Finally, several contour following experiments are conducted by a planar two-link robot manipulator to verify the effectiveness of the proposed approach.

This paper presents a C 2 Pythagorean-Hodograph (PH) spline curve interpolator for contour-following tasks. To generate the C 2 PH quintic spline curve, a uniform knot sequence is employed. The S-curve motion planning architecture with variable feedrate for a planar C 2 PH quintic spline curve is also developed. In particular, C1 cubic feed acceleration/deceleration is imposed on the first and last PH quintic spline segments. The proposed interpolation algorithm along with a simple position loop controller is employed to perform a closed C 2 PH quintic spline curve following task. Experimental results indicate that the proposed interpolator is not only feasible for machining the complicated parametric curves represented in C 2 PH quintic spline form but also yields satisfactory contouring performance for variable feedrate control.

In modern machining applications, reduction of contour error is an important issue concerning multi-axis contour following tasks. One popular approach to this problem is the cross-coupled controller (CCC). By exploiting the structure of CCC, an integrated control scheme is developed in this paper and an in-depth investigation on the issue of contour error reduction is also conducted. The proposed motion control scheme consists of a feedback controller, a feedforward controller, and a modified contour error controller (CCC equipped with a real-time contour error estimator). In addition, a fuzzy logic-based feedrate regulator is proposed to further reduce the contour error. The proposed feedrate regulator is designed based on the real-time estimated contour error and the curvature of the free-form parametric curves for machining. Several experiments are conducted to evaluate the performance of the proposed approach. Experimental results demonstrate the effectiveness of the proposed approach.

This paper deals with the partial pole placement design of a proportional-integral (PI) observer. The proposed partial pole placement approach offers a new method for designers to assign the PI observer gains on a detectable system. Analysis and design of the PI observer are discussed in detail. A crucial lemma and discussions to the proposed approach are presented, and an illustrative numerical example is given to verify the proposed design approach.

The cross-coupled control (CCC) is considered to be the most popular approach to reducing contouring error for biaxial contour following tasks. Using the CCC concept as a starting point, this paper will then develop the position error compensator (PEC) approach to reduce contour error. The main advantage of the proposed approach is that it can simultaneously improve tracking and contouring performances by compensating position errors in advance. Moreover, to further reduce the contour error, an integrated motion control scheme consisting of the proposed PEC, a modified version of CCC, and a fuzzy-logic-based feedrate regulator is employed. Several free form contour following experiments have been conducted. Experimental results demonstrate that the proposed approach can significantly reduce the contouring error for biaxial contour following tasks.

In contour-following tasks, contour error reduction is an issue of much concern. Generally speaking, contour error is caused by the mismatched dynamics between each axis. To reduce the contour error, many previous studies have focused on developing proper controllers and/or more accurate contour error estimation algorithms. An alternative method for reducing contour errors is to exploit the idea of desired feedrate adjustment. This paper proposes using the approximate contour error information to develop a fuzzy logic-based feedrate regulator, which adjusts the value of the desired feedrate. Moreover, to further reduce contour error, an integrated motion control scheme is also developed. This scheme consists of a position loop controller with velocity command feedforward, a tangential contouring controller (TCC), a real-time contour error estimator, and the proposed fuzzy logic-based feedrate regulator. Several experiments on free-form contour-following tasks are conducted to evaluate the performance of the proposed approach. The experimental results clearly demonstrate the effectiveness of the proposed approach.

Reduction of contour error is an important issue in contour-following applications. One of the common approaches to this problem is to design a controller based on contour error information. However, for the free-form contour-following tasks, there is a lack of effective algorithms for calculating contour errors in real time. To deal with this problem, this paper proposes a real-time contour error estimation algorithm. In addition, a motion control scheme that combines a position loop controller (which utilizes a velocity command feedforward) with a tangential-contouring controller (TCC) is employed to improve the contour-following accuracy. When implementing the TCC, a coordinate transformation matrix is needed. Unfortunately, it is difficult to calculate the coordinate transformation matrix when performing the free-form contour-following task. To overcome this difficulty and facilitate the use of contour controllers, a systematic approach is employed to derive the coordinate transformation matrix for the free-form contour-following tasks. Experimental results demonstrate the effectiveness of the proposed contour error estimation algorithm and the motion control scheme

An iterative error compensation approach is proposed in this article to improve the accuracies of high speed, computer-controlled machining processes. It is well known that the high-speed computer-numerically-controlled (CNC) machines are extremely useful in terms of manufacturing mass-produced parts. The proposed method uses an iterative learning technique that adopts the servo commands and cutting error experienced in previous maneuvers as references to current compensative actions. Moreover, non-repetitive disturbances and nonlinear dynamics of the cutting processes, and servo systems of the CNC machine that greatly affect the convergence of the learning-control systems were also studied in this research. State feedback and output feedback techniques were adopted in the proposed controller design. In addition to the stability analysis, a 1 degree-of-freedom servo positioning system is constructed to evaluate the performance of our proposed learning control approach. Both the simulation and experimental results verify the effectiveness of our approach.

Motion controllers play a pivotal role in the development of high-performance CNC machines. Precision motion control is achieved with a control structure employing S-curve motion planning on the velocity command before interpolation, command feedforward and friction feedforward compensation. To evaluate the performance of the proposed control scheme, a servomechanism is controlled to track a circular curve in the form of nonuniform rational B-splines, where the desired motion information such as velocity and acceleration are also provided. Experimental results indicate that the proposed motion-control structure exhibits a better performance, when compared with conventional motion-control schemes.

This study proposes a real-time Non-Uniform Rational B-Spline (NURBS) motion command generator for computer numerical control (CNC) machines to achieve the goal of high-speed and highly accurate machining. Different numerical algorithms for implementing the NURBS motion command generator are compared on the basis of both the computation time and the precision of geometric representation. In addition, to reduce the computation time such that the corresponding servo control laws can be executed in real time, both the NURBS motion command generator and the servo control laws are realized using a digital signal processor. Experimental results indicate that the proposed real-time NURBS command generator is able to provide a satisfactory performance.

A method is proposed for parameter tuning of PID controllers. Unlike the traditional techniques, the proposed tuning procedure is expressed in terms of fuzzy rules, in which the input variables are the error signal and its derivative, while the output variables are the PID gains. A genetic algorithm (GA) is then used to search for the optimal PID gains that will minimize the integral of the squared error. Meanwhile, to prevent damaging the plant due to abrupt changes in PID gains, a trained neural network will also be used to represent the plant in the genetic searching procedure. After determining the PID gains in this off‐line manner, these gains are then applied to the real plant for on‐line control. In training the neural network model, generation of training data and adjustment of neuron weights will be performed simultaneously in an on‐line manner. To show the validity of the proposed method, a seesaw system with one input and two outputs will be used for experimental evaluation.

In addition to positioning control, contour following control is also an important application of two-axis servomechanisms such as X-Y tables. Therefore, the reduction of contour following error so as to improve contour following accuracy is one of the important research topics for two-axis servomechanisms. Generally, the assessment of contour following accuracy is based on two error indices — tracking error and contour error. Although the reduction of tracking error can lead to the improvement of contour following accuracy, many previous studies suggest that contour error is a more crucial indicator than tracking error in contour following applications. As a result, this paper aims at developing a control scheme for contour error reduction so as to improve contour following accuracy. The proposed control scheme consists of a PI type feedback controller, a Cerebellar Model Articulation Control (CMAC) algorithm and an Iterative learning Control (ILC) scheme. In particular, the CMAC is combined with the ILC to compensate for the adverse effects due to external disturbance and nonlinear phenomenon. Experimental results verify the effectiveness of the proposed contour following control scheme.

In order to automatically identify the electrical parameters of PMSMs, rather than measure the parameters using instruments such as RLC meters, this paper proposes an approach in which the testing voltage is injected into the motor from the drive. Based on the analysis of equivalent circuits of the PMSMs as well as the phase voltage and phase current information recorded from standstill to sensorless control operation, the RLS method is employed to estimate the values of electrical parameters of the PMSMs. Moreover, the automatic motor parameter identification algorithm developed in this paper is also integrated into the open loop startup procedure of the sensorless control drive. Consequently, the proposed automatic motor parameter identification method has attractive features such as fast identification and being highly convenient. In addition, both the proposed automatic motor parameter identification method and the sensorless control drive developed in this paper are implemented using a low-cost 16-bit microcontroller. Two commercial surface-type and interior-type PMSMs are used in the experiments to assess the performance of the proposed approach. Experimental results verify the effectiveness of the proposed automatic motor parameter identification method.

Conventional motor winding machines use a passive device such as a dancer arm or hysteresis brake to adjust the tension of the wire. However, when the winding speed increases, the passive device may not be able to react quickly enough so that a sudden change in the tension will likely cause the enameled wire to vibrate. Consequently, the motor winding quality will be affected. In order to cope with this difficulty, instead of using a passive device, this paper proposes an active tension control scheme, in which the wire tension measured by a load cell is used as the feedback signal of the tension control loop. Moreover, feedforward control and iterative learning control are integrated into the proposed tension control scheme to improve system response and suppress the periodic disturbance arising from the winding process. Several motor winding experiments have been conducted to assess the performance of the proposed approach.

Due to attractive features such as low cost and highly robust, the demand for Switched Reluctance Motors has reached an all-time high. However, the torque ripple caused by the inherent double salient structure of SRMs leads to speed ripple as well. In order to cope with the aforementioned torque/speed ripple problem, many studies rely on sophisticated control techniques. However, in most of the previous studies the powerful Digital-Signal-Processor is used to realize these sophisticated control schemes since their complicated structures require massive computing power. The fact that the DSP-based solution is not cost effective results in a conflict with the original benefits of SRMs. To cope with the aforementioned problems, this paper employs a variable gain PI-type controller to suppress the torque ripples of SRMs. In order to have a cost effective solution, all the motor drive algorithms and control schemes are implemented using a low cost microcontroller in this paper. Experimental results show that the torque ripple has been significantly reduced so as to verify the effectiveness of the proposed control approach.

In manufacturing processes, human error and abnormal operation often result in excessive loads on the servomechanisms. To prevent the abnormal load from damaging the work piece or tool, it is important to find a means to detect the abnormal load so that an appropriate response can be performed. To estimate the load on the servomechanism, two types of torque observer structures are presented in this study. Based on the information obtained from the torque observer, criteria are proposed to determine whether the servomechanism is under the abnormal load, while the Wavelet analysis is employed to enhance the ability of abnormal load detection. Experimental results indicate that the presented observer structures are able to estimate the external torque accurately. In addition, the structure combined with Wavelet analysis is capable of identifying abnormal load events in servomechanisms.

This paper explores the bifurcation behavior of a buck-boost converter. Unlike the previous research, the nonlinearity of the MOSFET and the diode are taken into account when modeling the dynamic equations of the converter. In the simulation, bifurcation points are computed and compared with the ones calculated with the piecewise-linear model and the software SIMPLIS. The simulation results reveal that our model best represents the true behavior of the converter. Moreover, engineers can predict more precisely the occurrence of instability with this model.

Power assisting devices can be found in many different applications, most notably, exercise/fitness equipment, rehabilitation of spinal cord injury or stroke patients, limb muscle enhancement of workers, and bionic limbs of amputee patient. Since the power assisting device has a direct contact with the human user, in addition to providing suitable amount of assisting force, the highest priority in the design of power assisting devices is to ensure the safety of the human user. In order to fulfill such a requirement, in this paper an impedance controller and a passive velocity controller are combined to provide moderate amount of assisting force and also ensure the safety of the user simultaneously. Moreover, a torque observer is used to estimate the torque generated by the user's muscle rather than using a force sensor to measure the contact force between the user and the power assisting device. Experimental results verify the effectiveness of the observer-based impedance controller and the passive velocity controller.

The ability to sustain a smooth-running practice is very important in dentistry. Because of this reason, Electric handpieces driven by permanent magnetic synchronous motors (PMSMs) have been increasingly applied in dentistry and have replaced air-driven ones due to their high efficiency and ability to sustain constant speed while operating. Additionally, they produce little noise compared to the high pitched whine of their air-driven counterparts. As is well known, the rotor position is the necessary information for driving a PMSM. Unfortunately, a dental handpiece requires repeated heat sterilization that will break down the Hall sensors, and further, lacks the space to install an incremental encoder. Therefore, sensorless speed control of a PMSM is the key technology for an electric dental handpiece. In this paper, a sliding mode observer is used to implement an electric dental handpiece. Moreover, a prototype of the electric handpiece system has been designed and built. Experimental results are presented to verify the feasibility.

In high-precision manufacturing, the paramount issue is to diminish contour error regarding multi-axis contour following tasks. In particular, machining problems such as large contouring errors will likely occur in a complex shape machining task due to the inherent friction force and/or external disturbances. Among the possible solutions to dealing with this difficulty, the Cross-Coupled Controller (CCC) is arguably the most commonly used approach for contouring accuracy improvement in multi-axis contouring control systems. Therefore, to attain satisfactory contouring accuracy, this paper exploits the CCC approach for control of free-form contour following tasks in biaxial motion control systems. Additionally, a Fuzzy Logic-based Disturbance Compensator (FLDC) is presented to enhance tracking performance as well as contouring accuracy. Moreover, an integrated motion control structure consisting of a modified version of CCC and two proposed FLDCs is further developed in this paper to improve contouring performance. Several experiments on free-form contour following tasks have been performed on an X-Y table driven by two linear motors. Experimental results validate the feasibility of the proposed approach.

SUMMARYMany studies on control of dynamic biped walking have been done in the past two decades. While the biped dynamics is highly nonlinear, the stability analysis, if done, is usually based on a linearized model. The validity of the linearized model may become questionable if the walking involves states that are too far away from the operating point. In this paper, an approach for evaluating the robustness based on the linearized Poincare map is suggested and examined. The Poincare map is a useful tool to investigate the periodic motion of a dynamic system. Using the Poincare“ map, one can study an associated discrete time map instead of studying the continuous time system directly. Investigation of stability of a periodic motion can be reduced to the study of the stability of a fixed point of the Poincaré map. The computational method that results in a measurement for evaluating the robustness of biped locomotion is developed. Our simulation study has verified that the suggested measurement is a good indicator.

In this paper, a cost effective single stage bidirectional DC/AC converter is designed and implemented using a general full-bridge inverter without any additional power switches or bulky passive components. According to different driving conditions, three switching strategies are developed and analyzed. These switching strategies, which are named after the operating number of the power switches, are called the single-switch, two-switches and three-switches control strategies. Different performance indexes such as boost ratio, maximum voltage conversion ratio, braking torque, etc., are proposed and compared among different switching strategies. Theoretical analysis and experimental results have revealed that the cruising distance, braking torque, and reliability can be improved effectively using a variable braking control strategy according to the driving conditions. Since the additional power switches, passive components and costly position sensors are not required, the proposed method is particularly suitable for various light electric vehicles.

This paper focuses on the current control loop design of the permanent magnet synchronous motor based on sinusoidal commutation. It is well known that sinusoidal commutation can provide a smooth and fast torque response and is particularly suitable for a permanent magnet synchronous motor with sinusoidal back EMF. In general, sinusoidal commutation can be further divided into SPWM and SVPWM. In this paper, simulations of different current control loop approaches, e.g., three-phase current control and field oriented control are performed using Matlab/simulink to obtain suitable control parameters. Moreover, this paper also develops a motor drive for a permanent magnet synchronous motor, in which both SVPWM sinusoidal commutation and field oriented control are implemented using a cost effective microcontroller. Experimental results indicate that the motor drive developed in this paper exhibits satisfactory performance.

Generally, poor machining performance may occur due to the abrupt change of acceleration at the portion of a curve with large curvature. In order to deal with this problem, this paper presents a modified trajectory planning scheme based on PH (Pythagorean Hodograph) curves for sharp corner angle contouring tasks. The main idea of the proposed method is to force the actual toolpath trajectory closer to the original command path by exploiting a modified command trajectory (a C2 PH spline curve) at the sharp corner in advance, so that the corner contouring accuracy can be further improved. Finally, several different sharp corner contour-following experiments were conducted on dual servo motors to evaluate the effectiveness of the proposed approach. Experimental results indicate that the proposed approach can indeed reduce contour error in sharp corner-angle contour-following applications.

Generally, friction/disturbance compensation is an important issue in high-precision motion control applications. In particular, when the system under control undergoes low-speed or reversal motions, the friction force and external disturbances will degrade motion accuracy. Therefore, to achieve satisfactory motion performance, it is necessary to simultaneously compensate for the friction force and external disturbances. In this paper, an integrated motion control scheme consists of a PI-type feedback controller, a friction compensator based on the LuGre model, and a Virtual Plant Disturbance Compensator (VPDC) is developed. In particular, the VPDC is proposed to replace the PI-type Closed-loop Torque Observer (PICTO) since the latter may provide inaccurate information when used in disturbance compensation. Several experiments on load torque estimation and speed control are conducted in order to evaluate the performance of the proposed approach. Experimental results demonstrate the effectiveness of the proposed approach.

In this paper, a passivity-based control scheme for contour following applications is developed. However, the original passive velocity field control requires an accurate dynamic model. To cope with this problem, in the proposed approach an alternative control law design based on the Lyapunov function is employed to speed up the convergence rate of velocity error. Moreover, in order to deal with the modeling uncertainty problem, this paper develops a virtual plant disturbance compensator to estimate the uncertainties due to inaccurate modeling and external disturbance. Several experiments have been conducted to compare the proposed approach with the conventional coupling approach. Experimental results verify the effectiveness of the proposed approach.

In industrial precision applications using dual-axis micro-positioning stages powered by piezoelectric actuators (PEA), the trajectory tracking and contour following performances are limited due to PEA's inherent hysteretic nonlinearity and time varying parameters. In order to cope with this problem, a position control scheme based on reinforcement learning cerebellar model articulation controller (RLCMAC) is developed in this paper. In the proposed control scheme, for each individual-axis, a CMAC-based feedforward controller with reinforcement learning scheme and a conventional proportionalintegral (PI) feedback controller are used. Moreover, in order to reduce contour errors, a CMAC-based cross-coupled controller (CMAC-CCC) is applied to improve the contouring accuracy of a dual-axis micro-positioning stage. Finally, an integrated control scheme is proposed to improve the tracking and contouring accuracy. Experimental results verify the effectiveness of the proposed approach.

In this paper, a vision-based optical fiber alignment motion stage powered by Piezo-Actuator (PEA) is developed. However, the tracking performance of PEA is limited due to its inherent hysteretic nonlinearity and time varying parameters. In order to cope with this problem, a novel feedforward inverse hysteresis model based on B-spline approximation is adopted to eliminate the adverse effects due to hysteresis. In addition, a fuzzy logic controller is designed to reduce the error caused by noise and modeling inaccuracy. Moreover, the idea of multi-rate control is exploited to deal with the vision latency problem. The feasibility of the proposed control scheme is verified under a variety of reference inputs. Experimental results show that the proposed approach exhibits satisfactory performance.

Optical fiber communication has become mainstream in wired communication due to its low attenuation, low cost, and high bandwidth. However, optical fiber is light and thin, which makes the coupling procedure between fibers and optoelectronic components very complex and difficult. To maintain high transmission quality, it is imperative to develop a high-precision alignment technique for optical fiber fabrication. In this paper, a vision-based optical fiber alignment stage powered by a piezo-actuator (PEA) is proposed. The tracking performance of PEA is limited due to its inherent hysteretic nonlinearity and time varying parameters. In order to cope with this problem, a feedforward compensator based on a cerebellar model articulation controller (CMAC) combined with a PI feedback controller is developed to eliminate the effects of hysteresis. Multi-rate control is used to deal with the vision latency problem. Experimental results show that the proposed approach shows satisfactory performance.

In this paper, a single-phase DC/AC inverter for uninterruptible power supply using moving sliding manifold (MSM) sinusoidal tracking control is proposed. The characteristic of the MSM over the conventional sliding manifold is capable of ensuring the sliding mode proceeds from an arbitrary initial state and thus achieves the robustness against system uncertainties. The inverter tracking performances of steady-state and transient responses can be improved due to speedup-reaching the sliding manifold. A 60 Hz 400 W prototype is built with MSM control scheme based on dSPACE DSP by sensing the output voltage for the closed-loop feedback. The experimental results show that low total harmonic distortion (THD) output voltages under resistive load or even under rectifier-RC load and fast transient response subject to step change in load are obtained. Design procedures, computer simulations, and experimental results are provided to demonstrate the performance of the MSM controlled inverter.

In contour following applications, one of the main concerns is how to reduce contour errors. The common approach to this problem is to design the contour controller based on the real-time contour error information. However, for the free-form contour following tasks, there is a lack of effective algorithms for calculating contour errors in real time. To overcome this difficulty, this study proposed a real time contour error estimation algorithm. Based on the estimated contour error obtained from the proposed algorithm, an integrated motion control scheme is employed to improve the machining accuracy for a contour following task. Experimental results indicate that both the proposed contour error estimation algorithm and the integrated motion control scheme exhibit satisfactory performances

Reduction of contour error is an important topic in contour following applications. This study conducts an in-depth investigation on this issue. In addition, an integrated control scheme is proposed to reduce contour error. In this paper, we have accomplished the following: 1) based on the estimated contour error method, a contour error controller is designed to reduce the contour error for an arbitrary curve following task; 2) according to the estimated contour error, a fuzzy logic based feedrate regulator is proposed to determine a suitable feedrate in real-time; and 3) the contour error controller and the fuzzy logic based feedrate regulator are developed to reduce the contour error. Several experiments are conducted to evaluate the performance of the proposed approach. Experimental results demonstrate the effectiveness of the proposed approach

This paper presents the design, analysis, and implementation of a high performance and cost effective sensorless control scheme for the extensively used brushless DC motors (BLDCMs). Taking into consideration cost and ease of implementation, the commutation signals are obtained without the motor neutral voltage, multistage analog filters, A/D converter, and the complex digital phase shift (delay) circuit which are indispensable in the conventional sensorless control algorithms. Instead of detecting the zero crossing point of the non-excited phase back EMF to the neutral voltage, the commutation signals are extracted directly from the specific average terminal voltages with simple RC circuits and comparators in this study. Since the neutral voltage is not needed, the extracted commutation signal is insensitive to the common mode noise, hence the low speed performance is superior to the conventional methods. Moreover, the complex phase shift circuit has been eliminated. As a result, the control algorithm can be easily interfaced with the cost effective commercial Hall effect sensor based commutation ICs. Because of the inherent low cost property, the proposed algorithm is particularly suitable for cost sensitive products such as air purifiers, air blowers, cooling fans, and related home appliances. Theoretical analysis and experimental results show that the proposed control algorithm exhibits superior performance over a wide operation range when compared with the conventional solutions