scholarly journals Research on UAV Route Optimization Method Based on Double Target of Confidence and Ambiguity

2021 ◽  
Vol 15 ◽  
Author(s):  
Huijuan Zhang
Keyword(s):  
Flight Control ◽  
Control Method ◽  
Optimization Method ◽  
Route Optimization ◽  
Computing Power ◽  
Human Control ◽  
Ground Station ◽  
Calculation Results ◽  
Planning Decision ◽  
And Control

In recent years, with the continuous development of drone technology, UAVs are used as unmanned and flightable devices, UAV plays an important role in remote sensing and GIS disciplines. During the flight, no one directly participates in flight-related decisions such as flight routes, path planning, and flight control. In this case, it is necessary to use the computing power of the onboard computer of the UAV system, the computing power of the ground station computer, and related technologies such as detecting sensing, image vision, real-time wireless communication, etc., to develop target planning, decision-making and control algorithms for specific problems, and to solve the problem. Flight planning and flight control issues in machine applications. The UAV route optimization method based on the double target of confidence and ambiguity has positive significance for route optimization and wide application of UAV. In this context, this paper aims to analyze and study the UAV route optimization method based on the two goals of confidence and ambiguity, and optimized the method of drone route. The calculation results show that, compared with other methods, this method can make the UAV not rely on human control, but realize the use of fuzzy control method to identify the target and track the moving target.

Aeroelastic Vehicle Sensor Placement for Feedback Control Applications Using Gain Stability

2000 ◽  
Author(s):  
Abdul G. Al-Shehabi ◽  
Brett Newman
Keyword(s):  
Flight Control ◽  
Optimization Method ◽  
Stability Criteria ◽  
Control Loop ◽  
Aircraft Structure ◽  
Design Constraints ◽  
Optimal Approach ◽  
And Control ◽  
Vehicle Sensor ◽  
Structural Mode

Abstract Optimal positions for aeroelastic vehicle feedback sensors, which meet design constraints and control requirements, are difficult to determine. This paper introduces a systematic and optimal approach for choosing sensor locations based on gain stability criteria. A steepest descent optimization method with constraints is used to minimize such objective criteria, which are based on the dipole magnitudes for each aeroelastic mode appearing in a traditional Evans diagram for a scalar control loop. Each dipole magnitude term is multiplied by a weight parameter. Rigid-body augmentation characteristics are implicitly accounted for in the type of input-output pairs utilized and in predefined loop compensation structure. Constraints enforcing minimum phase zeros in the transfer function are also considered. A flexible aircraft structure is used as an example to demonstrate this procedure. Results indicate flight control and structural mode control characteristics can be effectively balanced.

scholarly journals Analysis, Design, and Control of an Omnidirectional Mobile Robot in Rough Terrain

2009 ◽  
Vol 131 (12) ◽  
Author(s):  
Martin Udengaard ◽  
Karl Iagnemma
Keyword(s):  
Mobile Robot ◽  
Control Method ◽  
Optimization Method ◽  
Contact Angles ◽  
Design Guidelines ◽  
Rough Terrain ◽  
Uneven Terrain ◽  
Omnidirectional Mobile Robot ◽  
Subsystem Design ◽  
And Control

An omnidirectional mobile robot is able, kinematically, to move in any direction regardless of current pose. To date, nearly all designs and analyses of omnidirectional mobile robots have considered the case of motion on flat, smooth terrain. In this paper, an investigation of the design and control of an omnidirectional mobile robot for use in rough terrain is presented. Kinematic and geometric properties of the active split offset caster drive mechanism are investigated along with system and subsystem design guidelines. An optimization method is implemented to explore the design space. The use of this method results in a robot that has higher mobility than a robot designed using engineering judgment. A simple kinematic controller that considers the effects of terrain unevenness via an estimate of the wheel-terrain contact angles is also presented. It is shown in simulation that under the proposed control method, near-omnidirectional tracking performance is possible even in rough, uneven terrain.

An Improved Nonlinear Flight Controller Design Using Active Disturbances Rejection Control Method

2013 ◽  
Vol 380-384 ◽  
pp. 332-336
Author(s):  
Zhan Qi Fan ◽  
Lin Liu ◽  
Xun Sun
Keyword(s):  
Neural Network ◽  
Flight Control ◽  
Particle Swarm Optimization Algorithm ◽  
Control Method ◽  
Controller Design ◽  
Wavelet Neural Network ◽  
Control Performance ◽  
Swarm Optimization ◽  
Excellent Control ◽  
And Control

An improved large envelope nonlinear flight control method using active disturbances rejection control (ADRC) method and wavelet neural network is approved in this paper. Wavelet neural network is used to realize the inversion of the 6-DOF nonlinear airplane model. The wavelet neural network is optimized using simulated annealing particle swarm optimization algorithm to improve the approach precision. In order to improve the robustness and control performance in all disturbances, ADRC is used to realize the high precision flight control. The simulation results show that the large envelope flight controller has excellent control performance.

Parking Motion Planning and Control of a Car-Like Robot Using a Fuzzy Neural Network

1995 ◽  
Vol 7 (1) ◽  
pp. 52-56 ◽  
Author(s):  
Motoji Yamamoto ◽  
◽  
Masaaki Kobayashi ◽  
Akira Mohri
Keyword(s):  
Neural Network ◽  
Motion Planning ◽  
Fuzzy Neural Network ◽  
Control Method ◽  
Difficult Problem ◽  
Human Control ◽  
Planning And Control ◽  
Fuzzy Neural ◽  
Neural Network System ◽  
And Control

This paper discusses a parking motion planning and control of a car-like robot. Because of non-holonomic constraints of the system, motion planning and control is regarded as a difficult problem. In this paper, constraints of steering operation and obstacle avoidance with garage and walls are also considered. As one approach to this problem, extracting human control strategy can be considered, because many drivers can easily park their cars in garages. This paper proposes a motion planning and control method using a fuzzy neural network (FNN). The fuzzy neural network system for parking motion planning learns good parking motions by human operations to generate motion strategy of parking. The fuzzy neural network is then used for parking motion planning in a restricted area surrounded by walls. Computer simulation demonstrates the effectiveness of the planning method. Furthermore, the method can be considered as a feedback control law for the parking of car-like robot. Therefore, an experiment of parking motion control using the fuzzy neural network is also tested.

scholarly journals Dynamic modeling and control method of a new concept wing-disk aircraft

2018 ◽  
Vol 189 ◽  
pp. 03015
Author(s):  
Da Hong ◽  
Jihong Zhu
Keyword(s):  
Flight Control ◽  
Control Method ◽  
Poor Performance ◽  
Previous Method ◽  
Modeling And Control ◽  
Inverse Control ◽  
Wing Disk ◽  
Integral Element ◽  
Dynamic Inverse ◽  
And Control

The research aimed at a new layout wing-disk solar aircraft concept with several wings around the disc fuselage, select coordinates and variables adaptively for the new dynamic subject, and establish dynamic model, using blade element momentum theory and CFD value for correction. Design the flight control strategy and controller constraint relations, put forward the method of control allocation and manipulation, and use nonlinear dynamic inversion control method aimed at the transverse and longitudinal coupling, serious nonlinear characteristics, and adds integral element as a robust dynamic inverse control to deal with the poor performance of previous method, and simulate to validate the control design.

scholarly journals Online prediction and control method for compensation regulation value in grinding processes

2019 ◽  
Vol 11 (3) ◽  
pp. 168781401983710
Author(s):  
Peng Zheng ◽  
Dong-liang Liu ◽  
Xue-hao Tian ◽  
Zhan-xin Zhi ◽  
Lin-na Zhang
Keyword(s):  
Prediction Model ◽  
Control Method ◽  
Prediction Method ◽  
Feedback System ◽  
Optimization Method ◽  
Support Vector ◽  
Machining Accuracy ◽  
Grinding Process ◽  
Compensation Control ◽  
And Control

In any grinding process, compensation regulation value is a crucial factor for maintaining precision during the batch processing of workpieces. Geometric characteristics, buffing allowance, temperature, wheel speed, and workpiece speed are the main factors that affect compensation regulation value in any grinding process. In this article, a novel prediction method for compensation regulation value is proposed based on incremental support vector machine and mixed kernel function. The support vectors for the prediction model are extracted using the convex hull vertex optimization algorithm, and the speed of the operation can be increased effectively. In addition, the parameters of the model are optimized using cross-validation optimization method to improve the accuracy of the prediction model. Then, the feedback control strategy of compensation regulation value for the grinding process is also proposed. Single-factor and multi-factor experiments are implemented respectively using the proposed method. The results verify the feasibility and effectiveness of the proposed method. It is also noted that the machining accuracy is improved significantly in comparison with the machining without prediction and compensation control. Moreover, by applying the prediction compensation control of compensation regulation value to the active measurement and control of the grinding process, a feedback system is formed, and then the intelligentization of the grinding system can be realized.

A Novel Optimization and Control Method for Signalized Traffic Network

2011 ◽  
Vol 403-408 ◽  
pp. 3229-3234
Author(s):  
Xiao Feng Chen ◽  
Zhong Ke Shi
Keyword(s):  
Dynamic Optimization ◽  
Control Method ◽  
Control Period ◽  
Optimization Method ◽  
Dynamic Traffic ◽  
Arterial Network ◽  
Real Coded Genetic Algorithm ◽  
Optimization And Control ◽  
Multi Phase ◽  
And Control

For the dynamic optimization and control problem of the signalized arterial network in urban, a dynamic traffic flow model based on multi-phase control is firstly formulated, in which the total number of the retained vehicles through the arterial during the control period is adopted as the optimization objective and the green times and offsets as the control variables. Then a hybrid optimization method based on real-coded genetic algorithm and local search technique is designed to solve the optimization problem. For examining the validity of the optimization and control method proposed, it is applied to a case study with dynamic traffic demands and a large number of simulations show that the dynamic optimization and control method proposed in this paper can work well for the signalized arterial network.

Aircraft Controller Flight Control System Design

2014 ◽  
Vol 602-605 ◽  
pp. 1291-1294
Author(s):  
Hong Cheng Zhou ◽  
Dao Bao Wang
Keyword(s):  
Control System ◽  
Flight Control ◽  
Control Method ◽  
Sliding Mode ◽  
Variable Structure ◽  
Control Law ◽  
Low Velocity ◽  
Structure Control ◽  
Sliding Mode Variable Structure ◽  
And Control

The servo control methods of motion configuration are researched. Based on analysis for characteristic of the motion configuration, the control strategy and control law used on the motion control system are presented. The controllers are respectively designed by frequency correcting method and normal control method which belongs to classical control theory. Sliding mode variable structure control method is presented for location control law designing, so that the problem of location control loop low velocity creeping is solved, and a simulating experimentation demonstrate the effectiveness of the proposed approach.

Perencanaan Pengendalian Kualitas Produk Pakaian Bayi dengan Metode Six Sigma Pada CV. AGP

JEMAP ◽  
2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Albertus Reynaldo Kurniawan ◽  
Bayu Prestianto
Keyword(s):  
Quality Control ◽  
Continuous Improvement ◽  
Six Sigma ◽  
Screen Printing ◽  
Control Method ◽  
Operational Performance ◽  
Machine Maintenance ◽  
Quality Product ◽  
Break Time ◽  
And Control

Quality control becomes an important key for companies in suppressing the number of defective produced products. Six Sigma is a quality control method that aims to minimize defective products to the lowest point or achieve operational performance with a sigma value of 6 with only yielding 3.4 defective products of 1 million product. Stages of Six Sigma method starts from the DMAIC (Define, Measure, Analyze, Improve and Control) stages that help the company in improving quality and continuous improvement. Based on the results of research on baby clothes products, data in March 2018 the percentage of defective products produced reached 1.4% exceeding 1% tolerance limit, with a Sigma value of 4.14 meaning a possible defect product of 4033.39 opportunities per million products. In the pareto diagram there were 5 types of CTQ (Critical to Quality) such as oblique obras, blobor screen printing, there is a fabric / head cloth code on the final product, hollow fabric / thin fabric fiber, and dirty cloth. The factors caused quality problems such as Manpower, Materials, Environtment, and Machine. Suggestion for consideration of company improvement was continuous improvement on every existing quality problem like in Manpower factor namely improving comprehension, awareness of employees in producing quality product and improve employee's accuracy, Strength Quality Control and give break time. Materials by making the method of cutting the fabric head, the Machine by scheduling machine maintenance and the provision of needle containers at each employees desk sewing and better environtment by installing exhaust fan and renovating the production room.

An Efficient Approach for Modeling and Control of a Quadrotor

2016 ◽  
Vol 4 (2) ◽  
pp. 1-16
Author(s):  
Ahmed S. Khusheef
Keyword(s):  
Pid Control ◽  
Control Method ◽  
Mechanical Design ◽  
Loop Control ◽  
Modeling And Control ◽  
Loop Control System ◽  
And Control ◽  
Close Loop Control ◽  
Close Loop Control System ◽  
Made In

 A quadrotor is a four-rotor aircraft capable of vertical take-off and landing, hovering, forward flight, and having great maneuverability. Its platform can be made in a small size make it convenient for indoor applications as well as for outdoor uses. In model there are four input forces that are essentially the thrust provided by each propeller attached to each motor with a fixed angle. The quadrotor is basically considered an unstable system because of the aerodynamic effects; consequently, a close-loop control system is required to achieve stability and autonomy. Such system must enable the quadrotor to reach the desired attitude as fast as possible without any steady state error. In this paper, an optimal controller is designed based on a Proportional Integral Derivative (PID) control method to obtain stability in flying the quadrotor. The dynamic model of this vehicle will be also explained by using Euler-Newton method. The mechanical design was performed along with the design of the controlling algorithm. Matlab Simulink was used to test and analyze the performance of the proposed control strategy. The experimental results on the quadrotor demonstrated the effectiveness of the methodology used.

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