Robust Sensors-Fault-Tolerance With Sliding Mode Estimation and Control for PMSM Drives

2018 ◽  
Vol 23 (1) ◽  
pp. 17-28 ◽  
Author(s):  
Suneel Kumar Kommuri ◽  
Sang Bin Lee ◽  
Kalyana Chakravarthy Veluvolu
Keyword(s):  
Fault Tolerance ◽  
Sliding Mode ◽  
Mode Estimation ◽  
Estimation And Control ◽  
And Control

The Problems of Competence Approach

2016 ◽  
pp. 31-43
Author(s):  
Vladimir Zelichenko ◽  
Irina Bushueva
Keyword(s):  
Detailed Analysis ◽  
Sliding Mode ◽  
Learning Systems ◽  
Main Attention ◽  
Mathematical Formula ◽  
Educational Standard ◽  
E Learning ◽  
Estimation And Control ◽  
And Control

In this chapter the authors consider the problems of competence approach, the estimation and the control in world E-Learning Systems. The main attention is on the problem of the formation of evaluation competencies. We consider detailed examples showing how, at a certain stage, learning can be assessed in varying levels of competence. Based on a detailed analysis of the educational standard and assessment of proposed methodology, the authors formalize this assessment and express it by a mathematical formula. The problems of estimation and control are proposed to be solved using feedback based on sliding mode by Prof. Vardan Mkrttchian.

scholarly journals Development of Online Adaptive Traction Control for Electric Robotic Tractors

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3394
Author(s):  
Idris Idris Sunusi ◽  
Jun Zhou ◽  
Chenyang Sun ◽  
Zhenzhen Wang ◽  
Jianlei Zhao ◽  
...  
Keyword(s):  
Friction Coefficient ◽  
Sliding Mode ◽  
Interpolation Method ◽  
Field Tests ◽  
Soil Disturbance ◽  
Wheel Slip ◽  
Slip Ratio ◽  
Optimal Values ◽  
Estimation And Control ◽  
And Control

Estimation and control of wheel slip is a critical consideration in preventing loss of traction, minimizing power consumptions, and reducing soil disturbance. An approach to wheel slip estimation and control, which is robust to sensor noises and modeling imperfection, has been investigated in this study. The proposed method uses a simplified form of wheels longitudinal dynamic and the measurement of wheel and vehicle speeds to estimate and control the optimum slip. The longitudinal wheel forces were estimated using a robust sliding mode observer. A straightforward and simple interpolation method, which involves the use of Burckhardt tire model, instantaneous values of wheel slip, and the estimate of longitudinal force, was used to determine the optimum slip ratio that guarantees maximum friction coefficient between the wheel and the road surface. An integral sliding mode control strategy was also developed to force the wheel slip to track the desired optimum value. The algorithm was tested in Matlab/Simulink environment and later implemented on an autonomous electric vehicle test platform developed by the Nanjing agricultural university. Results from simulation and field tests on surfaces with different friction coefficients (μ) have proved that the algorithm can detect an abrupt change in terrain friction coefficient; it can also estimate and track the optimum slip. More so, the result has shown that the algorithm is robust to bounded variations on the weight on the wheels and rolling resistance. During simulation and field test, the system reduced the slip from non-optimal values of about 0.8 to optimal values of less than 0.2. The algorithm achieved a reduction in slip ratio by reducing the torque delivery to the wheel, which invariably leads to a reduction in wheel velocity.

scholarly journals A Novel Adaptive Speed Observer Using Neural Network and Sliding-Mode for SPIM Drives

2020 ◽  
Vol 7 ◽  
Keyword(s):  
Neural Network ◽  
Sliding Mode ◽  
Speed Control ◽  
Speed Estimation ◽  
Adaptive Model ◽  
Stator Current ◽  
Rotor Flux ◽  
Flux Estimation ◽  
Estimation And Control ◽  
And Control

In this paper, a novel Stator Current Based Model Reference Adaptive System (SC_MRAS) speed estimation scheme using neural network (NN) and Sliding Mode (SM) is proposed to improve the performance of the MRAS speed observer for high-performance Six Phases Induction Motor (SPIM) drives, especially at low and zero speed region, where the poor performance of observers is still always a large challenge. In this novel SC_MRAS scheme, a two-layer linear NN, which has been trained online by means of the Total Least Squares (TLS) algorithm, is used as an adaptive model to estimate the stator current and this model is employed in prediction mode. These novel proposed can ensure that the whole drive system achieves faster satisfactory torque and speed control and strong robustness, the observer operate better accuracy and stability both in transient and steady-state operation. Especially, in this proposed observer, the rotor flux, which is needed for the stator current estimation of the adaptive model and providing to the controller, is identified based on adaptive SM technique. The improvement of Rotor Flux Estimation for SC_MRAS-Based Sensorless SPIM Drives help to eliminate the disadvantages in SC_MRAS based observer such as stator resistance sensitivity, and flux open loop integration which may cause dc drift and initial condition problems or instability in the regenerating mode of operation, therefore, enhancing the rotor flux estimation, speed estimation and control accuracy at very low and zero stator frequency operation help improve the overall observer and drive system performance. The indirect field oriented control (IFOC) for speed control of a sensorless SPIM drive using the proposed observer is built by MATLAB/ Simulink. The simulation results are presented under sensorless speed control performance to validate the effectiveness of the proposed estimation and control algorithms.

Compensation of Input Disturbance in EPS System Using Sliding Mode Observer

2011 ◽  
Vol 110-116 ◽  
pp. 4992-5000
Author(s):  
Byeongjeom Son ◽  
Gwangmin Park ◽  
Daehyun Kum ◽  
Seonghun Lee
Keyword(s):  
Control Algorithm ◽  
Sliding Mode ◽  
Reaction Force ◽  
Sliding Mode Observer ◽  
Disturbance Compensation ◽  
Electric Power Steering ◽  
Input Disturbance ◽  
Power Steering ◽  
Estimation And Control ◽  
And Control

Electric power steering is developed to reduce effort by providing steering assist to the driver of a vehicle. In recent years, a research regarding returnability is performed in order to improve driver's steering feeling. Returnability is affected to friction force in EPS system and reaction force through tire and rack. Usually in the EPS system, friction and Reaction force are uncertain components which are hard to measure. This paper introduces both estimation using sliding mode observer and control algorithm using input disturbance compensation for returnability of EPS system. And simulation confirms the results of the estimation and control algorithm.

Position-Based Visual Servoing of a Mobile Robot with an Automatic Extrinsic Calibration Scheme

Robotica ◽  
2019 ◽  
Vol 38 (5) ◽  
pp. 831-844 ◽  
Author(s):  
Radhe Shyam Sharma ◽  
Santosh Shukla ◽  
Laxmidhar Behera ◽  
Venkatesh K. Subramanian
Keyword(s):  
Mobile Robot ◽  
Gradient Descent ◽  
Visual Servoing ◽  
Sliding Mode ◽  
Single Experiment ◽  
Novel Approach ◽  
Position And Orientation ◽  
Estimation And Control ◽  
Adaptive Nature ◽  
And Control

SUMMARYIn this paper, we present and implement a novel approach for position-based visual servoing. The challenge of controlling the mobile robot while simultaneously estimating the camera to mobile robot transformation is solved. This is achieved using gradient descent (GD)-based estimation and the sliding-mode approach. The GD approach allows online parameter estimation for controlling the robot to achieve a desired position and orientation. The adaptive nature of the parameters demonstrates the robustness of the system. In contrast to existing work, the proposed technique achieves both estimation and control tasks in a single experiment. Simulation and experimental results are provided to validate the performance of the proposed scheme.

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