Cheng Yap Shee

Feedforward Controller of Ill-Conditioned Hysteresis Using Singularity-Free Prandtl–Ishlinskii Model

Piezoelectric, magnetostrictive, and shape memory alloy actuators are gaining importance in high-frequency precision applications constrained by space. Their intrinsic hysteretic behavior makes control difficult. The Prandtl-Ishlinskii (PI) operator can model hysteresis well, albeit a major inadequacy: the inverse operator does not exist when the hysteretic curve gradient is not positive definite, i.e., ill condition occurs when slope is negative. An inevitable tradeoff between modeling accuracy and inversion stability exists. The hysteretic modeling improves with increasing number of play operators. But as the piecewise continuous interval of each operator reduces, the model tends to be ill-conditioned, especially at the turning points. Similar ill-conditioned situation arises when these actuators move heavy loads or operate at high frequency. This paper proposes an extended PI operator to map hysteresis to a domain where inversion is well behaved. The inverse weights are then evaluated to determine the inverse hysteresis model for the feedforward controller. For illustration purpose, a piezoelectric actuator is used.

Estimating Displacement of Periodic Motion With Inertial Sensors

Inertial sensors, like accelerometers and gyroscopes, are rarely used by themselves to measure displacement. Accuracy of inertial sensors is greatly handicapped by the notorious integration drift, which arises due to numerical integration of the sensors zero bias error. A solution is proposed in this paper to provide drift free estimation of displacement from inertial sensors.

Automatic Hysteresis Modeling of Piezoelectric Micromanipulator in Vision-Guided Micromanipulation Systems

Conventional hysteresis modeling of piezoelectric actuators using interferometers or capacitive sensors is often performed off-line. However, the hysteresis of the piezoelectric actuator changes as the load acting on it or the driving frequency of the input signal alters, demanding that the hysteresis of the micromanipulator be modeled on the fly. The employment of interferometers or capacitive sensors is a challenging task in micromanipulation systems due to their special requirements, e.g., the micropipette tip is desired to provide mirror-like reflection of the incoming beam if an interferometer is employed while a capacitive sensor might not be easily placed in the workspace. An automatic Prandtl-Ishlinskii hysteresis modeling method is proposed and implemented using vision-feedback. The method can be conducted on the fly in real time making it suitable for time critical vision-guided micromanipulation, while providing comparable accuracy with that of using interferometers.

A Low-Cost Flexure-Based Handheld Mechanism for Micromanipulation

With the advancement in the knowledge of surgical procedures and cell micromanipulation, there is a demand for a handheld instrument to perform micromanipulation. Hence, this paper presents a 3-DOF handheld mechanism for micromanipulation driven by three piezoelectric actuators. Flexure-based joints are utilized because of its advantages like the nonexistence of backlash and assembly errors. However, it is difficult and expensive to make such compact mechanism using traditional machining methods. In addition, the traditional machining methods are limited to simple design. To reduce the cost of fabrication and also to allow more complex designs, Objet (a rapid prototyping machine) is proposed to be used to build the mechanism. With regards to the handheld applications, the size of the mechanism is a constraint. Hence, a parallel manipulator design is the preferred choice because of its rigidity and compactness. For the illustration of an application, the mechanism is designed with an intraocular needle attached to it. Possible applications of this design include enhancement of performance in microsurgery and cell micromanipulation. Experiments are also conducted to evaluate the manipulators tracking performance of the needle tip at a frequency of 10 Hz.

Compact Sensing Design of a Handheld Active Tremor Compensation Instrument

Active physiological tremor compensation instruments have been under research and development recently. The sensing unit of the instruments provides information on three degrees-of-freedom (DOF) motion of the instrument tip using accelerations provided by accelerometers placed inside the instruments. A complete vector of angular acceleration of the instrument needs to be known to obtain information on three DOF motions of the tip. Sensing resolution of angular acceleration about the instrument axis is directly proportional to the width of the proximal-end sensing unit. To keep the sensing resolution high enough, the width of the unit has to be made large. As a result, the proximal-end sensing unit of the instruments is bulky. In this paper, placement of accelerometers is proposed such that the angular acceleration about the instrument axis need not be known to obtain information on the three DOF motions of the tip. With the proposed placement, the instrument is no longer bulky and fewer number of accelerometers is required, thereby making the instrument compact and better in terms of ergonomics and reliability. Experiments were conducted to show that the proposed design of placement works properly.

Physiological tremor sensing using only accelerometers for real-time compensation

A hand-held tremor compensation instrument, Micron, has been under research recently. The sensing part of the instrument comprises a magnetometer and accelerometers. The use of the magnetometer is to provide accurate instrument orientation information. The drawbacks of relying on the magnetometer include the requirement for on-site calibration of the magnetometer and sub-optimal estimation of the tremor due to sub-optimal estimation of the instrument orientation. To eliminate the problems associated with the magnetometer, an algorithm of sensing the tremor using only accelerometers is proposed. The algorithm is tested with real accelerometer output data and the results are shown and discussed.

Kalman filtering of accelerometer and electromyography (EMG) data in pathological tremor sensing system

Currently there is a lack of objective clinical diagnosis and classification of tremor is difficult when it is subtle. Thus in previous work, a sensing system has been developed to quantify pathological tremor in human upper limb. In this paper, a Kalman filter algorithm to fuse information from accelerometers and surface electromyography is proposed. As the ground truth, an optical motion tracking system will be utilized. Then two sensor fusion algorithms based on Kalman filter are formulated to estimate the joint angle of the limb from the reading of accelerometers and surface EMG. Initial results using tremor data from two Parkinsons disease patients show promising future in this sensor fusion. The sensing system and the algorithms proposed are useful for actively compensating the tremor and helping the clinicians in tremor diagnostics.

A compact 3-DOF compliant serial mechanism for trajectory tracking with flexures made by rapid prototyping

To fulfill the needs for accurate trajectory tracking with large displacement in a handheld instrument, a 3-DOF serial compliant mechanism is developed. The mechanism is compact with a total length less than 150 mm and a maximum diameter of 22 mm. Two flexures are developed using different rapid prototyping techniques: one 3-DOF flexural lever made of Vero-Gray by Polyjet and a 1-DOF translational flexure made of stainless steel by Direct Metal Laser Sintering (DMLS). Analytical and Finite Element (FE) models are developed for the proposed flexural mechanisms. Experiments are conducted on a prototype. To improve the tracking accuracy, the hysteretic nonlinearities of the system are modeled using Prandtl-Ishlinskii model. Inverse feedforward controller is implemented to linearize the relationship between input and output. The tracking errors are reduced while maintaining a fast response of the system. The total tracking errors are identified individually for each axis and then compensated. Tracking performances of the tool tip are evaluated experimentally with different inputs. The RMS tracking error of the proposed mechanism is lower than 1 μm in all axes, which is improved more than four times compared to the previous systems.

Filtering of intended motion for real-time tremor compensation in human upper limb using surface electromyography

The recorded motion from (pathological) tremor patient may consist of the involuntary tremulous component and the intended motion. These two components have to be separated so that the actuation part will be able to suppress only the tremor. This paper proposes an algorithm to remove the intended motion by using an extended Kalman filter with the help of adaptive high-pass filter. The effectiveness of the algorithm is also shown in the presence of stimulation artifacts. It is part of the active pathological tremor compensation project for human upper limb.

An Extended Kalman filtering of accelerometer and surface electromyography data for attenuation of pathological tremor

Previously a Kalman filter has been developed to estimate joint angle of the tremulous upper limb using data from accelerometer (ACC) and surface electromyography (sEMG). Results have shown that the fused information can be useful for actively compensating the tremor and helping the clinicians in tremor diagnostics. In this paper, an improvement for the current algorithm is proposed by implementing Extended Kalman Filter (EKF). There is electromechanical delay between the muscle activation (sensed by sEMG) and onset of motion (sensed by ACC). Thus some information from the sEMG will be extracted first then it will be fed to the EKF algorithm together with the measurement from ACC.Weighted-Frequency Linear Combiner (WFLC) is used to extract the frequency of the sEMG data. The EKF will then be able to estimate the amplitude and phase of the tremor, along with the accelerometer bias. The extracted parameters of the tremor will be useful for its attenuation. The recursive nature of WFLC and EKF algorithm enables a real time implementation.