Multi-motor position synchronization control method based on non-singular fast terminal sliding mode control.

In order to improve the position high-precision synchronization performance of multi-motor synchronous control, a multi-motor position synchronization control method based on non-singular fast terminal sliding mode control (NFTSMC) combined with an improved deviation coupling control structure (Improved Deviation Coupling Control(IDCC), NFTSMC+IDCC). Firstly, this paper designs a sliding mode controller using a non-singular fast terminal sliding mode surface with a Permanent Magnet Synchronous Motor (PMSM) as the control object. Secondly, the deviation coupling is improved to enhance the coupling between multiple motors and achieve position synchronization. Finally, the simulation results show that the total error of multi-motor position synchronization under NFTSMC control is 0.553r in the simulation of multi-motor synchronization control under the same working conditions, which is 2.873r and 1.772r less than that of SMC and FTSMC in terms of speed error, and the anti-disturbance performance is 83.68% and 76.22% higher than that of both of them, respectively. In the subsequent simulation of the improved multi-motor position synchronization structure, the total error of the multi-motor position is in the range of 0.56r-0.58r at three speeds, which is much smaller than the synchronization error under the Ring Coupling Control (RCC) structure and Deviation Coupling Control (DCC) structure, showing a better The synchronization error is much smaller than that of the RCC structure and DCC structure, which shows better position synchronization performance. Therefore, the multi-motor position synchronization control method proposed in this paper has a good position synchronization effect and achieves the control effect of small displacement error and fast convergence of the multi-motor position synchronization control system after being disturbed, the control performance is significantly improved.

Three-dimensional continuous picking path planning based on ant colony optimization algorithm.

Fruit-picking robots are one of the important means to promote agricultural modernization and improve agricultural efficiency. With the development of artificial intelligence technology, people are demanding higher picking efficiency from fruit-picking robots. And a good fruit-picking path determines the efficiency of fruit-picking. Currently, most picking path planning is a point-to-point approach, which means that the path needs to be re-planned after each completed path planning. If the picking path planning method of the fruit-picking robot is changed from a point-to-point approach to a continuous picking method, it will significantly improve its picking efficiency. The optimal sequential ant colony optimization algorithm(OSACO) is proposed for the path planning problem of continuous fruit-picking. The algorithm adopts a new pheromone update method. It introduces a reward and punishment mechanism and a pheromone volatility factor adaptive adjustment mechanism to ensure the global search capability of the algorithm, while solving the premature and local convergence problems in the solution process. And the multi-variable bit adaptive genetic algorithm is used to optimize its initial parameters so that the parameter selection does not depend on empirical and the combination of parameters can be intelligently adjusted according to different scales, thus bringing out the best performance of the ant colony algorithm. The results show that OSACO algorithms have better global search capability, higher quality of convergence to the optimal solution, shorter generated path lengths, and greater robustness than other variants of the ant colony algorithm.

Misperception of sleep duration in mild traumatic brain injury/concussion: a preliminary report.

Background: Polysomnographic (PSG) findings of persons with mild traumatic brain injury (mTBI)/concussion show longer total sleep time than patients themselves report; the reason for this is not entirely clear.Objective: This study aimed to elucidate the socio-demographic, brain-injury-related, and clinical characteristics that underlie accuracy of sleep duration reporting in mTBI/concussion.Methods: Thirty-seven participants diagnosed with mTBI/concussion (57% male, 47.54 ± 11.3 years old) underwent clinical and neuroimaging examinations, full-night PSG, and estimated sleep duration following PSG.Results: Mean self-reported sleep duration was 342 ± 93.6 minutes and PSG-measured sleep duration was 382 ± 76.8 minutes. Measurements were moderately correlated (rho = 0.46, p = .004). Age associated with self- and PSG-measured sleep duration (rho = 0.34 and rho = 0.84, respectively, p < .05). Self-reported sleep duration was uniquely associated with insomnia severity (rho = -0.48, p = .002). In the fully adjusted multivariable regression analysis, several clinical characteristics of patients explained 30% of the discrepancy between self- and PSG-measured sleep duration.Conclusion: The observed results indicate that persons with mTBI do not accurately assess their sleep duration and, therefore, PSG is warranted in clinical situations where sleep duration is of concern.