The paper aims to study the problem of obstacle avoidance in air?ground cooperative tracking control for the unmanned aerial helicopter (UAH),in which a new approach of designing the path obstacle avoidance plan and controller design is proposed.Initially, as for the uncertain linear UAH,by processing and judging two?dimensional environmental information within the warning range for the UAH,an obstacle avoidance strategy is proposed with the help of wall?following algorithm,and the flight angle of obstacle avoidance path and the tracking speed that can make up for bypass distance are calculated.Secondly,the proposed obstacle avoidance method is extended to the three?dimensional case,and the flight angle of the UAH is determined based on the obstacle information in the horizontal and vertical directions,which can reduce the bypass distance caused by the obstacle avoidance link as possible.Thirdly,based on two derived obstacle avoidance algorithms above,the artificial neural network (ANN) is introduced to estimate model uncertainty,and then the tracking control design schemes are established by using feedforward compensation and optimal control technologies.some simulations demonstrate the effectiveness of the proposed obstacle avoidance strategy and control algorithm.

In this work, the inner and outer loop control strategy is adopted for the unmanned aerial vehicles (UAVs) formation system. Firstly, a sliding mode control method based on memory event?triggered mechanism (METM) is proposed for the position subsystem under delay and disturbance. The second?order model is established for each UAV, and the leader?follower framework is adopted to realize the desired flight formation. Secondly, an adaptive METM is proposed to alleviate the transmission burden, in which control input feedback is introduced. For the resulting communication delay of the control input in the proposed METM and the external disturbance to the system, a sliding mode controller is designed, which maintains desirable control performance and solves the influence of communication delay and bounded disturbance to a certain extent. Thirdly, the stability of the closed?loop system is proved by applying Lyapunov theory and H_∞ control theory, and a method that facilitates solving controller gain and triggering parameter through a series of linear matrix inequalities (LMIs) is proposed. Moreover, based on the obtained virtual control quantity, a tracking controller is designed for the attitude subsystem. Finally, a simulated example is exploited to verify the effectiveness of the proposed method.

Adopt solvent refining and chemical caustic washing method to enrich and extract phenolic compounds from Fushun shale oil, then analyzed and identified with gas chromatographymass spectrometry (GC-MS). Fushun shale oil is extracted with N, N-dimethyl formamide (DMF) solvent, and the extracted phase of oil the initially enriched phenolic compound is obtained. The phenolic compounds are converted into phenol sodium salt dissolved in the inorganic phase by chemical caustic washing method, then reverse extract via acidification after separation to obtain phenolic compounds. Through the analysis and identification, the relative mass fraction of phenolic compounds in Fushun shale oil will be increased from 4.06% to 73.74% after enrichment. 49 kinds of phenolic compounds are identified in the extracted products, mainly for phenol class, including C3 phenol compounds with the highest mass fraction at 27.69%, and followed by C2 and C4 phenols at 19.18% and 15.96%, respectively.