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A fuzzy logic based performance augmentation of MEMS gyroscope
Abstract
This paper describes a compensation strategy utilizing fuzzy logic methodology to augment the performance of low cost micromechanical gyros. Among many serious parameters affecting the performance of MEMS gyros, our attention is focused on the scale factor error due to its nonlinearity and asymmetry. Motivated by the capability of fuzzy logic in managing nonlinear mapping, a fuzzy logic based compensation algorithm is proposed. The ADXRS 300 gyros of Analog Device were selected as the candidates at our lab. Experimental results demonstrate that gyros augmented by proposed approach show improvements in scale factor error of an order of magnitude (extremely linear output) throughout operating dynamic range.
... b Movable plate gets access to one third of its first distance to the fixed plate at the pull-in point [33,35] provided corrections to the stand-alone IMU predicted navigation states particularly position. Hong [18] took advantage of fuzzy logic methodology to augment the performance of low cost MEMS gyroscopes. Fei and Xin [15] approached adaptive fuzzy control to estimate the upper bound of the lumped uncertainty in back-stepping Sliding Mode Control (SMC) with application to MEMS triaxial gyroscopes. ...
... This gain ( K u ) and the corresponding oscillation period ( T u ) are the tuning/schedualing design factors in Table 2. For this purpose, a pole is added to the plant to have asymptotes with degrees of 60 • , −60 • and 180 • in the modified system of G tot (s) , considering Eq. (18) for the angles of the root locus asymptotes [9]. The asymptote angle equation is: where n z and m z respectively symbolize the degrees of the denominator and nominator of G tot (s) . ...
This study presents a conventional Ziegler-Nichols (ZN) Proportional Integral Derivative (PID) controller, having reviewed the mathematical modeling of the Micro Electro Mechanical Systems (MEMS) Tunable Capacitors (TCs), and also proposes a fuzzy PID controller which demonstrates a better tracking performance in the presence of measurement noise, in comparison with conventional ZN-based PID controllers. Referring to importance and impact of this research, the proposed controller takes advantage of fuzzy control properties such as robustness against noise. TCs are responsible for regulating the reference voltage when integrated into Alternating Current (AC) Voltage Reference Sources (VRS). Capacitance regulation for tunable capacitors in VRS is carried out by modulating the distance of a movable plate. A successful modulation depends on maintaining the stability around the pull-in point. This distance regulation can be achieved by the proposed controller which guarantees the tracking performance of the movable plate in moving towards the pull-in point, and remaining in this critical position. The simulation results of the tracking performance and capacitance tuning are very promising, subjected to measurement noise.
Article Highlights
This article deals with MEMS tunable capacitor dynamics and modeling, considering measurement noise.
It designs and applies fuzzy PID control system for regulating MEMS voltage reference output.
This paper contributes to robustness increase in pull-in performance of the tunable capacitor.
... Additionally, it results in lower installation and operating costs for the entire system [5,6]. However, as yaw-angle estimation relies on the integration of rate signals from gyros that have relatively large drift errors, unbounded yaw-angle errors can occur, which consequently causes unbounded position errors [7][8][9][10][11]. ...
This paper proposes an improved algorithm for augmenting the enhanced HDR by utilizing encoder readings to achieve further minimized drift on the yaw-angle estimation of cleaning robots. The primary idea of the proposed approach consists of two phases: 1) classifying the manoeuvre (stop, straight and curving) being carried out using logic as a function of encoder readings; 2) controlling the Attenuator gain, resetting the Binary I-controller and switching Integrator in the enhanced HDR structure, taking into account the identified manoeuvring conditions. The proposed algorithm is applied to a cleaning robot and the experimental data demonstrate the effectiveness of this approach.
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This paper present an effective complementary filtering method using encoder and gyro sensors for the self-localization(including heading and velocity) of indoor mobile robot. The main idea of the proposed approach is to find the pros and cons of each sensor through a various maneuvering tests and to design of an adaptive complementary filter that works for the entire maneuvering phases. The proposed method is applied to an indoor mobile robot and the performances are verified through extensive experiments.
This paper proposes a practical algorithm for the reduction of measurement errors due to drift in a micro-electromechanical system (MEMS) gyros that are used for a mobile robot. Any drift in a MEMS gyro will cause an unbounded growth of errors in the estimation of heading, which makes it nearly useless in applications that require high accuracy over a long operating time. In proposed method, maneuvers of a cleaning robot are observed through encoders' measurement process and a decision to correct bias drift will be made if necessary. The method used in this paper is called the "heading estimation filter". To evaluate the accuracy of the proposed method, a comparison was made between the estimation of the heading of the cleaning robot and one from a motion capture system.
This paper presents the design of smart filter for the 2D localization of robotic fish using low-cost MEMS (Micro-Electro Mechanical System) accelerometer. The main purpose of the paper is to minimize the drift error that is inevitable in the double integration process in accelerometer-only navigation system. The proposed approach relies on two parts: 1) an effective calibration method to remove the major part of the deterministic sensor errors and, 2) a novel smart filtering scheme based on fuzzy-logic in order to accurately estimate a 2D position with an accelerometer triad. In addition, we compare the results of the fuzzy logic based on 2D position estimation system with simulation result from a conventional Kalman Filter.
This paper presents the design of smart filter for the 2D localization of robotic fish using low-cost MEMS (Micro-Electro Mechanical System) accelerometer. The main purpose of the paper is to minimize the drift error that is inevitable in the double integration process in accelerometer-only navigation system. The proposed approach relies on two parts: 1) an effective calibration method to remove the major part of the deterministic sensor errors and, 2) a novel smart filtering scheme based on fuzzy-logic in order to accurately estimate a 2D position with an accelerometer triad. In addition, we compare the results of the fuzzy logic based on 2D position estimation system with simulation result from a conventional Kalman Filter.
This paper presents the position estimation for small robotic fish using GPS(Global Positioning System)/INS (Inertial Navigation System) and USBL (Ultra-Short Baseline). The main purpose of the paper is divided in to two parts: 1) to minimize the drift error that is inevitable in the double integration process in INS. 2) to enhance accuracy and update rates on the small robotic fish's position estimates. The simulation results show the efficiency of this algorithm.
To achieve the goal of low-cost MEMS gyros for the precise self-localization of mobile robots, this paper presents a simple, yet effective method to minimize drifts on the heading angle by combining measurements from a gyro with measurements from wheel encoders (odometry). The main idea of the proposed approach is to estimate the accuracy of both sensors as a function of the actual maneuver being carried out, and then the output of both sensors are fused by the complementary filter taking into account the maneuvering conditions. The proposed method is applied to a mobile robot and the experimental data demonstrate the effectiveness of this approach.
Most studies of women working in foreign-owned industries in Southeast Asia have directed their attention to the transnational corporations (TNCs). Here, rather small Norwegian-owned companies are the focus of study, concentrating on one case in Southern Johor. Asking whether the nationality of the company makes any difference to the workers and whether we can trace a Scandinavian tradition of industrial relations, we found that it is rather the rural location and the local adaptation of the company that makes it different from the TNCs. Focus is on the relation between a foreign company and a rural community, thus on the interplay between different development strategies.
This paper presents a simple, yet very effective filtering method to suppress short-term broadband noise in micro-electro-mechanical system (MEMS) gyros for yaw angle measurement with minimized drift. This method is suitable for autonomous indoor mobile robots that use two low-cost sensors: an inertial one, which uses a gyroscope, and an odometric one, which uses encoders mounted on the vehicle’s wheels. The main idea of the proposed approach is consists of two phases: (1) a threshold filter for translational motions, and (2) a moving average filter for rotational motions to reject the broadband noise component that affects short-term performance. Experimental results with the proposed phased method applied to an Epson XV3500 MEMS gyro demonstrate that it effectively suppresses short-term broadband noise and yields accurate yaw angle with minimized drift.
A low-cost, solid-state inertial navigation system for robotics applications is described. Error models for the inertial sensors are generated and included in an extended Kalman filter (EKF) for estimating
the position and orientation of a moving robot vehicle. A solid-state gyroscope and an accelerometer have been evaluated. Without error compensation, the error in orientation is between 5-15°/min but can be improved at least by a factor of five if an adequate error model is
supplied. Similar error models have been developed for each axis of a solid-state triaxial accelerometer. Linear position estimation with accelerometers and tilt sensors is more susceptible to errors due to the double integration process involved in estimating position. WIth the system described here, the position drift rate is 1-8 cm/s, depending on the frequency of acceleration changes. The results show that with careful and detailed modeling of error sources, low cost inertial
sensing systems can provide valuable position information.
This paper describes two methods aimed at improving dead-reckoning
accuracy with fiber-optic gyroscopes (FOGs) in mobile robots. The first
method is a precision calibration procedure for FOGs, which effectively
reduces the ill effects of nonlinearity of the scale-factor and
temperature dependency. The second method is the implementation of an
indirect feedback Kalman filter that fuses the sensor data from the FOG
with the odometry system of the mobile robot. The paper also provides
experimental results and compares the relative effectiveness of the two
methods as implemented on a four-wheel drive/skidsteer Pioneer AT mobile
robot
A low-cost solid-state inertial navigation system (INS) for mobile
robotics applications is described. Error models for the inertial
sensors are generated and included in an extended Kalman filter (EKF)
for estimating the position and orientation of a moving robot vehicle.
Two different solid-state gyroscopes have been evaluated for estimating
the orientation of the robot. Performance of the gyroscopes with error
models is compared to the performance when the error models are excluded
from the system. Similar error models have been developed for each axis
of a solid-state triaxial accelerometer and for a conducting-bubble tilt
sensor which may also be used as a low-cost accelerometer. An integrated
inertial platform consisting of three gyroscopes, a triaxial
accelerometer and two tilt sensors is described
In this paper, our attention is focused on the compensation of the nonlinear thermal bias (zero-rate-output) drift of RRS (Resonant Rate Sensor), which originates from a number of sources, including manufacturing tolerances, material inhomogeneity and inevitable mechanical characteristic variation of the cylinder with temperature. Motivated by the capability of fuzzy logic in managing nonlinearity, the nonlinearity of bias was represented by Takagi–Sugeno (TS) fuzzy model over the entire range of the operating temperature. Then, the fuzzy model was directly used for compensation of nonlinear bias drift by subtracting the estimated output from the raw data of RRS. By doing this, we can guarantee robust (against temperature variations) sensor performance throughout the entire operating temperature range.
This paper describes the development of a fuzzy logic based closed-loop strapdown attitude reference system (SARS) algorithm, integrated filtering estimator for determining attitude reference, for unmanned aerial vehicles (UAVs) using low-cost solid-state inertial sensors. The SARS for this research consists of three single-axis rate gyros in conjunction with two single-axis accelerometers. For the solution scheme fuzzy modules (rules and reasoning) are utilized for online scheduling of the parameters for the filtering estimator. Implementation using experimental flight test data of SURV-1 Sejong UAV has been performed in order to verify the estimation. The proposed fuzzy logic aided estimation results demonstrate that more accurate performance can be achieved in comparison with conventional fixed parameter filtering estimators. The estimation results were compared with the on-board vertical gyro used as the reference standard or ‘truth model’ for this analysis.
In this paper, our attention is focused on the compensation of the
nonlinear thermal bias (zero-rate-output) drift of RRS (Resonant Rate
Sensor), which originates from a number of sources, including
manufacturing tolerances, material inhomogeneity and inevitable
mechanical characteristic variation of the cylinder with temperature.
Motivated by the capability of fuzzy logic in managing nonlinearity, the
nonlinearity of bias was represented by Takagi-Sugeno (TS) fuzzy model
over the entire range of operating temperature. Then, the fuzzy model
was directly used for compensation of nonlinear bias drift by
subtracting the estimated output from the raw data of RRS. By doing
this, we can guarantee the robust (against temperature variations)
sensor performance throughout entire operating temperature ranges
This paper presents an overview of how inertial sensor technology
is applied in current applications and how it is expected to be applied
in nearand far-term applications. The ongoing trends in inertial sensor
technology development are discussed, namely interferometric fiber-optic
gyros, micro-mechanical gyros and accelerometers, and micro-optical
sensors. Micromechanical sensors and improved fiber-optic gyros are
expected to replace many of the current systems using ring laser
gyroscopes or mechanical sensors. The successful introduction of the new
technologies is primarily driven by cost and cost projections for
systems using these new technologies are presented. Externally aiding
the inertial navigation system (INS) with the global positioning system
(GPS) has opened up the ability to navigate a wide variety of new
large-volume applications, such as guided artillery shells. These new
applications are driving the need for extremely low-cost,
batch-producible sensors
Proposes a robust fuzzy logic-based control scheme for a rotating
active magnetic bearing (AMB) system. We represent the nonlinear
magnetic bearing by means of a Takagi-Sugeno-Kang fuzzy model.
Subsequently a systematic synthesis procedure is used to derive a
nonlinear fuzzy logic control strategy that overcomes the inherent
characteristics of displacement sensitivity and position-dependent
nonlinearity of the AMB. Experimentation and simulation results
demonstrate that the proposed fuzzy controller yields robustness against
harmonic disturbances and parameter uncertainties
This paper presents a review of silicon micromachined
accelerometers and gyroscopes. Following a brief introduction to their
operating principles and specifications, various device structures,
fabrication, technologies, device designs, packaging, and interface
electronics issues, along with the present status in the
commercialization of micromachined inertial sensors, are discussed.
Inertial sensors have seen a steady improvement in their performance,
and today, microaccelerometers can resolve accelerations in the micro-g
range, while the performance of gyroscopes has improved by a factor of
10× every two years during the past eight years. This impressive
drive to higher performance, lower cost, greater functionality, higher
levels of integration, and higher volume will continue as new
fabrication, circuit, and packaging techniques are developed to meet the
ever increasing demand for inertial sensors
Strapdown inertial navigation technology, IEE Radar, Sonar, Navigation and Avionics Series <b>5</b>
- D H Titterton
- J L Weston