Research on Man-Machine Function Allocation of Tank Fire Control System

2012 ◽  
Vol 580 ◽  
pp. 160-164
Author(s):  
Tian Qing Chang ◽  
Dong Chen ◽  
Jun Wei Chen
Keyword(s):  
Control System ◽  
System Design ◽  
Engineering Application ◽  
Current Method ◽  
Control System Design ◽  
Fire Control ◽  
Working Mechanism ◽  
Level Of Automation ◽  
Function Allocation ◽  
New Type

Man-machine function allocation is an important step in new type tank fire control system design. Aiming at the problem of engineering application abilities deficiency in current method, a flow of function allocation is proposed. System working mechanism, functions and tasks are analyzed to define the level of automation and guide preliminary design. AHP is adopted to seek out the optimal plan. The method can offer new theory reference for intelligent tank fire control system design.

Based on Analysis of Fast Simulation Algorithm for Multi-Objective BVR Attacking Fire Control System

2014 ◽  
Vol 898 ◽  
pp. 900-903
Author(s):  
Yi Guo Ji ◽  
Zhong Xiang Tao ◽  
Cui Chen ◽  
Zhi Huan Lan ◽  
Chun Yan Tian
Keyword(s):  
Control System ◽  
System Design ◽  
Continuous Improvement ◽  
Control System Design ◽  
Simulation Algorithm ◽  
Fast Simulation ◽  
Fire Control ◽  
Multi Objective ◽  
Combat Aircraft ◽  
Simulation Results

With the continuous improvement of fire control system functions to further improve the performance of missile weapons, combat aircraft requires BVR combat capability, multi-objective BVRAC will be the next major form of combat and trends. This article will fast simulation algorithm is applied to multi-target attack fire control system design, we propose a multi-target attack BVR fire control system design. Simulation results show that: the design of high precision, calculation speed, fully meet the requirements of real-time speed and airborne weapons systems.

scholarly journals Multiobjective Optimal Control of Wind Turbines: A Survey on Methods and Recommendations for the Implementation

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 567
Author(s):  
Adrian Gambier
Keyword(s):  
Control System ◽  
Power Systems ◽  
System Design ◽  
Wind Turbines ◽  
Systems Engineering ◽  
Engineering Application ◽  
Current Control ◽  
Optimization Techniques ◽  
Control System Design ◽  
Large Wind

advanced control system design for large wind turbines is becoming increasingly complex, and high-level optimization techniques are receiving particular attention as an instrument to fulfil this significant degree of design requirements. Multiobjective optimal (MOO) control, in particular, is today a popular methodology for achieving a control system that conciliates multiple design objectives that may typically be incompatible. Multiobjective optimization was a matter of theoretical study for a long time, particularly in the areas of game theory and operations research. Nevertheless, the discipline experienced remarkable progress and multiple advances over the last two decades. Thus, many high-complexity optimization algorithms are currently accessible to address current control problems in systems engineering. On the other hand, utilizing such methods is not straightforward and requires a long period of trying and searching for, among other aspects, start parameters, adequate objective functions, and the best optimization algorithm for the problem. Hence, the primary intention of this work is to investigate old and new MOO methods from the application perspective for the purpose of control system design, offering practical experience, some open topics, and design hints. A very challenging problem in the system engineering application of power systems is to dominate the dynamic behavior of very large wind turbines. For this reason, it is used as a numeric case study to complete the presentation of the paper.

Sign in / Sign up

Export Citation Format

Share Document