The presence of dense irregular obstacles in complex urban environments and strong nonlinear dynamics of fixed-wing Unmanned Aerial Vehicle (UAV) cause low efficiency of trajectory planning and safety risks for fixed-wing UAVs. To address these issues, this paper investigates a spatial-temporal hierarchical trajectory planning method for fixed-wing UAVs based on differential flatness. A hierarchical planning framework of “path planning-safe corridors generation-trajectory optimization” is constructed. Firstly, heuristic graph search is utilized to obtain the reference path as the initial motion. Guided by the path planning results, safe flight corridors are generated through the iterative regional inflation method, which efficiently provides the initial values and feasible regions of trajectories. Subsequently, to reduce the complexity of trajectory optimization, a differential flatness-based spatial-temporal trajectory parameterization model for fixed-wing UAVs is established, enabling elimination of nonlinear dynamics, and terminal and safety constraints. Additionally, by designing penalty costs to handle flight performance constraints and deriving their analytical gradients, the original problem of trajectory planning is transformed into an unconstrained nonlinear optimization with analytical gradients. Finally, a Differential Flatness-Based Spatial-Temporal Hierarchical Trajectory Planning (STH-DFTP) algorithm is proposed to achieve efficient trajectory generation. The simulation results illustrate that the proposed STH-DFTP has superior efficiency, which only takes 10⁻²–10⁻¹ s to generate the flight trajectories for fixed-wing UAVs in complex urban environments, meeting the requirements for online trajectory planning in practice.

To realize continuous leapfrog upgrades of the hypersonic vehicle from single-point optimal fixed configuration to full envelope optimal of morphing configuration, a quasi-wave rider profile and composite deformation scheme morphing wingspan and sweep are designed. On this basis, to reduce the computational burdens of reentry trajectory planning, the adaptive trust-region-based penalty sequence convex programming method is proposed. To increase the approximate accuracy, the path restrictions are communicated using the logarithmic convexification technique. A virtual control is introduced to replace the dynamic equation constraints. Using the penalty function method, modify the second-order cone constraint and incorporate it into the objective function to direct the iterative results in order to approximate the feasible domain. An adaptive trust region updating strategy is designed to accelerate the convergence of the sequence convex optimization algorithm. As demonstrated by the simulation results, the hypersonic morphing vehicle's range extension is 16.63% when compared to the fixed configuration, and the ATP-SCP computing time is 89.24% less than when compared to the HP pseudospectral method.

In this paper, the multi-missile cooperative guidance system is formulated as a general nonlinear multi-agent system. To save the limited communication resources, an adaptive event-triggered optimal guidance law is proposed by designing a synchronization-error-driven triggering condition, which brings together the consensus control with Adaptive Dynamic Programming (ADP) technique. Then, the developed event-triggered distributed control law can be employed by finding an approximate solution of event-triggered coupled Hamilton-Jacobi-Bellman (HJB) equation. To address this issue, the critic network architecture is constructed, in which an adaptive weight updating law is designed for estimating the cooperative optimal cost function online. Therefore, the event-triggered closed-loop system is decomposed into two subsystems: the system with flow dynamics and the system with jump dynamics. By using Lyapunov method, the stability of this closed-loop system is guaranteed and all signals are ensured to be Uniformly Ultimately Bounded (UUB). Furthermore, the Zeno behavior is avoided. Simulation results are finally provided to demonstrate the effectiveness of the proposed method.