For the chaotic motion control of a vibro-impact system with clearance, the parameter feedback chaos control strategy based on the data-driven control method is presented in this article. The pseudo-partial-derivative is estimated on-line by using the input/output data of the controlled system so that the compact form dynamic linearization (CFDL) data model of the controlled system can be established. And then, the chaos controller is designed based on the CFDL data model of the controlled system. And the distance between two adjacent points on the Poincaré section is used as the judgment basis to guide the controller to output a small perturbation to adjust the damping coefficient of the controlled system, so the chaotic motion can be controlled to a periodic motion by dynamically and slightly adjusting the damping coefficient of the controlled system. In this method, the design of the controller is independent of the order of the controlled system and the structure of the mathematical model. Only the input/output data of the controlled system can be used to complete the design of the controller. In the simulation experiment, the effectiveness and feasibility of the proposed control method in this article are verified by simulation results.
In order to reduce the threat cost of multi-UAV coordination, improve the effective flight time and the mission success rate, a path planning model was designed for the effectiveness and real-time performance of multi-UAV track coordination. In this paper, based on the path planning model under the condition of non-interference, the model of minimum cost flight path of multi-UAV based on time synergy is given, and a time-sequence-space coordination model is proposed to meet the requirements of electronic jamming, mission confusion and radar illumination. The decision variables of range and threat are introduced into the collaborative function of track cost, and by adjusting the cost functions and collaborative variables in real time, the path planning model was optimized for unmanned support aircraft in coordination with multiple unmanned aircraft mission, at the same time, the genetic algorithm is improved by combining the adaptive crossover rate and mutation rate, and the optimization of track collaborative solution process is realized. Finally, the effectiveness of track coordination model of multi-UAV based on decision variables and improved genetic algorithm is verified by semi-physical simulation.
With the improvement of reliability design of nonlinear airborne power supply system, it is more difficult to analyze the performance degradation of components under lean failure data in reliability growth test. In this paper, a state space model of performance degradation was established for nonlinear airborne power system, and the method of performance degradation modeling and analysis was studied by using nonlinear logistic regression process. Taking electrical, mechanical and thermal stress as characteristic failure loads, a nonlinear logistic regression analysis model was established to describe the performance degradation under comprehensive stress. The state of the degradation space is divided by the Markov distance, and the performance degradation trajectory is transformed into the degradation state space by using the maximum likelihood model and correlation degree model of observed variables, the degradation space trajectory of the performance of the characteristic parameters under multi-input variables is obtained. The correctness and validity of the nonlinear logistic regression model and the degradation process analysis method are verified by the test on the brushless motor reliability test platform.
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