Multi-UAV coordination control by chaotic grey wolf optimization based distributed MPC with event-triggered strategy

The paper proposes a new swarm intelligence-based distributed Model Predictive Control (MPC) approach for coordination control of multiple Unmanned Aerial Vehicles (UAVs). First, a distributed MPC framework is designed and each member only shares the information with neighbors. The Chaotic Grey Wolf Optimization (CGWO) method is developed on the basis of chaotic initialization and chaotic search to solve the local Finite Horizon Optimal Control Problem (FHOCP). Then, the distributed cost function is designed and integrated into each FHOCP to achieve multi-UAV formation control and trajectory tracking with no-fly zone constraint. Further, an event-triggered strategy is proposed to reduce the computational burden for the distributed MPC approach, which considers the predicted state errors and the convergence of cost function. Simulation results show that the CGWO-based distributed MPC approach is more computationally efficient to achieve multi-UAV coordination control than traditional method.     

Virtual target guidance-based distributed model predictive control for formation control of multiple UAVs

The paper proposes a Virtual Target Guidance (VTG)-based distributed Model Predictive Control (MPC) scheme for formation control of multiple Unmanned Aerial Vehicles (UAVs). First, a framework of distributed MPC scheme is designed in which each UAV only shares the information with its neighbors, and the obtained local Finite-Horizon Optimal Control Problem (FHOCP) can be solved by swarm intelligent optimization algorithm. Then, a VTG approach is developed and integrated into the distributed MPC scheme to achieve trajectory tracking and obstacle avoidance. Further, an event-triggered mechanism is proposed to reduce the computational burden for UAV formation control, which takes into consideration the predictive state errors as well as the convergence of cost function. Numerical simulations show that the proposed VTG-based distributed MPC scheme is more computationally efficient to achieve formation control of multiple UAVs in comparison with the traditional distributed MPC method.     

Interaction mechanisms of shock waves with the boundary layer and wakes in a highly-loaded NGV using hybrid RANS/LES

Accurate predictions of Shock Waves and Boundary Layer Interaction (SWBLI) and strong Shock Waves and Wake Vortices Interaction (SWWVI) in a highly-loaded turbine propose challenges to the currently widely used Reynolds-Averaged Navier-Stokes (RANS) model. In this work, the SWBLI and the SWWVI in a highly-loaded Nozzle Guide Vane (NGV) are studied using a hybrid RANS/LES strategy. The Turbulence Kinetic Energy (TKE) budget and the Proper Orthogonal Decomposition (POD) method are used to analyze flow mechanisms. Results show that this hybrid RANS/LES method can obtain detailed flow structures for flow mechanisms analysis. Strong shock waves induce boundary layer separation, while the presence of a separation bubble can in turn lead to a Mach reflection phenomenon. The shock waves cause trailing-edge vortices to break clearly, and the wakes, in turn, can change the shocks intensity and direction. Furthermore, the Entropy Generation Rate (EGR) is used to analyze the irreversible loss. It turns out that the SWWVI can reduce the flow field loss. There are several weak shock waves in the NGV flow field, which can increase the irreversible loss. This work offers flow mechanisms analysis and presents the EGR distribution in SWBLI and SWWVI areas in a transonic turbine blade.     

ATC3000航空地图制作软件及其关键技术分析

针对ATC3000空管自动化系统的运行要求以及飞行管制区现场实际工作的需要,介绍了ATC3000航空地图制作软件的关键技术。文中分析了该软件的结构以及在Windows系统中使用Delphi开发的具体实现技术。     

Application of novel force control strategies to enhance robotic abrasive belt grinding quality of aero-engine blades

Robotic belt grinding has emerged as a finishing process in recent years for machining components with high surface finish and flexibility.The surface machining consistency, however,is difficult to be guaranteed in such a process.To overcome this problem, a method of hybrid force-position control combined with PI/PD control is proposed to be applied in robotic abrasive belt grinding of complex geometries.Voltage signals are firstly obtained and transformed to force information with signal conditioning methods.Secondly, zero drift and gravity compensation algorithms are presented to calibrate the F/T transducer which is installed on the robot end-effector.Next, a force control strategy combining hybrid force-position control with PI/PD control is introduced to be employed in robotic abrasive belt grinding operations where the force control law is applied to the Z direction of the tool frame and the positon control law is used in the X direction of the tool frame.Then, the accuracy of the F/T transducer and the robotic force control system is analyzed to ensure the stability and reliability of force control in the robotic grinding process.Finally, two typical cases on robotic belt grinding of a test workpiece and an aero-engine blade are conducted to validate the practicality and effectiveness of the force control technology proposed.     

Optimal mission planning of the reconfiguration process of satellite constellations through orbital maneuvers: A novel technical framework

In this paper, a general new methodology is presented for the orbital reconfiguration of satellite constellations on the basis of Lambert targeting theorem. In view of the cost and risk reduction, it is very important to consider the problem of satellite constellation reconfiguration with the two constraints of overall mission cost minimization and the desired final configuration. Hence, the dependent non-simultaneous deployment approach is proposed to minimize overall fuel cost. Despite the fact that the satellites deploy in a non-simultaneous manner, supplementary phasing maneuvers on the target orbital pattern to achieve the desired orbital configuration are avoided. Moreover, a novel idea is presented to optimize the flight of satellites, which plays an important role in complying with the constraint of overall fuel cost minimization as much as possible. In order to achieve the global optimal solution of the satellite constellation reconfiguration problem, the efficient hybrid Particle Swarm Optimization/Genetic Algorithm (PSO/GA) technique, is implemented. Finally, to indicate the superiority of the presented method, a comparison to the simultaneous maneuver viewpoint is made on a number of representative cases. The obtained results imply significant reduction of reconfiguration costs by employing the proposed method.     

Robust control for an unmanned helicopter with constrained flapping dynamics

In this paper, a neural network based adaptive prescribed performance control scheme is proposed for the altitude and attitude tracking system of the unmanned helicopter in the presence of state and output constraints. For handling the state constraints, the barrier Lyapunov function and the saturation function are employed. And, the prescribed performance method is used to deal with the flapping angle constraints for the unmanned helicopter. It is proved that the proposed control approach can ensure that all the signals of the resulting closed-loop system are bounded, and the tracking errors are within the prescribed performance bounds for all time. The numerical simulation is given to illustrate the performance of the proposed scheme.     

Period selection for integrated controller tasks in cyber-physical systems

Performance optimization of cyber-physical systems(CPS)calls for co-design strategies that handle the issues in both computing domain and physical domain.Periods of controller tasks integrated into a uniprocessor system are related to both control performance and real-time schedulability analysis simultaneously.System performance improvement can be achieved by optimizing the periods of controller tasks.This paper extends an existing model to select task periods in real-time for CPS with fixed priority controller tasks scheduled by rate-monotonic algorithm.When all the tasks can be integrated,the analytic solution of the problem is derived by using the method of Lagrange multipliers and gradient descent method is evaluated to be suitable online.To further deal with the condition that the system is overloaded,an integrated method is proposed to select periods of tasks online by selecting a subset of tasks first and then optimizing the periods for them.Experimental results demonstrate that our method yields near-optimal result with a short running time.     

智能化交流磁化电流控制器设计中的若干问题

本文对设计智能化交流磁化电流控制器过程中所必须解决的非正弦交流磁化电流的测量、退磁速率的线性化等问题进行了讨论，详细分析了磁化回路中电流与触发角及负载功率因数角之间的关系，并在此基础上提出相应的解决方案，同时叙述了以单片机技术为核心的交流磁化电流控制器的组成及工作原理。对进一步提高我国磁粉探伤设备的技术水平具有一定的促进意义。