在本文中，描述了一種用於DC-AC轉換器的BPSO優化的NTSMC，它

在本文中，描述了一種用於DC-AC轉換器的BPSO優化的NTSMC，它能夠產生低THD和快速瞬變。 NTSMC的重要性在於有限的系統狀態收斂時間且沒有奇異之處。另外，應該選擇NTSMC的參數以獲得最佳性能。傳統上，這些參數是通過反複試驗的方法確定的，該方法非常繁瑣，難以實施且耗時。因此，BPSO用於優化NTSMC參數，從而產生更好的瞬態和穩態響應。李雅普諾夫方法用於分析改進技術的穩定性。證明了滑動表面的有限時間可達性，閉環系統的漸近穩定性以及跟踪誤差的有限時間收斂性。因此，我們相信，改進的技術將有助於未來人工智能相關係統的控制設計。利用DSP對DC-AC轉換器的原型進行了仿真和實驗，以驗證改進技術的適用性。

結果 (英文) 1:

Herein, there is described a method for NTSMC DC-AC converter BPSO optimized, it can generate fast transient and low THD. NTSMC importance lies in the limited convergence time system status and there is no strange place. In addition, you should select the parameters NTSMC to get the best performance. Traditionally, these parameters are determined by trial and error, the process is very cumbersome, time consuming and difficult to implement. Thus, the BPSO NTSMC for optimizing parameters to produce better transient and steady state response. A method for improving Lyapunov stability analysis techniques. Proved sliding surface reachability finite time, closed-loop system asymptotic stability and tracking error convergence time is limited. Therefore, we believe that improved technology will help control the design of future artificial intelligence-related systems. DSP prototype using DC-AC converter is simulated and experiments to verify the applicability of the improved technique.

結果 (英文) 2:

In this article, a BPSO-optimized NTSMC for DC-AC converters is described to produce low THD and rapid transients. The importance of NTSMC lies in the limited system state convergence time and there is no singularity. In addition, the NTSMC parameters should be selected for optimal performance. Traditionally, these parameters have been determined by a trial-and-error method that is cumbersome, difficult to implement and time-consuming. As a result, BPSO is used to optimize NTSMC parameters for better transient and steady-state responses. The Lyapunov method is used to analyze the stability of the improved technology. The limited time accessibility of the sliding surface, the asymptomatic stability of the dead cycle system and the limited time convergence of the tracking error are proved. Therefore, we believe that improved technology will contribute to the control design of ad intelligence-related systems in the future. The prototype of the DC-AC converter was simulated and tested by DSP to verify the suitability of the improved technology.

結果 (英文) 3:

In this paper, we describe a BPSO optimized ntsmc for DC-AC converters, which can generate low THD and fast transients. The importance of ntsmc lies in the limited time of system state convergence and there is no singularity. In addition, ntsmc parameters should be selected for optimal performance. Traditionally, these parameters are determined by repeated experiments, which is very tedious, difficult to implement and time-consuming. Therefore, BPSO is used to optimize ntsmc parameters to produce better transient and steady-state response. Lyapunov method is used to analyze the stability of the improved technology. The finite time reachability of sliding surface, the asymptotic stability of closed-loop system and the finite time convergence of tracking error are proved. Therefore, we believe that the improved technology will contribute to the control design of future AI related systems. The prototype of DC-AC converter is simulated and tested with DSP to verify the applicability of the improved technology.