Estimation Of Angular Acceleration Research Articles

Angular acceleration estimation and aerodynamic parameter identification based on angular velocity equivalent model

Conventional angular acceleration estimation methods generate non-negligible errors when the control surface rapidly deflects; hence, the estimated angular acceleration cannot be used for aerodynamic parameter identification directly. This paper proposes an angular acceleration estimation method based on angular velocity equivalent model. The angular acceleration of the angular velocity equivalent model, whose angular velocity response is consistent with the flight test data, is used as the estimated angular acceleration. Firstly, the equivalent angular velocity model is established by combining the generic aerodynamic model with the rotational dynamic equations of aircraft. Secondly, the angular velocity data and the control surface deflection data are synchronized. Finally, the angular velocity response of the equivalent model is used as the predictor, and the estimated angular acceleration is obtained by extended Kalman filter. The aerodynamic parameter identification and validation are carried out using the estimated angular acceleration of a large civil aircraft flight test data. The results show that the angular acceleration obtained through the proposed angular acceleration estimation method meets the accuracy requirement of aerodynamic parameter identification.

Dynamic characteristics analysis and robust transition control of tail-sitter VTOL UAVs

The strong nonlinear dynamics of tail-sitter vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAVs) have consistently constrained their applications. Particularly, the widely-varying flight speed and attitude during the transition flights pose substantial challenges for the controller design. In order to gain a clear understanding of the nonlinear transition flights, the long- and short- period dynamic characteristics of tail-sitter UAVs are investigated for the first time. The results reveal that the short-period mode exhibits either sluggish response or excessive overshoot in different transition stages, primarily due to the widely-varying damping ratio and natural angular frequency. Even worse, the long-period mode can diverge due to positive poles. To address these issues, a systematic controller is proposed. First, the transition trajectory is optimized and the optimal control inputs are employed in a feedforward manner to trim the nominal forces and moments. On this basis, a discrete-time linear quadratic regulation (LQR) controller with a predefined decay rate is developed to position the desired poles, and a novel angular acceleration estimation method is introduced to compensate for unmodeled dynamics. Simulations under different uncertainties indicate that the proposed control method performs better in both transition trajectory tracking and uncertainty suppression, compared to the PID and incremental nonlinear dynamic inversion (INDI) controllers.

Generalized Gini indices–enhanced sparsity decomposition for rotating machinery health assessment using a rotary encoder

ABSTRACT Rotary encoder signal has been attracting considerable attention for health estimation of the rotating elements, since its advantages in lower testing costs and sensitive to torsional stiffness loss caused by incipient faults. However, the practical encoder signal often keeps low signal-to-noise ratio due to its instantaneous angular acceleration conventional method, which brings new challenges for the commonly used feature extraction methods. Sparse decomposition is an efficient method for fault impact features extracting of rotating machinery. However, limited by the quality of initial dictionary and the learning efficiency of K-SVD algorithm, commonly used sparse decomposition is susceptible to the signal noise, especially when unsuitable initial atoms are applied. To overcome this problem, a simple but effective framework term Generalized Gini indices-enhanced sparsity decomposition is established in this paper for practical encoder signal analysis. Firstly, the de-trended and frequency domain weighting methods are used for instantaneous angular acceleration estimation. After that, a Generalized Gini indices guided tunable Q-factor wavelet filter is introduced for the atom selection. Then, the shift-invariant K-SVD method is introduced for dictionary updating and sparse coefficients calculation. Through the analysis of simulation and experiment, the transient characteristics of the gear can be extracted well which provides an alternative methodology for incipient fault detection of rotating machinery.

Improved state estimation of a robot end-effector using laser tracker and inertial sensor fusion

An increased focus on automation in the aerospace industry has led to a demand for flexible manipulators that can achieve high trajectory following accuracy for tasks like machining, joining, and painting. These tasks require an accurate, real-time state estimation of the robot’s end-effector. Currently, the most accurate methods of estimating the end-effector state involve using high-end position and orientation sensors such as laser trackers and camera-based metrology systems and tend to focus on accurately estimating the end-effector position and orientation. This paper investigates the potential benefits and practical considerations in supplementing the data from these kinds of sensors with acceleration and angular velocity measurements obtained from an inertial measurement unit (IMU) to improve the overall robot end-effector state estimation including its velocity and angular acceleration. The sensor fusion is achieved using a Kalman Filter for motions with no rotation and using a Particle Filter for motions with rotation. Simulation results indicate that up to 95% improvement in velocity estimation accuracy, and up to 45% improvement in angular acceleration estimation accuracy can be achieved by fusing IMU data with laser tracker data. In addition, the paper analyzes the thresholds of sensor accuracy beyond which fusion no longer provides significant benefits. Finally, hardware experiments are conducted using a fusion of robot encoder data with IMU measurements. These experiments indicate up to 40% improvement in velocity estimation accuracy from the sensor fusion.

로봇팔의 시간지연 제어기에서 각 가속도 추정에 대한 추종 성능 비교연구

This paper presents a comparative study of tracking performances between several methods of estimating acceleration signals for a time-delayed controller(TDC) of a robot manipulator. To implement the time-delayed controller completely, there are three requirements: 1) Fast sampling time, 2) constant inertia value, and 3) angular acceleration signals. This paper focuses on the acceleration estimation for TDC. Several methods for angular acceleration estimation are tested: 1) Finite difference method with low pass filtering, 2) Kalman filtering, 3) desired angular acceleration, 4) control input, 5) Jacobian relationship. We experimented five methods on one arm of a dual arm robot to follow a circular trajectory and their tracking performances are compared.

Angular Rate Sensitive Method of Magnetically Suspended Control & Sensing Gyroscope Based on Deflection Current and Angle

A high-precision angular rate sensitive method of spacecraft based on deflection current and deflection angle measurement is proposed in this paper, in the view of this problem that the angular rate sensitive accuracy of spacecraft using Magnetically Suspended Control & Sensing Gyroscope (MSCSG) is affected by the deflection disturbance of the rotor relative to the stator. Firstly, the moment model of the rotor and the Lorentz force magnetic bearing (LFMB) is established, and the main factors affecting the sensitive accuracy of MSCSG are analyzed in detail; The inertial coupling terms which have great influence on the sensitivity accuracy are effectively retained by the rotor deflection angular velocity and angular acceleration estimation. The high precision analytical expression of attitude angular rate is derived and the error analysis is carried out; It is verified by simulation and experiment that the high precision sensitive method proposed in this paper has higher sensitive precision than the traditional measurement method, which greatly improves the zero bias stability index of MSCSG. The method proposed in this paper has important reference significance for improving the integration of magnetic suspension rotor control and sense performance.

Planetary gearbox fault diagnosis via rotary encoder signal analysis

Planetary gearbox fault diagnosis via vibration signal analysis is highly challenging, because of vibration spectral complexity due to gear fault modulation and especially time-varying transmission path effects. Rotary encoder signals contain gear fault signature, and are free of extra amplitude modulation caused by time-varying transmission path effects. Hence, encoder signal analysis provides a potentially effective approach to overcome difficulties in planetary gearbox fault diagnosis. Gear faults induce jitters in instantaneous angular speed, thus leading to changes in pulse interval of encoder signals. We proposed to analyze the order spectrum of repetitive temporal interval reciprocal between adjacent encoder pulses in the angle domain. Our proposed method is free from the algorithmic complexity of instantaneous angular speed or acceleration estimation, and more importantly addresses the difficult issue of planetary gearbox fault diagnosis under time-varying speeds. It is validated through lab experiments of a planetary gearbox under both constant and time-varying speed conditions. Localized faults on the sun, planet and ring gears are all successfully diagnosed.

Robust proportional incremental nonlinear dynamic inversion control of a flying-wing tailsitter

Tailsitter unmanned aerial vehicles are utilized extensively nowadays since they merge advantages of both fixed-wing unmanned aerial vehicles and rotary-wing unmanned aerial vehicles. However, their attitude control suffers from unknown nonlinearities and disturbances due to the wide flight envelope. To solve the problems, a robust attitude controller based on a newly designed flying-wing tailsitter is proposed in this paper. By employing the angular acceleration feedback to compensate unmodeled dynamics, the proportional incremental nonlinear dynamic inversion control law is first developed. The proportional incremental nonlinear dynamic inversion strengthens the conventional nominal gain incremental nonlinear dynamic inversion with a proportional term to reflect the change of the angular acceleration more directly. Therefore, the tailsitter has a quicker response and performs better in suppressing model uncertainties and external disturbances. Since the angular acceleration is difficult to measure in practice, an angular acceleration estimation method is then established to provide accurate signals for the proportional incremental nonlinear dynamic inversion. The signals are derived as complementary results of model prediction method and direct differential method. Theoretical analysis and systematic simulations are conducted to corroborate the effectiveness of the developed estimation method as well as the robustness of the proposed controller.

Flight Control Design using Incremental Nonlinear Dynamic Inversion with Fixed-lag Smoothing Estimation

In this study, a flight control design strategy based on incremental nonlinear dynamic inversion (INDI) and smoothing algorithm is presented. The INDI is an enhanced version of the nonlinear dynamic inversion technique with a better robust performance. It reduces the aircraft model dependence via the feedback information of the state derivative, that is, angular acceleration for the aircraft attitude motion (or angular velocity related to the wind axis parameters). However, the state derivatives cannot always be obtained by direct measurement, thus they need to be estimated on-line. Moreover, taking into account that INDI requires one-step delay of state derivative and the fact that the inertial measurement unit (IMU) operates faster than the flight control computer (FCC), there will be additional information that can be used to improve the estimation. Therefore, a fixed-lag smoothing algorithm based on a discrete Kalman filter is proposed for angular velocity and angular acceleration estimation. The smoother utilizes the state variable from the sensor measurement and thus dealing with noise and delay.

Line-of-sight stabilization of roll-pitch seeker using differentiator-based disturbance compensation control

A new control problem of roll-pitch seeker about the disturbance coupling is investigated in this work. Previous control strategies of roll-pitch seeker rarely considered the effects of the dynamic coupling disturbances from the missile angular motion, and because of the polar coordinate structure, the disturbance rejection strategies of yaw-pitch seeker cannot be utilized directly on roll-pitch seeker. Thus this article presents a new control strategy to improve the disturbance rejection ability of roll-pitch seeker. To analyze the disturbance coupling problem, the roll-pitch seeker model is derived with consideration of the missile body angular motion and torque disturbances. The motion equation of roll-pitch seeker shows that part of the dynamic coupling disturbance can be eliminated by certain choices of inertial parameters. The rest of disturbance is reduced by the stabilization loops using a differentiator-based disturbance compensation controller. Particularly, a missile body angular acceleration estimation method is designed for the compensator based on an adaptive differentiator. In addition, comparisons with other control strategies are carried out via numerical simulations, and the results confirm the effectiveness of the proposed method.

Attitude and Altitude Control of Unmanned Aerial-Underwater Vehicle Based on Incremental Nonlinear Dynamic Inversion

A vehicle able to navigate both in the air and underwater is referred to an unmanned aerial-underwater vehicle (UAUV). Aiming at the attitude and altitude control of UAUVs, an incremental dynamic inverse control (INDI) method with second-order low-pass filters is proposed. Based on the underwater motion model of an UAUV and the incremental attitude control model, the relationship between thrust increment and angular acceleration increment is obtained through Taylor series expansion and angular acceleration feedback. Subsequently, attitude and altitude controllers based on nonlinear dynamic inversion (NDI) and INDI are designed and their robustness is analyzed. By introducing second-order low-pass filters at the part of control and feedback, the accuracy of the angular acceleration estimation is improved and the time synchronization of the control system is ensured. Simulation results demonstrated that when introducing external disturbances and uncertainties, the INDI control with second-order low-pass filters proposed in this article can track the reference signal faster and more accurately than the NDI control.

Comparison of joint angle, velocity and acceleration estimators for hydraulically actuated manipulators to a novel dynamical approach

Excavators are used for a wide range of applications like earthworks and material handling. Assistance systems are becoming more common to support the operator. For monitoring and control based assistance functions the angular position, velocity and acceleration of the joints from the working implement are required. Commercial systems often use inertial measurement units, consisting of triaxial accelerometers and gyroscopes, to accomplish an estimation of those states. A novel joint angle, velocity and acceleration estimation for hydraulic manipulators is proposed and compared to state of the art methods. A decentralized kinematic filter using no information about the underlying system and a centralized kinematic filter taking the system kinematics into account are implemented as state of the art approaches. Both filters only use inertial measurement units to obtain information about the current state of the system. The novel centralized dynamic filter uses the same information as the centralized kinematic filter and extends it by a dynamic model containing additional information about the angular acceleration due to pressure readings of the hydraulic cylinders. Kalman filtering is used to combine the derived system and measurement models with the sensor information. The methods are evaluated on a material handling excavator for single and coupled movements of the working implement. The novel centralized dynamic filter enables improvements for the angular acceleration estimation compared to the decentralized and centralized kinematic filter. Less noise of the acceleration estimation and a better tracking of the actual acceleration are shown.

Estimation of angular velocity and acceleration with Kalman filter, based on position measurement only

This paper presents a method to obtain good synchronous and instantaneous estimates in position, velocity and acceleration; using a position measurement only. The proposed method shows better estimates in position, velocity and acceleration than other methods such as nonlinear tracking differentiator (TD), extended state estimation (ESO) and digital differentiator based on Taylor series (DDBTS). The proposed method allows for an increased accuracy of estimates by generating a feedback frequency obtained to the position measurement signals. The model and method proposed in this paper reduce the error when the measurement signal presents a change in frequency. The model update and adjusts simultaneously to changes in sample rates using a feedback frequency estimate. The proposed method was validated with the QNET DC Motor Control Trained (DCMCT). Since the method requires the measurement position only from an encoder, it eliminates the need for more sensors for velocity and acceleration, thus begin less costly.

Spacecraft Angular Rates and Angular Acceleration Estimation Using Single-Gimbal Magnetically Suspended Control Moment Gyros

To achieve the high-precision angular velocity and angular acceleration estimation of spacecraft under high dynamic conditions, a novel method based on single-gimbal magnetically suspended control moment gyroscope (SGMSCMG) configuration is proposed in this paper. Both the angular rates and angular accelerations have been resolved analytically, and their comparative estimation precision between the proposed method and the traditional one has been further analyzed in the presence of gyro error and installation error. Compared to the traditional three-orthogonal configuration method, the proposed one employs any three SGMSCMGs in the control actuator configuration instead of additional rate gyros. All the inertial coupling items are retained tactfully in the angular rate and angular acceleration solution by the proposed method. Thus, the relative estimation accuracy of the attitude rate depends only on the gyro error and its installation error in practice, which do not decay under high dynamic conditions anymore. And its corresponding angular acceleration estimation precision is determined by the size of angular velocity instead of angular acceleration under the given error condition. The semiphysical simulation results demonstrate the correctness and superiority of the proposed estimation method.

Improving backdrivability in preoperative manual manipulability of minimally invasive surgery robot

PurposeThe purpose of this paper is to propose a control algorithm to improve the backdrivability performance of minimally invasive surgical robotic arms, so that precise manual manipulations of robotic arms can be performed in the preoperative operation.Design/methodology/approachFirst, the flexible-joint dynamic model of the 3-degree of freedom remote center motion (RCM) mechanisms of minimally invasive surgery (MIS) robot is derived and its dynamic parameters and friction parameters are identified. Next, the angular velocities and angular accelerations of joints are estimated in real time by the designed Kalman filter. Finally, a control algorithm based on Kalman filter is proposed to enhance the backdrivability of RCM mechanisms by compensating for the internally generated gravitational, frictional and inertial resistances experienced during the positioning and orientating.FindingsThe parameter identification for RCM mechanisms can be experimentally evaluated from comparison between the measured torques and the reconstructed torques. The accuracy and convergence of the real-time estimation of angular velocity and acceleration of the joint by the designed Kalman filter can be verified from corresponding simulation experiments. Manual adjustment experiments and animal experiments validate the effectiveness of the proposed backdrivability control algorithm.Research limitations/implicationsThe backdrivability control algorithm presented in this paper is a universal method to enhance the manual operation performance of robots, which can be used not only in the medical robot preoperative manual manipulation but also in robot haptic interaction, industrial robot direct teaching and active rehabilitation training of rehabilitation robot and so on.Originality/valueCompared with other backdrivability design methods, the proposed algorithm achieves good backdrivability for RCM mechanisms without using force sensors and accelerometers. In addition, this paper presents a new static friction compensation approach for a joint moving with very low velocity.

An asymptotic differentiation approach of signals in velocity tracking control of DC motors

An output feedback dynamic control scheme is proposed for efficient velocity trajectory tracking tasks for direct current (DC) electric motors. An asymptotic differentiation approach of signals is also introduced and applied for real-time angular acceleration estimation. The novel feature of this differentiator of signals is that it does not require any system mathematical model. Hence the presented differentiation approach admits a wide variety of practical applications in diverse electric power systems that require signal differentiation for their control and identification. The synthesis of the differentiation scheme considers the possible practical scenario of contaminated output signals with reasonably small noise. Some computer simulations results are included to show controller robustness to reject completely unknown chaotic load torque disturbances and parametric uncertainty, as well as effectiveness of the differentiation scheme of signals.

Sensor Fusion for Joint Kinematic Estimation in Serial Robots Using Encoder, Accelerometer and Gyroscope

Open-chain manipulator robots play an important role in the industry, since they are utilized in applications requiring precise motion. High-performance motion of a robot system mainly relies on adequate trajectory planning and the controller that coordinates the movement. The controller performance depends of both, the employed control law and the sensor feedback. Optical encoder feedback is the most used sensor for angular position estimation of each joint in the robot, since they feature accurate and low noise angular position measurements. However, it cannot detect mechanical imperfections and deformations common in open chain robots. Moreover, velocity and acceleration cannot be extracted from the encoder data without adding phase delays. Sensor fusion techniques are found to be a good solution for solving this problem. However, few works has been carried out in serial robots for kinematic estimation of angular position, velocity and acceleration, since the delays induced by the filtering techniques avoids its use as controller feedback. This work proposes a novel sensor-fusion-based feedback system capable of providing complete kinematic information from each joint in 4-degrees of freedom serial robot, with the contribution of a proposed methodology based on Kalman filtering for fusing the information from optical encoder, gyroscope and accelerometer appended to the robot. Calibration and experimentation are carried out for validating the proposal. The results are compared with another kinematic estimation technique finding that this proposal provides more information about the robot movement without adding state delays, which is important for being used as controller feedback.

인체 머리부 6 자유도 운동 측정의 신뢰성 향상을 위한 가속도계 감도축의 옵셋(offset) 추정

Notion sickness is well known to be caused by long time exposure to the very low frequency motion in the multiple axes of human body Since the vestibular system for the perception of low frequency motion is located in the head, accurate measurement of 6 degree of freedom head motion is of great importance. In this study, the measurement system consisting of a safety helmet and 9 translational accelerometers was constructed for the estimation of 3 translational and 3 rotational motions of human head. Since estimation errors of 3 rotational components can be significantly magnified even by small offset of the sensitivity axis from the geometric center of an accelerometer, accurate measurement of sensitivity axis must be preceded. The method for accurate estimation of the offset was proposed, and the effect of offset on the estimation of angular acceleration was investigated.

Angular acceleration estimation and feedback control: An experimental investigation

Angular acceleration estimation and its application in acceleration feedback control are investigated experimentally in the paper. In combination of Newton Predictor (NP) with Kalman Filter (KF), a new predictive estimator for angular acceleration, called Newton Predictor Enhanced Kalman Filter (NPEKF) is proposed. This estimator provides a wide bandwidth and a small phase lag of the estimated acceleration while attenuating noises. Based on the estimated acceleration an acceleration feedback control (AFC) is presented for multiple degree-of-freedom (DOF) mechatronic system. The design of AFC is specified in terms of its stability and ability in suppressing dynamic disturbances. Experiments are conducted on a 2-DOF direct-drive manipulator. The frequency responses of the acceleration estimated by NP, KF and NPEKF are compared with those of the measured acceleration via linear accelerometer. The performance of AFC using the estimated acceleration is assessed against that using the measured acceleration. This study has shown that the proposed NPEKF estimator is able to supply the AFC with reliable required acceleration.

Independent traction control for uneven terrain using stick-slip phenomenon: application to a stair climbing robot

Mobile robots are being developed for building inspection and security, military reconnaissance, and planetary exploration. In such applications, the robot is expected to encounter rough terrain. In rough terrain, it is important for mobile robots to maintain adequate traction as excessive wheel slip causes the robot to lose mobility or even be trapped. This paper proposes a traction control algorithm that can be independently implemented to each wheel without requiring extra sensors and devices compared with standard velocity control methods. The algorithm estimates the stick-slip of the wheels based on estimation of angular acceleration. Thus, the traction force induced by torque of wheel converses between the maximum static friction and kinetic friction. Simulations and experiments are performed to validate the algorithm. The proposed traction control algorithm yielded a 40.5% reduction of total slip distance and 25.6% reduction of power consumption compared with the standard velocity control method. Furthermore, the algorithm does not require a complex wheel-soil interaction model or optimization of robot kinematics.