With the increasing complexity and frequency of interactions among a large number of heterogeneous nodes within a combat system of systems (SoS), evaluating the capability of the SoS to withstand external attacks and interferences has become an increasingly challenging and urgent issue. However, the complexity of a combat SoS often brings about difficulties in quantitative analysis. This paper proposes a method to assess the resilience of a combat SoS. Firstly, a network model of a combat SoS is constructed, taking into account multi-functional composite nodes. Secondly, the combat capability model of the combat SoS is built based on the capabilities of the kill chains and kill networks. Lastly, an approach is proposed to calculate the combat capability of the system based on the network’s two-terminal connectivity. Moreover, based on the SoS’s combat capability, the resilience is analyzed from the dimensions of anti-destruction, survival, and recovery. The simulation experiments show that, compared to other methods, the method in this paper for calculating the combat capability of the combat SoS does not depend on the number of kill chains and aligns with the combat processes and actual patterns. Additionally, the resilience measurement method can effectively analyze its capability to cope with external interferences.

Intelligent wars can take place not only in the physical domain and information domain but also in the cognitive domain. The cognitive domain will become the key domain to win in the future intelligent war. A Lanchester equation considering cognitive domain is proposed to fit the development tendency intelligent wars in this paper. One party is considered to obtain the exponential enhancement advantage on combat forces in combat if it can gain an advantage in the cognitive domain over the other party according to the systemic advantage function. The operational effectiveness of the cognitive domain in war is considered to consist of a series of indicators. Hesitant fuzzy sets and linguistic term sets are powerful tools when evaluating indicators, hence the indicators are scored by experts using hesitant fuzzy linguistic terms sets here. A unique hesitant fuzzy hybrid arithmetical averaging operator is used to aggregate the evaluation.

The hybrid unmanned aerial vehicle combines the vertical take-off and landing and hover abilities of rotary-wing UAVs with the high-speed cruise and long-endurance capabilities of fixed-wing UAVs, expanding the flight envelope and application areas. The designed controller must handle the highly nonlinear dynamics and variable actuators resulting from this combination. Furthermore, the performance of the controller is also influenced by uncertainties in model parameters and external disturbances. To address these issues, a unified robust disturbance rejection control based on fixed-time stability theory is proposed for attitude control. A fixed-time disturbance observer is utilized to estimate composite disturbances without some strict assumptions. Based on this observer, a nonsingular chattering-free fixed-time integral sliding mode control law is introduced to ensure that tracking errors converge to the origin within a fixed time. In addition, an optimized control allocator based on the weighted least squares method is designed to handle the overactuation of a dual-system hybrid UAV. Finally, numerical simulations and hardware-in-the-loop experiments under different flight modes and disturbance conditions are carried out, and compared with nonlinear dynamic inverse and the nonsingular terminal sliding mode control based on a finite-time observer, the developed controller enhances attitude angle tracking accuracy and disturbance rejection performance.

During the interception of a high-speed gliding vehicle (HGV), the predicted intercept point (PIP) is updated many times, so the interceptor must continuously adjust its trajectory. In this paper, we propose an online guidance correction algorithm for the interceptor, which can effectively meet the position constraints and energy management of the guidance process. Firstly, we simplify the interceptor’s maneuvering problem to a two-body orbital transfer problem. The Lambert orbit transfer method is used to enable the interceptor to maneuver towards the target’s PIP. Secondly, by comparing the target’s high probability existence area (THPEA) with the interceptor-interceptable area (IIA), the engine start threshold is set in stages to avoid frequent redundancy maneuvers caused by frequent engine starting during missile correction. This approach achieves energy management. Simulation results show that our midcourse guidance strategy is effective.

An adaptive attitude controller is designed based on Barrier Lyapunov Function (BLF) to meet the state constraints caused by side window detection. Firstly, the attitude controller is designed based on the BLF, but the stabilization function is complex and its time derivative will cause “differential explosion”. Therefore, Finite-time-convergent Differentiator (FD) is used to estimate the first derivative of the stabilization function. If the tracking error is outside the BLF's convergence domain, BLF controller cannot guarantee the error global convergence. Sliding mode controller (SMC) is used to make the system's error converge to set domain, and then the BLF controller could be used to ensure that the output constraint is not violated. Uncertainties and unknown time-varying disturbances usually make the control precision worse and Nonlinear Disturbance Observer (NDO) is designed for estimation and compensation uncertainties and disturbances. The pseudo rate modulator (PSR) is used to shape the continuous control command to pulse or on-off signals to meet the requirements of the thruster. Numerical simulations show that the proposed method can achieve state constraints, pseudo-linear operation, and high accuracy.