scholarly journals Application of dynamic calibration and control waveform optimization techniques in the fast sweeping reflectometer upgrade on the HL-2A tokamak

2021 ◽  
Vol 16 (05) ◽  
pp. P05020
Author(s):  
Z.C. Yang ◽  
M. Jiang ◽  
Z.B. Shi ◽  
W.L. Zhong ◽  
P.W. Shi ◽  
...  
Keyword(s):  
Optimization Techniques ◽  
Dynamic Calibration ◽  
Waveform Optimization ◽  
Fast Sweeping ◽  
And Control

Optimization in the Design and Control of Robotic Manipulators: A Survey

1989 ◽  
Vol 42 (4) ◽  
pp. 117-128 ◽  
Author(s):  
S. S. Rao ◽  
P. K. Bhatti
Keyword(s):  
Optimal Control ◽  
Robot Manipulator ◽  
Research Effort ◽  
Industrial Robot ◽  
Load Capacity ◽  
Robotic Manipulators ◽  
Optimization Techniques ◽  
Highly Nonlinear ◽  
Manipulator Design ◽  
And Control

Robotics is a relatively new and evolving technology being applied to manufacturing automation and is fast replacing the special-purpose machines or hard automation as it is often called. Demands for higher productivity, better and uniform quality products, and better working environments are primary reasons for its development. An industrial robot is a multifunctional and computer-controlled mechanical manipulator exhibiting a complex and highly nonlinear behavior. Even though most current robots have anthropomorphic configurations, they have far inferior manipulating abilities compared to humans. A great deal of research effort is presently being directed toward improving their overall performance by using optimal mechanical structures and control strategies. The optimal design of robot manipulators can include kinematic performance characteristics such as workspace, accuracy, repeatability, and redundancy. The static load capacity as well as dynamic criteria such as generalized inertia ellipsoid, dynamic manipulability, and vibratory response have also been considered in the design stages. The optimal control problems typically involve trajectory planning, time-optimal control, energy-optimal control, and mixed-optimal control. The constraints in a robot manipulator design problem usually involve link stresses, actuator torques, elastic deformation of links, and collision avoidance. This paper presents a review of the literature on the issues of optimum design and control of robotic manipulators and also the various optimization techniques currently available for application to robotics.

Genetic Algorithm-Based Maximum Likelihood Parameter Estimation for Transit Buses

2001 ◽  
Author(s):  
Jie Xiao ◽  
Bohdan T. Kulakowski
Keyword(s):  
Parameter Estimation ◽  
Maximum Likelihood ◽  
Dynamic Models ◽  
Estimation Method ◽  
Optimization Techniques ◽  
Model Parameters ◽  
Parameter Estimation Method ◽  
Transit Buses ◽  
Simulation And Control ◽  
And Control

Abstract Vehicle dynamic models include parameters that qualify the dependence of input forces and moments on state and control variables. The accuracy of the model parameter estimates is important for modeling, simulation, and control. In general, the most accurate method for determining values of model parameters is by direct measurement. However, some parameters of vehicle dynamics, such as suspension damping or moments of inertia, are difficult to measure accurately. This study aims at establishing an efficient and accurate parameter estimation method for developing dynamic models for transit buses, such that this method can be easily implemented for simulation and control design purposes. Based on the analysis of robustness, as well as accuracy and efficiency of optimization techniques, a parameter estimation method that integrates Genetic Algorithms and the Maximum Likelihood Estimation is proposed. Choices of output signals and estimation criterion are discussed involving an extensive sensitivity analysis of the predicted output with respect to model parameters. Other experiment-related aspects, such as imperfection of data acquisition, are also considered. Finally, asymptotic Cramer-Rao lower bounds for the covariance of estimated parameters are obtained. Computer simulation results show that the proposed method is superior to gradient-based methods in accuracy, as well as robustness to the initial guesses and measurement uncertainty.

Design and Control of Forming Processes Using Optimization Techniques

1999 ◽  
Author(s):  
O. Ghouati ◽  
H. Lenoir ◽  
J. C. Gelin ◽  
M. Baida
Keyword(s):  
Finite Element ◽  
Sheet Metal ◽  
Thickness Distribution ◽  
Optimization Technique ◽  
Optimization Techniques ◽  
Finite Element Code ◽  
Optimal Process ◽  
Shell Elements ◽  
Numerical Examples ◽  
And Control

Abstract The paper deals with the design and control of forming processes. The finite element code used is based on isoparametric shell elements with three or four nodes, the workpiece being considered as a sheet metal. An optimization technique is used in order to achieve the design or the control of the process by determining the optimal process parameters. The criterion used in that purpose can be based on thickness distribution as well as the respect of the final shape desired for the product. Numerical examples are presented as illustration.

Optimization Methods in Continuous Improvement Models

2019 ◽  
Vol 6 (1) ◽  
pp. 46-59
Author(s):  
Brian J. Galli
Keyword(s):  
Continuous Improvement ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
Problem Analysis ◽  
Measure Problem ◽  
Continuous Improvement Model ◽  
Current Utilization ◽  
And Control ◽  
Theory Of Constraint

There are numerous processes used to implement quality, such as TQM, 6 Sigma, and Lean. For these quality processes to remain effective, a continuous improvement model is required and implemented from time to time. Some of these models include Define, Measure, Analyse, Improve and Control (DMAIC); Plan, Do, Check, and Act (PDCA); Identify, Measure, Problem Analysis, Remedy, Operationalize, Validate, and Evaluate (IMPROVE); and Theory of Constraint (TOC). Furthermore, continuous improvement tools need to remain effective through the use of optimization techniques to produce the best possible outcomes. This article discusses some of the current utilization of these tools and proposes different optimizing techniques and variations to make robust quality implementation tools.

Study on Modeling and Simulation of Digital Factory Technology in Complex Production Development

2011 ◽  
Vol 383-390 ◽  
pp. 2383-2389
Author(s):  
Shan Li ◽  
Yan En Wang ◽  
Bing Chen ◽  
Ting Yang ◽  
Qian Li Dong
Keyword(s):  
Service Oriented Architecture ◽  
Integrated Approach ◽  
Optimization Techniques ◽  
Simulation Technology ◽  
Production Engineering ◽  
Digital Factory ◽  
Simulation And Optimization ◽  
Planning And Control ◽  
Service Oriented ◽  
And Control

This paper describes an innovative systematic approach to factory automation. Northwestern Polytechnical University developed an Enterprise-level Digital fActory and its Simulation Platform, NPU-EDASP that adopted service-oriented architecture methodology to design and develop this software. In particular, it specifies the simulation technology within the NPU-EDASP platform to bridge the gape exits among products and production manufacturing process. In an advanced stage, simulation technology can be applied in the NPU-EDASP to enhance the operative production planning and control. Further, the combination of simulation and optimization techniques will improve and optimize material flow, resource utilization and logistics in production engineering processes. A case study of a model demonstrates that the NPU-EDASP digital factory offers an integrated approach to promote the ability of production engineering.

A Report on Optimization Techniques at the AIAA Atmospheric Flight Mechanics and Guidance and Control Conference

2007 ◽  
Vol 3 (2) ◽  
pp. 203-206
Author(s):  
Walton E. Williamson ◽  
Ronald W. Greene ◽  
D. J. Bell ◽  
Prabhat Hajela
Keyword(s):  
Optimization Techniques ◽  
Flight Mechanics ◽  
Guidance And Control ◽  
And Control

scholarly journals An Experimental Approach towards Motion Modeling and Control of a Vehicle Transiting a Non-Newtonian Environment

2021 ◽  
Vol 5 (3) ◽  
pp. 104
Author(s):  
Isabela Birs ◽  
Cristina Muresan ◽  
Ovidiu Prodan ◽  
Silviu Folea ◽  
Clara Ionescu
Keyword(s):  
Fractional Order ◽  
Process Model ◽  
Real Life ◽  
Optimization Techniques ◽  
Motion Modeling ◽  
Modeling And Control ◽  
Control Approach ◽  
Real Life Data ◽  
And Control ◽  
The Mathematical Model

The present work tackles the modeling of the motion dynamics of an object submerged in a non-Newtonian environment. The mathematical model is developed starting from already known Newtonian interactions between the submersible and the fluid. The obtained model is therefore altered through optimization techniques to describe non-Newtonian interactions on the motion of the vehicle by using real-life data regarding non-Newtonian influences on submerged thrusting. For the obtained non-Newtonian fractional order process model, a fractional order control approach is employed to sway the submerged object’s position inside the viscoelastic environment. The presented modeling and control methodologies are solidified by real-life experimental data used to validate the veracity of the presented concepts. The robustness of the control strategy is experimentally validated on both Newtonian and non-Newtonian environments.

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