基于传统导引与控制相独立的无人机控导一体化问题是制约复杂战场环境下UCAV时敏攻击和精确打击能力提升的关键所在，而将导引与控制相融合的自主操控方式可充分实现相异功能模型间的优势互补从而平衡不同外部干扰间的差异，降低实时累积误差从而有效提高整体控制的鲁棒性。本项目通过研究高度不确定条件下的前端目标状态精确估计方法，针对多通道独立条件下的导引与控制系统融合以及全状态耦合的非自治非线性控制系统的部分状态调节问题，创新地提出了利用三通道独立解耦及非线性干扰观测的融合导引控制方法，结合自适应块动态面算法开展全状态耦合融合导引控制方法的相关理论建模，参数优化和实验验证三方面的研究工作，验证所提模型和方法既有对前端目标状态输出与导引控制过程的融合能力，又有对真实战场环境中存在的多种不确定性因素较强的适应能力，最终突破UCAV自主攻击中导引与控制融合的关键技术瓶颈，并在某UCAV平台验证其有效性及可靠性。

The integrated guidance and control problem of the unmanned aerial vehicle(UAV) based on traditional independent guidance and control systems is the key to restrict the ability increase of precious attack and time-sensitive attack of UCAV under the complicated war environment, while the autonomous operation mode of fusing the guidance system and control system can realize the mutual compensation of advantages between two different function models sufficiently so as to balance different divergence of external disturbance, besides, it would decrease the real-time accumulative error, thus, improve integral control robustness effectively. This project researches the front-end target state precision estimation method under high uncertain conditions, then puts forward an integrated guidance and control method using the three-channel independent decouple model and nonlinear disturbance observer, and carries out the related modeling theory, parameter optimization, and experimental verification of full states coupling integrated guidance and control by adopting an adaptive dynamic surface algorithm aiming at dealing with the three-channel independent integration problem of guidance and control systems and partial states regulation problem of the full states coupling non-autonomous nonlinear control system. Finally, the fusing ability between the front-end target state output and the integration of guidance and control, and the strong adaptability to various uncertainty factors in the real war environment of the proposed models and methods are verified. The proposed model and method in this project can break through the key technology bottleneck of the integration of guidance and control of the UCAV autonomous attack, and the effectiveness and reliability of them are tested on a certain UCAV platform.