Suboptimal Anisotropic Filtering for Linear Discrete Nonstationary Systems with Uncentered External Disturbance

This paper proposes a state-feedback controller using the linear matrix inequality (LMI) approach for the robust position control of a 1-DoF, periodically forced, impact mechanical oscillator subject to asymmetric two-sided rigid end-stops. The periodic forcing input is considered as a persistent external disturbance. The motion of the impacting oscillator is modeled by an impulsive hybrid dynamics. Thus, the control problem of the impact oscillator is recast as a problem of the robust control of such disturbed impulsive hybrid system. To synthesize stability conditions, we introduce the S-procedure and the Finsler lemmas by only considering the region within which the state evolves. We show that the stability conditions are first expressed in terms of bilinear matrix inequalities (BMIs). Using some technical lemmas, we convert these BMIs into LMIs. Finally, some numerical results and simulations are given. We show the effectiveness of the designed state-feedback controller in the robust stabilization of the position of the impact mechanical oscillator under the disturbance.

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A Preprocess Method of External Disturbance Suppression for Carotid Wall Motion Estimation Using Local Phase and Orientation of B-Mode Ultrasound Sequences

BioMed Research International ◽

10.1155/2019/6547982 ◽

2019 ◽

Vol 2019 ◽

pp. 1-15

Author(s):

Qinghui Zhang ◽

Junqiu Li ◽

Zhenping Qiang ◽

Libo He

Keyword(s):

Motion Estimation ◽

Wall Motion ◽

Structural Information ◽

External Disturbance ◽

Estimation Accuracy ◽

Ultrasound Images ◽

Local Phase ◽

Registration Method ◽

Anisotropic Diffusion Filter ◽

Disturbance Suppression

Estimating the motions of the common carotid artery wall plays a very important role in early diagnosis of the carotid atherosclerotic disease. However, the disturbances caused by either the instability of the probe operator or the breathing of subjects degrade the estimation accuracy of arterial wall motion when performing speckle tracking on the B-mode ultrasound images. In this paper, we propose a global registration method to suppress external disturbances before motion estimation. The local vector images, transformed from B-mode images, were used for registration. To take advantage of both the structural information from the local phase and the geometric information from the local orientation, we proposed a confidence coefficient to combine them two. Furthermore, we altered the speckle reducing anisotropic diffusion filter to improve the performance of disturbance suppression. We compared this method with schemes of extracting wall displacement directly from B-mode or phase images. The results show that this scheme can effectively suppress the disturbances and significantly improve the estimation accuracy.

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Spherical Formation Tracking Control of Spacecraft Flying Under Directed Communication Topology and External Disturbance

2020 IEEE 16th International Conference on Control & Automation (ICCA) ◽

10.1109/icca51439.2020.9264563 ◽

2020 ◽

Author(s):

Rui Yu ◽

Yang-Yang Chen ◽

Fa-Xiang Zhang

Keyword(s):

Tracking Control ◽

External Disturbance ◽

Formation Tracking ◽

Communication Topology

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Displacement Estimation Based on Optical and Inertial Sensor Fusion

Sensors ◽

10.3390/s21041390 ◽

2021 ◽

Vol 21 (4) ◽

pp. 1390

Author(s):

Tomasz Ursel ◽

Michał Olinski

Keyword(s):

Sensor Fusion ◽

Inertial Sensor ◽

External Disturbance ◽

Linear Displacement ◽

Measuring System ◽

Displacement Estimation ◽

Mems Accelerometer ◽

Pedestrian Navigation ◽

Complementary Filter ◽

Optical Flow Sensor

This article aims to develop a system capable of estimating the displacement of a moving object with the usage of a relatively cheap and easy to apply sensors. There is a growing need for such systems, not only for robots, but also, for instance, pedestrian navigation. In this paper, the theory for this idea, including data postprocessing algorithms for a MEMS accelerometer and an optical flow sensor (OFS), as well as the developed complementary filter applied for sensor fusion, are presented. In addition, a vital part of the accelerometer’s algorithm, the zero velocity states detection, is implemented. It is based on analysis of the acceleration’s signal and further application of acceleration symmetrization, greatly improving the obtained displacement. A test stand with a linear guide and motor enabling imposing a specified linear motion is built. The results of both sensors’ testing suggest that the displacement estimated by each of them is highly correct. Fusion of the sensors’ data gives even better outcomes, especially in cases with external disturbance of OFS. The comparative evaluation of estimated linear displacements, in each case related to encoder data, confirms the algorithms’ operation correctness and proves the chosen sensors’ usefulness in the development of a linear displacement measuring system.

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Robust Quadrotor Control through Reinforcement Learning with Disturbance Compensation

Applied Sciences ◽

10.3390/app11073257 ◽

2021 ◽

Vol 11 (7) ◽

pp. 3257

Author(s):

Chen-Huan Pi ◽

Wei-Yuan Ye ◽

Stone Cheng

Keyword(s):

Neural Network ◽

Reinforcement Learning ◽

Control Strategy ◽

External Disturbance ◽

Control Agent ◽

Network Control ◽

Outdoor Environment ◽

Disturbance Compensation ◽

Tracking Accuracy ◽

Control Scheme

In this paper, a novel control strategy is presented for reinforcement learning with disturbance compensation to solve the problem of quadrotor positioning under external disturbance. The proposed control scheme applies a trained neural-network-based reinforcement learning agent to control the quadrotor, and its output is directly mapped to four actuators in an end-to-end manner. The proposed control scheme constructs a disturbance observer to estimate the external forces exerted on the three axes of the quadrotor, such as wind gusts in an outdoor environment. By introducing an interference compensator into the neural network control agent, the tracking accuracy and robustness were significantly increased in indoor and outdoor experiments. The experimental results indicate that the proposed control strategy is highly robust to external disturbances. In the experiments, compensation improved control accuracy and reduced positioning error by 75%. To the best of our knowledge, this study is the first to achieve quadrotor positioning control through low-level reinforcement learning by using a global positioning system in an outdoor environment.

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Sensorless Pedalling Torque Estimation Based on Motor Load Torque Observation for Electrically Assisted Bicycles

Actuators ◽

10.3390/act10050088 ◽

2021 ◽

Vol 10 (5) ◽

pp. 88

Author(s):

Riccardo Mandriota ◽

Stefano Fabbri ◽

Matthias Nienhaus ◽

Emanuele Grasso

Keyword(s):

External Disturbance ◽

State Observer ◽

Position Estimation ◽

Load Torque ◽

Estimation Errors ◽

Position Information ◽

Longitudinal Dynamics ◽

Rotor Position ◽

Electrically Assisted ◽

Motor Load

The need for reducing the cost of and space in Electrically Assisted Bicycles (EABs) has led the research to the development of solutions able to sense the applied pedalling torque and to provide a suitable electrical assistance avoiding the installation of torque sensors. Among these approaches, this paper proposes a novel method for the estimation of the pedalling torque starting from an estimation of the motor load torque given by a Load Torque Observer (LTO) and evaluating the environmental disturbances that act on the vehicle longitudinal dynamics. Moreover, this work shows the robustness of this approach to rotor position estimation errors introduced when sensorless techniques are used to control the motor. Therefore, this method allows removing also position sensors leading to an additional cost and space reduction. After a mathematical description of the vehicle longitudinal dynamics, this work proposes a state observer capable of estimating the applied pedalling torque. The theory is validated by means of experimental results performed on a bicycle under different conditions and exploiting the Direct Flux Control (DFC) sensorless technique to obtain the rotor position information. Afterwards, the identification of the system parameters together with the tuning of the control system and of the LTO required for the validation of the proposed theory are thoroughly described. Finally, the capabilities of the state observer of estimating an applied pedalling torque and of recognizing the application of external disturbance torques to the motor is verified.

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Fixed-time tracking control for two-link rigid manipulator based on disturbance observer

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331220983637 ◽

2021 ◽

pp. 014233122098363

Author(s):

Heli Gao ◽

Mou Chen

Keyword(s):

Numerical Simulations ◽

Lyapunov Stability ◽

Stability Theory ◽

Tracking Control ◽

Disturbance Observer ◽

Inverse Dynamics ◽

External Disturbance ◽

Lyapunov Stability Theory ◽

Fixed Time ◽

Extended State

This paper studies the fixed-time disturbance estimate and tracking control for two-link manipulators subjected to external disturbance. A fixed-time extended-state disturbance observer (FxTESDO) is proposed by improving the extended state observer. Also, a fixed-time inverse dynamics tracking control (FxTIDTC) scheme based on the FxTESDO is given for two-link manipulators. The fixed-time convergence of the FxTESDO and FxTIDTC is proved by the Lyapunov stability theory and with the aid of the bi-limit homogeneous technique. Numerical simulations are employed to illustrate the effectiveness of the proposed FxTIDTC.

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