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This paper studies the problem of multiple fixed-wing UAVs coordination Standoff tracking of target, and proposes a dual-virtual structure UAV formation Standoff tracking method. Firstly, a dual-virtual structure is designed to solve the problem of formation trajectory guidance and formation control in target tracking by designing the functions and algorithms of two virtual UAVs. Secondly, we propose that motion parameter group to represent the process of UAV formation tracking target, and the phase coordination problem between UAVs is converted into the setting of phase factor in the parameter group, which simplifies the complexity of the algorithm design. Then the formation tracking control law is given based on the consistency algorithm and the stability of the system is proved. Finally, the situation that UAV formation tracking a maneuvering target is simulated and the simulation results verify the validity of the algorithm.

AlGaN/GaN lateral Schottky barrier diodes (SBDs) with three different anode geometries (stripe, circular, and the conventional plane one) and different rows of anode trenches are fabricated and electrically characterized to study the influence of anode trench geometries. The SBDs with anode trenches exhibit the lower on-state resistance (RON) than that with the conventional plane one. It can be explained that the anode trenches made the Schottky metal directly contact to the 2DEG at the sidewall of the AlGaN/GaN interface, removing the AlGaN barrier layer in the conventional plane anode. In addition, the RON of the SBDs with circular trenches is smaller than that of the SBDs with stripe ones. Furthermore, the RON decreases with the increasing rows of anode trenches, which can be attributed to the increased contact area between the Schottky metal and the 2DEG. For the reverse characteristics, the anode trenches do not lead to performance degradation. The fabricated devices exhibit the low reverse current (IR, IR﹤1 &mu, A/mm), and the breakdown voltage (VBK) remains unchanged with different anode geometries.

With the flight environment becoming more and more complex, how to avoid the moving threat for the UAV under the dynamic environment and complete the mission become a key problem. With the idea of guidance, using the method of dimension reduction, the dynamic guidance obstacle avoidance method in three dimensional spaces is given. Considering the collision avoidance completion time and the UAV’s maneuverability, the parameters range of obstacle avoidance navigation law are deduced. Simulation results show the validity of the algorithm.

With the extensive use of UAV, how to make the UAV avoid the obstacle and arrive at the destination has become a hot issue. To make the angle shift minimum, a method on dynamic guidance obstacle avoidance of UAV based on the minimum angle shift is proposed, considering the constraints such as the completion time of obstacle, the motor performance, the direction of velocity after obstacle avoidance and so on, determining the range of guidance parameters. In the meanwhile, the obstacle method is extended to 3D-space based on 2D. Moreover, numerical simulations are carried out to verify the effectiveness of the method.

For the complex combat environment, considering the flyable performance constrains and the safety constrains, an online trajectory planning algorithm of UAVs(Unmanned Aerial Vehicles) based on Pythagorean Hodograph (PH) curve is put forward, which is easy to traced. When the unexpected obstacles are detected, based on the velocity obstacles avoidance method, the collision avoidance trajectory is planned online. The position of the interrupt point and the direction of the UAV turn are calculated. To fully use the PH trajectories performance that the curvature of the curve is continuous and precisely known, the location and crossing heading error equations were established within the Serret-Frenet coordinates. The corresponding asymptotically stable convergence backstepping trajectory tracking control law was designed based on the error formulations. The autonomous collision avoidance trajectory simulation result and its tracking control result show that the proposed trajectory generation method and the corresponding adaptive tracking control method are effective and can improve the tracking accuracy.

For the demand of the UAV autonomous path planning in dynamic thread environment, the three-dimensional path planning algorithm on-line of UAV based on Pythagorean Hodograph (PH) curve is put forward. According to the UAV’s current flight state such as location and speed, and the interrupt point or the target’s state, a flyable path with continuous curvature is planed out online. The roles of the key parameters are analyzed and the range of the values are given. On this basis, the distribution estimation algorithm is used to optimize the selection of path parameters, which avoid the blindness iterative process and consider the kinematics constraints such as the curvature, torsion and climbing angle. The multiple UAVs’ three dimensional path planning in dynamic environment are tested. Simulation results prove the validity and practicability of the algorithm.

Focusing on obstacle avoidance in three-dimensional space for unmanned aerial vehicle (UAV), the direct obstacle avoidance method in dynamic space based on three-dimensional velocity obstacle spherical cap is proposed, which quantifies the influence of threatening obstacles through velocity obstacle spherical cap parameters. In addition, the obstacle avoidance schemes of any point on the critical curve during the multi-obstacles avoidance are given. Through prediction, the insertion point for the obstacle avoidance can be obtained and the flight path can be re-planned. Taking the Pythagorean Hodograph (PH) curve trajectory re-planning as an example, the three-dimensional direct obstacle avoidance method in dynamic space is tested. Simulation results show that the proposed method can realize the online obstacle avoidance trajectory re-planning, which increases the flexibility of obstacle avoidance greatly.

One isolate of Brachiomonas submarina was tested for its ability to grow heterotrophicly on 5 different organic compounds. Sodium acetate and glucose were found to be effective in supporting the growth. Sodium acetate was chosen as the organic nutrient to test the combined effects of organic and inorganic solutions on the growth and fatty acid composition of Brachiomonas submarina. The best growth rates were achieved at 3 mmol L−1 CH3COONa and 0.88 mmol L−1 NaNO3 in heterotrophic condition, and 4 mmol L−1 CH3COONa and 3.52 mmol L−1 NaNO3 in mixotrophic condition. The differences between fatty acid contents were significant. The total polyunsaturated fatty acids (T. P. U. F. As) varied from 55.79% to 67.72% in heteritrophic growth and from 52.39% to 65.55% in mixotrophic growth. It is concluded that CH3COONa and NaNO3 at 3 mmol L−1 and 3.52 mmol L−1 should respectively be used in order to achieve the highest growth rate and fatty acid content.

An online UAV collision avoidance trajectory planning algorithm based on Pythagorean Hodograph (PH) curve is presented. To fully use the PH trajectories performance that the curvature of the curve is continuous and precisely known, the backstepping trajectory tracking control is introduced. The location and crossing heading equations were established within the Serret-Frenet coordinates. The asymptotically stable convergence crossing heading law was designed based on the error formulations. The flight experimental results show that the proposed adaptive tracking control method are effective.

A new algorithm based on probability collectives is proposed to solve the target assignment of multiple unmanned aerial vehicles (UAVs) to coordinated attack multi-target without centric control, while keeping the probability equilibrium of every UAV weapons. The estimation of distribution algorithms is used to solving the Multiple UAVs target assignment, which is proper to solve the discrete combination optimization. Simulation results show the accuracy of the optimization model for target assignment. Compared with conventional methods, the proposed method is able to converge to the global optimum with more stability, scalability and faster convergence rate.

The platform of "Transportation Economic GIS of Civil Aviation" is sub-product of civil aviation execution operation management and GIS technology. It can manage and visually analyze the information and data of air-transportation resources about distribution of cities, airlines, airports, ability of transportation, and other air-lines based on geography range [1].

To complete the control of exoskeleton carrying robot perfectly, the human-machine interaction forces model should be identified, which can be simulated using spring-damper model, that is, the coefficient elasticity and damping should be gotten. For the coupling of the several joints, the parameters should be optimized from the system global performance. In this paper, genetic algorithm is used to identification interaction parameters. Pseudo-gradient is introduced and the individual pseudo-gradient justification is used in genetic algorithm. Annealing selection according to the fitness is given to keep the population diversity, and the memory mechanism is added to speed up evolution. Combing the characteristics of the lower extremity carrying robot walking, the detail human-machine interaction forces identification method using the improved genetic algorithm is given and the quasi-Newton iterative learning control simulation results show the validity of the method.

Lower extremity exoskeleton intelligent carrying system is a new concept human-machine intelligent robot system. To provide a virtual experiment platform for the system, virtual prototyping technique is used to build up a human-machine carrying exoskeleton system, which is benefit to study the kinematics and dynamics characteristics, speed up the development of prototype. The dynamic model of exoskeleton for the integral movement is established, and the virtual joint nonlinear adaptive torque control is provided to complete the walking experiment. Simulation results show the validity of this the virtual platform and the control method.

In this paper, the quasi-Newton method is presented and the improved quasi-Newton method based on feedback is provided, which can be used in strongly coupled nonlinear time-variable system and improve the control speed and precision. Combining the carrying robot, the application of the improved quasi-Newton method is given and the simulation results show the validity of the method.