scholarly journals Laser Beam Pointing Stabilization Control through Disturbance Classification

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1946
Author(s):  
Hui Chang ◽  
Wen-Qi Ge ◽  
Hao-Cheng Wang ◽  
Hong Yuan ◽  
Zhong-Wei Fan
Keyword(s):  
Control System ◽  
Laser Beam ◽  
Control Strategies ◽  
Kinematic Model ◽  
Mechanical Vibration ◽  
External Disturbances ◽  
Stabilization Control ◽  
Laser Systems ◽  
Pointing Control ◽  
The Relationship

In laser systems, beam pointing usually drifts as a consequence of various disturbances, e.g., inherent drift, airflow, transmission medium variation, mechanical vibration, and elastic deformation. In this paper, we develop a laser beam pointing control system with Fast Steering Mirrors (FSMs) and Position Sensitive Devices (PSDs), which is capable of stabilizing both the position and angle of a laser beam. Specifically, using the ABCD matrix, we analyze the kinematic model governing the relationship between the rotation angles of two FSMs and the four degree-of-freedom (DOF) beam vector. Then, we design a Jacobian matrix feedback controller, which can be conveniently calibrated. Since disturbances vary significantly in terms of inconsistent physical characteristics and temporal patterns, great challenges are imposed to control strategies. In order to improve beam pointing control performance under a variety of disturbances, we propose a data-driven disturbance classification method by using a Recurrent Neural Network (RNN). The trained RNN model can classify the disturbance type in real time, and the corresponding type can be subsequently used to select suitable control parameters. This approach can realize the universality of the beam stabilization pointing system under various disturbances. Experiments on beam pointing control under several typical external disturbances are carried out to verify the effectiveness of the proposed control system.

Differential relationship of kinematic model and speed control strategies for a computer-controlled robot manipulator

Robotica ◽  
1986 ◽  
Vol 4 (3) ◽  
pp. 155-162 ◽  
Author(s):  
C. Y. Ho ◽  
Sriwattanathamma Jen
Keyword(s):  
Robot Manipulator ◽  
Control Strategies ◽  
Kinematic Model ◽  
Speed Control ◽  
New Approach ◽  
Manipulator Link ◽  
Moving Coordinate ◽  
Relationship Of ◽  
The Relationship ◽  
Differential Relationship

SummaryThis paper describes a new approach to obtaining a differential relationship of a robot manipulator via the Theoretical Kinematics method which may expedite computational efforts. The method involves a successive transformation of velocities from the end-effector to the base of the manipulator, link by link, using the relationship of moving coordinate systems. The equations obtained are written in the form suitable for programming on a digital computer. Furthermore, this paper also discusses the speed control model for general robot manipulators and together presents the Inverse Jacobian of cases of underdetermined and overdetermined of joint-controlled variables.

scholarly journals A Study on Vision-Based Backstepping Control for a Target Tracking System

Actuators ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 105
Author(s):  
Thinh Huynh ◽  
Minh-Thien Tran ◽  
Dong-Hun Lee ◽  
Soumayya Chakir ◽  
Young-Bok Kim
Keyword(s):  
Control System ◽  
Visual Servoing ◽  
Tracking System ◽  
Experimental Studies ◽  
Imaging Geometry ◽  
Control Scheme ◽  
Decoupled Control ◽  
Control Configuration ◽  
A New Technique ◽  
Pointing Control

This paper proposes a new method to control the pose of a camera mounted on a two-axis gimbal system for visual servoing applications. In these applications, the camera should be stable while its line-of-sight points at a target located within the camera’s field of view. One of the most challenging aspects of these systems is the coupling in the gimbal kinematics as well as the imaging geometry. Such factors must be considered in the control system design process to achieve better control performances. The novelty of this study is that the couplings in both mechanism’s kinematics and imaging geometry are decoupled simultaneously by a new technique, so popular control methods can be easily implemented, and good tracking performances are obtained. The proposed control configuration includes a calculation of the gimbal’s desired motion taking into account the coupling influence, and a control law derived by the backstepping procedure. Simulation and experimental studies were conducted, and their results validate the efficiency of the proposed control system. Moreover, comparison studies are conducted between the proposed control scheme, the image-based pointing control, and the decoupled control. This proves the superiority of the proposed approach that requires fewer measurements and results in smoother transient responses.

FLY System of Green Infrastructure for Coping with Climate Change

2012 ◽  
Vol 260-261 ◽  
pp. 1156-1157
Author(s):  
Goeun Choei ◽  
Jeon Geun Bae ◽  
Sang Min Shin ◽  
Heek Yung Park
Keyword(s):  
Climate Change ◽  
Control System ◽  
Green Infrastructure ◽  
Transition Layer ◽  
Cfd Simulation ◽  
Outdoor Temperature ◽  
External Disturbances ◽  
Indoor Temperature ◽  
Technical Feasibility

This study aims to examine technical feasibility of the FLY system that was developed for control indoor temperature against change of outdoor temperature based on principles for green infrastructure. The FLY system is a control system that protects inner system from external disturbances by making transition layer. The CFD simulation was used for analyzing change of temperature at transition layer and indoor. It was analyzed that the FLY system can reduce variability of indoor temperature against uncertain change of outdoor temperature.

Digital twin of the chip formation process

2020 ◽  
pp. 81-86
Author(s):  
Yu.G. Kabaldin ◽  
D.A. Shatagin ◽  
M.S. Anosov ◽  
A.M. Kuz'mishina
Keyword(s):  
Neural Network ◽  
Control System ◽  
Crystal Lattice ◽  
Network Model ◽  
Intelligent Control ◽  
Neural Network Model ◽  
Formation Process ◽  
Chip Formation ◽  
Intelligent Control System ◽  
The Relationship

The formation of chips during the processing of various materials was studied. The relationship between the type of chips, the type of crystal lattice of the material and the number of sliding systems is shown. A neural network model of chip formation is developed, which allows predicting the type of chips. An intelligent control system for the process of chip formation during cutting is proposed. Keywords: chip formation, crystal lattice, neural network model, type of chips. [email protected]

Energy consumption optimization for AC drives position control

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Branislav Ftorek ◽  
Milan Saga ◽  
Pavol Orsansky ◽  
Jan Vittek ◽  
Peter Butko
Keyword(s):  
Control System ◽  
Energy Saving ◽  
Energy Savings ◽  
Position Control ◽  
Control Strategies ◽  
Content Type ◽  
Ac Drives ◽  
Energy Demands ◽  
Wide Range ◽  
Energy Consumption Optimization

Purpose The main purpose of this paper is to evaluate the two energy saving position control strategies for AC drives valid for a wide range of boundary conditions including an analysis of their energy expenses. Design/methodology/approach For energy demands analysis, the optimal energy control based on mechanical and electrical losses minimization is compared with the near-optimal one based on symmetrical trapezoidal speed profile. Both control strategies respect prescribed maneuver time and define acceleration profile for preplanned rest-to-rest maneuver. Findings Presented simulations confirm lower total energy expenditures of energy optimal control if compared with near-optimal one, but the differences are only small due to the fact that two energy saving strategies are compared. Research limitations/implications Developed overall control system consisting of energy saving profile generator, pre-compensator and position control system respecting principles of field-oriented control is capable to track precomputed state variables precisely. Practical implications Energy demands of both control strategies are verified and compared to simulations and preliminary experiments. The possibilities of energy savings were confirmed for both control strategies. Originality/value Experimental verification of designed control structure is sufficiently promising and confirmed assumed energy savings.

Neural network modeling of the efficiency of response to emergency situations in a multi-level control system

2021 ◽  
Vol 92 ◽  
pp. 79-93
Author(s):  
N. G. Topolsky ◽  
◽  
S. Y. Butuzov ◽  
V. Y. Vilisov ◽  
V. L. Semikov ◽  
...  
Keyword(s):  
Neural Network ◽  
Control System ◽  
Control Systems ◽  
Hierarchical Control ◽  
Hierarchical Systems ◽  
Level Control ◽  
Emergency Situations ◽  
Expert Assessments ◽  
Multi Level ◽  
The Relationship

Introduction. It is important to have models that adequately describe the relationship between the integral indicators of the functioning of the system with the particular indicators of the lower levels of management in complex control systems, in particular in RSChS. Traditional approaches based on normative models often turn out to be untenable due to the impossibility of covering all aspects of the functioning of such systems, as well as due to the high variability of the environment and the values of the set of target indicators. Recently, adaptive machine-learning models have proven to be productive, allowing build stable and adequate models, one of the variants of which is artificial neural networks (ANN), based on the solution of inverse problems using expert estimates. The relevance of the study lies in the development of compact models that allow assessing the effectiveness of the functioning of complex multi-level control systems (RSChS) in emergency situations, developing according to complex scenarios, in which emergencies of various types can occur simultaneously. Goals and objectives. The purpose of the article is to build and test the technology for creating compact models that are adequate to the system of indicators of the functioning of hierarchically organized control systems. This goal gives rise to the task of choosing tools for constructing the necessary models and sources of initial data. Methods. The research tools include methods for analyzing hierarchical systems, mathematical statistics, machine learning methods of ANN, simulation modeling, expert assessment methods, software systems for processing statistical data. The research is based on materials from domestic and foreign publications. Results and discussion. The proposed technology for constructing a neural network model of the effectiveness of the functioning of complex hierarchical systems provides a basis for constructing dynamic models of this type, which make it possible to distribute limited financial and other resources during the operation of the system according to a complex scenario of emergency response. Conclusion. The paper presents the results of solving the problem of constructing an ANN and its corresponding nonlinear function, reflecting the relationship between the performance indicators of the lower levels of the hierarchical control system (RSChS) with the upper level. The neural network model constructed in this way can be used in the decision support system for resource management in the context of complex scenarios for the development of emergency situations. The use of expert assessments as an information basis makes it possible to take into account numerous target indicators, which are extremely difficult to take into account in other ways. Keywords: emergency situations, hierarchical control system, efficiency, artificial neural network, expert assessments

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