In this paper, the input-output finite time stability of fuzzy sliding mode control in nonlinear robot systems is discussed. Specifically, the system considers more realistic factors, such as uncertainty, nonlinearity, interference, and state delay. An improved fuzzy sliding mode control (FSMC) scheme is developed, which is considered in most results of FSMC schemes. Based on the input-output finite-time stability characteristics and the proposed control scheme, the objective of this work is to reduce the effects of uncertainty, nonlinearity, disturbance, and state delay. Finally, the effectiveness and superiority of the proposed method are verified by simulation and comparison with other reference methods.
As an important power component of the material conveying system, the motor will inevitably cause the vibration of the mechanical structure when rotating, thus affecting the stable operation of the motor. Most material conveying systems have high requirements for motor vibration level, and usually take vibration performance and electrical performance as the evaluation criteria of the same level. A nonlinear terminal sliding mode controller is proposed to solve the phase delay and vibration problems in the sliding mode control system of surface-mounted permanent magnet synchronous motor (SPMSM) in material transmission system.. The sliding surface is an organic combination of nonlinear sliding mode and fast terminal mode, and its relative stability is verified by Lyapunov function. Through MATLAB simulation and fine comparison analysis with other advanced sliding mode control system methods, it can be seen from the simulation results that the signal of the proposed method can obviously control the noise, and the global root-mean-square error is only 1.9%, so it can be seen that the scheme is feasible..
The transportation of containers plays an important role in the transportation of cargos. The effective loading of containers can greatly reduce the transportation cost of logistics cargos. The purpose of packing problem is to get a reasonable packing scheme, so using heuristic algorithm to obtain approximate solution in limited time has become the first choice to solve this kind of problem. Container packing problem is a classic three-dimensional packing problem. In this paper, the mathematical model of the container problem is established with the maximum utilization of container space as the loading optimization objective. A combination heuristic algorithm is proposed, and the actual data of a company is modeled and solved through python programming, and a visual model is established to obtain a loading scheme with the maximum utilization rate of container space of 95.2%. It proves the effectiveness and feasibility of the algorithm in a certain sense, and verifies the effectiveness of the optimization algorithm in this paper.
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