Aiming at the challenges to the accurate and stable heading control of underactuated unmanned surface vehicles arising from the nonlinear interference caused by the overlay and the interaction of multi interference, and also the uncertainties of model parameters, a heading control algorithm for an underactuated unmanned surface vehicle based on an improved backpropagation neural network is proposed. Based on applying optimization theory to realize that the underactuated unmanned surface vehicle tracks the desired yaw angle and maintains it, the improved momentum of weight is combined with an improved tracking differentiator to improve the robustness of the system and the dynamic property of the control. A hyperbolic tangent function is used to establish the nonlinear mappings an approximate method is adopted to summarize the general mathematical expressions, and the gradient descent method is applied to ensure the convergence. The simulation results show that the proposed algorithm has the advantages of strong robustness, strong anti-interference and high control accuracy. Compared with two commonly used heading control algorithms, the accuracy of the heading control in the complex environment of the proposed algorithm is improved by more than 50%.
In this paper, a novel dynamic surface sliding mode control (DSSMC) method, combined with a lateral velocity tracking differentiator (LVTD), is proposed for the cooperative formation control of underactuated unmanned surface vehicles (USVs) exposed to complex marine environment disturbances. Firstly, in view of the kinematic and dynamic models of USVs and the design idea of a virtual control law in a backstepping approach, the trajectory tracking control problem of USVs’ cooperative formation is transformed into a stabilisation problem of the virtual control law of longitudinal and lateral velocities. Then, aiming at the problem of differential explosion caused by repeated derivation in the process of backstepping design, the first-order low-pass filter about the virtual longitudinal velocity and intermediate state quantity of position is constructed to replace differential calculations during the design of the control law, respectively. In order to reduce the steady-state error when stabilising the virtual lateral velocity control law, the integral term is introduced into the design of the sliding mode surface with a lateral velocity error, and then the second-order sliding mode surface with an integral is structured. In addition, due to the problem of controller oscillation and the role of the tracking differentiator (TD) in active disturbance rejection control (ADRC), the LVTD is designed to smooth the state quantity of lateral velocity. Subsequently, based on the dynamic model of USV under complex marine environment disturbances, the nonlinear disturbance observer is designed to observe the disturbances and compensate the control law. Finally, the whole cooperative formation system is proved to be uniformly and ultimately bounded, according to the Lyapunov stability theory, and the stability and validity of the method is also verified by the simulation results.
The longitudinal shaft anchor excavation machine is a new type of excavating machinery; the cutting head directly participates in cutting work. This paper focuses on the performance parameters of the cutting head. Two variables of the cutting head are selected to study, that is, the included the alloy head clip angle and the alloy head diameter. The installation angle of the pick is 55° and the section spac-ing is 60 mm. Three groups of data were selected for each variable, and the ANSYS finite element analysis software was used to simulate the rock cutting of the pick, and the load characteristics of the pick were obtained. The fuzzy number principle and entropy evaluation method are used to evaluate the load fluctuation, specific energy consumption, and pick load of three groups of data in each variable, and then the optimal performance parameters of the pick are obtained. The specific work is as follows: 1. Two parameter variables of the pick are selected and analyzed by LS-DYNA simulation software to obtain the cutting load of the pick at work. 2. Determine the index set and evaluation set of the cutting head, use the fuzzy number principle and entropy evaluation method to calculate the weight of each pa-rameter variable, create the fuzzy number relation evaluation matrix of performance parameters, and then use the fuzzy number comprehensive evaluation model to calculate the fuzzy number comprehensive evaluation result vector, finally get a set of optimal performance parameters of the pick. The final results show that the cutting head has the best performance when the alloy head clip angle is 100° and the alloy head diameter is 11 mm.
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