Deployment the Spoke of a Large-Sized Transformable Refl ector Using a Sequential Optimization Algorithm

2021 ◽  
Vol 22 (8) ◽  
pp. 433-441
Author(s):  
S. A. Kabanov ◽  
D. S. Kabanov
Keyword(s):  
Optimization Algorithm ◽  
Simulation Modeling ◽  
Spreading Rate ◽  
Terminal Condition ◽  
Sequential Optimization ◽  
Bending Vibrations ◽  
The Maximum Principle ◽  
Composed Functions ◽  
Comparison Of The Results ◽  
Weight Coefficients

The use of large-sized opening reflectors close-packed in spacecraft is associated with spreading the spokes at a given angle, extending the fragments of the spokes and adjusting the shape of the radio-reflecting mesh. The problem of optimizing these processes with automatic output of the reflector to the deployed working state is urgent. The optimal control problem of spreading spokes of a large-sized space-based reflector with respect to bending vibrations is investigated in the article. The optimization process is complicated by ensuring convergence of iterative procedure for control finding. The bending vibrations of the spokes complicate the task of spreading. That makes it difficult to fix spokes when reaching the stops. In this paper the mathematical model of spoke dynamics is improved with respect to spoke’s bend change in length and in time, the model takes into account the presence of stop and retainer devices and an actuator. It is proposed to consider a hierarchy of two target composed functions and develop an algorithm for sequential optimization for a smooth exit to the stops. It is suggested to include the terminal condition for the angular spreading rate in the first criterion. A study was carried out using mathematical simulation for the process of turning the spoke by a given angle at small values of the angular velocity at the final moment of time taking into account bending vibrations. The exact values of the weight coefficients included in the target composed functions are found. Weight coefficients influence on transient processes is investigated. The performance of the algorithm was checked when the value of the optimization interval was changed. The comparison of the results of simulation modeling with control options using the PID controller, application of an algorithm with a predictive model and an algorithm with optimal correction of the control structure, revealed by means of the maximum principle, was carried out. The results of simulation modeling foe spokes spreading process using the sequential optimization algorithm demonstrate the achievement of the required accuracy with permissible tolerance residual vibrations. The developed algorithm of sequential optimization forms control in a real time and it is recommended to use it in more complex solutions under random disturbances using measurement process and optimization of observation intervals.

A Sequential Optimization Algorithm Using Metamodel-Based Multilevel Analysis

2009 ◽  
Vol 33 (9) ◽  
pp. 892-902 ◽  
Author(s):  
Seok-Heum Baek ◽  
Kang-Min Kim ◽  
Seok-Swoo Cho ◽  
Deuk-Yul Jang ◽  
Won-Sik Joo
Keyword(s):  
Multilevel Analysis ◽  
Optimization Algorithm ◽  
Sequential Optimization

Global Optimization Algorithm of Subaperture Stitching Weight Coefficients

2013 ◽  
Vol 42 (8) ◽  
pp. 943-949
Author(s):  
田爱玲 TIAN Ailing ◽  
吴世霞 WU Shixia ◽  
刘丙才 LIU Bingcai ◽  
张鹏飞 ZHANG Peifei
Keyword(s):  
Global Optimization ◽  
Optimization Algorithm ◽  
Global Optimization Algorithm ◽  
Weight Coefficients

A Sequential Algorithm for Possibility-Based Design Optimization

2006 ◽  
Author(s):  
Jun Zhou ◽  
Zissimos P. Mourelatos
Keyword(s):  
Design Optimization ◽  
Optimization Algorithm ◽  
Computational Cost ◽  
Possibility Theory ◽  
Sequential Optimization ◽  
Sequential Algorithm ◽  
Computationally Efficient ◽  
Worst Case ◽  
Reliability Based Design ◽  
Design Variables

Deterministic optimal designs that are obtained without taking into account uncertainty/variation are usually unreliable. Although reliability-based design optimization accounts for variation, it assumes that statistical information is available in the form of fully defined probabilistic distributions. This is not true for a variety of engineering problems where uncertainty is usually given in terms of interval ranges. In this case, interval analysis or possibility theory can be used instead of probability theory. This paper shows how possibility theory can be used in design and presents a computationally efficient sequential optimization algorithm. After, the fundamentals of possibility theory and fuzzy measures are described, a double-loop, possibility-based design optimization algorithm is presented where all design constraints are expressed possibilistically. The algorithm handles problems with only uncertain or a combination of random and uncertain design variables and parameters. In order to reduce the high computational cost, a sequential algorithm for possibility-based design optimization is presented. It consists of a sequence of cycles composed of a deterministic design optimization followed by a set of worst-case reliability evaluation loops. Two examples demonstrate the accuracy and efficiency of the proposed sequential algorithm.

SIMULATION MODELING OF RUNOFF REGULATION BY AN IRRIGATION WATER RESERVOIR UNDER THE CONDITIONS OF LOW-WATER

2020 ◽  
pp. 106-111
Author(s):  
I.G. VELIEV ◽  
◽  
V.V. ILJINICH ◽  
A.V. PERMINOV
Keyword(s):  
Reservoir Operation ◽  
Simulation Modeling ◽  
River Flow ◽  
Water Reservoir ◽  
Reservoir Management ◽  
Water Yield ◽  
Short Term ◽  
Runoff Regulation ◽  
Comparison Of The Results ◽  
Operation Schedule

The article is dealt with the analysis of the Krasnodar water reservoir operation carried out under various options for regulating river flow. The considered options for water reservoir management were implemented in accordance with the current operation schedule and new regulations developed on the basis of simulation modeling using the IMIT-BALANS model which uses optimization elements. Previously this model was adapted by means of a more detailed discreteness of intra-annual intervals. Comparison of the results of the reservoir operation in relation to the deficient planned water yield for dry year conditions showed that the developed new regulations for reservoir management for low water years are much more effective. Their use by the decision-maker (DM) would reduce deficit of water consumption provided that short-term and medium-term runoff forecasts are used.

scholarly journals Assessment of the Effect of Energy Consumption on Trajectory Improvement for a Car-like Robot

Robotica ◽  
2019 ◽  
Vol 37 (11) ◽  
pp. 1998-2009 ◽  
Author(s):  
Francisco Valero ◽  
Francisco Rubio ◽  
Carlos Llopis-Albert
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Mobile Robot ◽  
Optimization Algorithm ◽  
Random Distribution ◽  
Lower Cost ◽  
Maximum Velocity ◽  
Optimization Techniques ◽  
Sequential Optimization ◽  
Inertial Parameters

SummaryReducing the energy consumed by a car-like mobile robot makes it possible to move at a lower cost, yet it takes more working time. This paper proposes an optimization algorithm for trajectories with optimal times and analyzes the consequences of restricting the energy consumed on the trajectory obtained for a car-like robot. When modeling the dynamic behavior of the vehicle, it is necessary to consider its inertial parameters, the behavior of the motor, and the basic properties of the tire in its interaction with the ground. To obtain collision-free, minimum-time trajectories quadratic sequential optimization techniques are used, where the objective function is the time taken by the robot to move between two given configurations. This is subject to constraints relating to the vehicle and tires as well as the energy consumed, which is the basis for this paper. We work with a real random distribution of consumed energy values following a normal Gaussian distribution in order to analyze its influence on the trajectories obtained by the vehicle. The energy consumed, the time taken, the maximum velocity reached, and the distance traveled are analyzed in order to characterize the properties of the trajectories obtained. The proposed algorithm has been applied to 101 examples, showing that the computational times needed to obtain the solutions are always lower than those required to realize the trajectories. The results obtained allow us to reach conclusions about the energy efficiency of the trajectories.

scholarly journals Simulation of processes of electric power consumption for traction in conditions of changing the traffic schedule of freight trains at the electrified sections

2018 ◽  
Vol 239 ◽  
pp. 01034
Author(s):  
Vladislav Nezevak ◽  
Elena Sidorova ◽  
Yury Demin
Keyword(s):  
Energy Efficiency ◽  
Electric Power ◽  
Simulation Modeling ◽  
Network Models ◽  
Rolling Stock ◽  
Neural Network Models ◽  
Electric Rolling Stock ◽  
Traction Power Supply System ◽  
Traction Power Supply ◽  
Comparison Of The Results

The paper is devoted to the solution of the problem of increasing the energy efficiency of the transportation process on the electrified sections of the railways. The task is considered in the aspect of energy efficiency when comparing forecasted traffic schedules with each other and assessing the effectiveness of implementing the forecasted and executed schedule of train traffic at the section. The basis for the calculations is a simulation modeling of the interaction between the electric rolling stock and the traction power supply system at the sections with different track profiles. Simulation modeling was carried out for the conditions of changing the traffic schedule of freight trains and maintaining the amount of traffic and the amount of work unchanged. The results of the change in the amount of electric power for traction and the level of unbalance of energy for existing sections of constant and alternating current are used as the basis for construction of approximating models, in the function of which regression and neural network models are used. Comparison of the results of approximation of the considered models for the estimation of changes in amount of electric power for traction and unbalance is made. Models with the best results of approximation to simulation results are determined.

scholarly journals Performance evaluation of NB-IoT in-band deployment mode in suburban area

2021 ◽  
Vol 23 (2) ◽  
pp. 855
Author(s):  
Karina Turzhanova ◽  
Sergey Konshin ◽  
Valery Tikhvinskiy ◽  
Alexandr Solochshenko
Keyword(s):  
Simulation Modeling ◽  
Experimental Testing ◽  
Mobile Network ◽  
Network Capacity ◽  
Suburban Area ◽  
Case Scenario ◽  
Local Conditions ◽  
Testing Methodology ◽  
Study Results ◽  
Comparison Of The Results

There given to discuss the study results about one of three deployment scenarios performance (in-band deployment mode) of the narrow-band internet of things (NB-IoT) technology. The study is carrying out with help of simulation modeling and experimental testing of the main network parameters, namely: radio coverage, network capacity, user experience, and their dependencies on each other. Comparison of the results of a physical experiment and simulation modeling shows their high convergence and confirms the adequacy of the applied testing methodology. As a case scenario provided an example of NB-IoT implementation on a 4G mobile network in the 800 MHz band, in a suburban area for remote metering applications. The article presents the applying testing methodology of NB-IoT that adapted to the local conditions of radio network planning. Based on the obtained data, adducing the main conclusions about the feasibility of using an in-band scenario for deploying NB-IoT on a 4G network in a suburban environment.

A Sequential Algorithm for Possibility-Based Design Optimization

2007 ◽  
Vol 130 (1) ◽  
Author(s):  
Jun Zhou ◽  
Zissimos P. Mourelatos
Keyword(s):  
Design Optimization ◽  
Optimization Algorithm ◽  
Computational Cost ◽  
Possibility Theory ◽  
Sequential Optimization ◽  
Sequential Algorithm ◽  
Computationally Efficient ◽  
Worst Case ◽  
Reliability Based Design ◽  
Design Variables

Deterministic optimal designs that are obtained without taking into account uncertainty/variation are usually unreliable. Although reliability-based design optimization accounts for variation, it assumes that statistical information is available in the form of fully defined probabilistic distributions. This is not true for a variety of engineering problems where uncertainty is usually given in terms of interval ranges. In this case, interval analysis or possibility theory can be used instead of probability theory. This paper shows how possibility theory can be used in design and presents a computationally efficient sequential optimization algorithm. After the fundamentals of possibility theory and fuzzy measures are described, a double-loop, possibility-based design optimization algorithm is presented where all design constraints are expressed possibilistically. The algorithm handles problems with only uncertain or a combination of random and uncertain design variables and parameters. In order to reduce the high computational cost, a sequential algorithm for possibility-based design optimization is presented. It consists of a sequence of cycles composed of a deterministic design optimization followed by a set of worst-case reliability evaluation loops. Two examples demonstrate the accuracy and efficiency of the proposed sequential algorithm.

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