This research focuses on motion control of hydraulic servo-mechanism and presents a novel quasi-adaptive sliding mode control algorithm with barrier function-based control gain. The mathematical model of the system is established in integral series format to contribute to the controller design. The utilized sliding mode control gain is designed to be adapted with the change of design error related to tracking error. It can first increase until the design error reaches to a small domain at a designed time by utilizing constant gain. And then the control gain will automatically switch to barrier function form to hold design error within a predefined domain un-depending on the modeling uncertainties theoretically. Correspondingly, the tracking error will converge to a small domain. The system stability is proved via Lyapunov analysis. By comparing to three classic controllers with motion tracking experiments, the achievable higher tracking accuracy of the proposed new control law are validated sufficiently.

This technical note focus on the tracking control problem of uncertain nonlinear systems with multiple states constraints. Based on the Barrier Lyapunov function and backstepping technology, a new continuous smooth control solution can be ultimately synthesized to realize asymptotic tracking control in presence of multiple states constraints and modeling uncertainties. Firstly, the modeling uncertainties are divided into periodic and un-periodic components and Fourier expansion technology is employed to translate the periodic disturbance into the form which can be easily compensated. Then the Barrier Lyapunov function are flexibly utilized to design the virtual control law of every step and the final controller, which can guarantee the specified states within certain bounds regardless of the amplitude of system output. Meanwhile, a novel nonlinear control technology is introduced to each design step to realize the final asymptotic tracking control despite the matched and mismatched uncertainties. By analyzing the choice of the control parameters, the backstepping cross-term is skillfully dealt with and the stability of the whole system is proved rigorously. Finally, the simulation results on a three-order nonlinear hydraulic system demonstrate the satisfactory performance of the proposed control method.

Aiming at the problem that the current aerial infrared aircraft targets are blurred, low contrast, and susceptible to noise interference, which can lead to inaccurate recognition, an improved YOLOv4-tiny infrared aircraft target detection method based on cavity convolution is proposed. First, in order to make full use of the shallow features, add a parallel branch after the feature layer whose output size of YOLOv4-tiny is; then, after the first network output layer, add three parallel holes of 1, 3 respectively. 5. The depth of 5 can separate the hollow convolution layer to expand the feature map receptive field; finally, the feature fusion network is improved, the final output feature layer of the network, the improved anti-residual block extraction feature, and the size is adjusted after convolution. The prediction result is processed and output by yolo head. Experiments on the aerial infrared aircraft data set show that compared with the original YOLOv4-tiny, the detection accuracy is increased by 4.29% and the detection effect is significantly improved under the premise of less loss of detection frame rate and small weight.

The problem of cooperative interception of the manoeuvring target is investigated in this paper. Firstly, in light of fast fixed-time consensus theory, time-to-go, and undirected topologies, adaptive cooperative guidance along the line-of-sight (LOS) direction is proposed to guarantee impact time synchronization. Next, novel nonsingular terminal sliding mode (NTSM) is designed to establish adaptive fixed-time guidance law for steering LOS angular rates to the origin or its small neighbourhood. Without the knowledge of target manoeuvre, the proposed cooperative guidance law can be provided by lateral and longitudinal accelerations of each missile, while more reasonable and rigorous analysis of fixed-time stability is carried out through the Lyapunov theory. Within the specified time, both control tasks of simultaneous attack and the desired impact angles can be completed before the final time of the guidance process. Finally, numerical simulations demonstrate the feasibility and effectiveness of the proposed scheme.

In underwater acoustic networks, the accurate estimation of routing weights is NP-hard due to the time-varying environment. Fuzzy logic is a powerful tool for dealing with vague problems. Software-defined networking (SDN) is a promising technology that enables flexible management by decoupling the data plane from the control plane. Inspired by this, we proposed a fuzzy logic-based software-defined routing scheme for underwater acoustic networks (FL-SDUAN). Specifically, we designed a software-defined underwater acoustic network architecture. Based on fuzzy path optimization (FPO-MST) and fuzzy cut-set optimization (FCO-MST), two minimum spanning tree algorithms under different network scales were proposed. In addition, we compared the proposed algorithms to state-of-the-art methods regarding packet delivery rate, end-to-end latency, and throughput in different underwater acoustic network scenarios. Extensive experiments demonstrated that a trade-off between performance and complexity was achieved in our work.