Dual-rate modified stochastic gradient identification for permanent magnet synchronous motor

The high-performance application of high-power permanent magnet synchronous motor (PMSM) is increasing. This paper focuses on the parameter estimation of PMSM. A novel estimation algorithm for PMSM’s dual-rate sampled-data system has been developed. A polynomial transformation technique is employed to derive a mathematical model for PMSM’s dual-rate sampled-data system. The proposed modified stochastic gradient algorithm gets more excellent convergence performance for smaller index ε. Simulation and experimental results demonstrate the effectiveness and performance improvement of the proposed algorithm

Multirate input based quasi-sliding mode control for permanent magnet synchronous motor

Permanent magnet synchronous motor field oriented control system often uses dual-loop (speed and current) cascade structure, and the dynamics speeds of the two loops mismatch. The motor’s mechanical and electrical subsystems have the typical multirate characteristics. Based on the multirate control theory, this paper proposes multirate input quasi-sliding mode algorithm for the speed control loop. Under the situation of the output data loss, the proposed algorithm builds the extended input vector with the output prediction information. Due to the extended input vector, the proposed algorithm reduces the system steady state chatterring, and then improves the performance of the whole system. Simulation and experimental results demonstrate the effectiveness of the proposed algorithm

Why Users Accept Discriminatory Pricing: The Roles of AI Agent\u27s Presence and Explanation

Discriminatory pricing practices have raised consumers’ negative reactions. This study investigates how AI agent’s presence and the use of explanations impact consumers\u27 acceptance of discriminatory pricing. A scenario-based experiment revealed that AI agent’s presence negatively moderates the negative relationship between offer unfavorability and offer acceptance, which is mediated by perceived justice and invasion of privacy. Moreover, this research indicated that for unfavored price, environment-based explanation is more effective than user-based explanation and the positive effect of AI agent’s presence on offer acceptance is more pronounced when providing user-based explanations. This study contributes to price management literature and AI decision literature by illustrating how the AI agent\u27s presence asymmetrically shapes consumers\u27 perceptions of offer outcomes, enriching our understanding of consumer responses to AI. The findings have implications for firms managing discriminatory pricing, offering insights into optimal AI agents and explanation utilization for enhancing customer experience and business performance

Algorithmic Pricing and Fairness: A Moderated Moderation Model of AI Disclosure and Typicality of AI Pricing

In the era of big data, the utilization of algorithms for dynamic pricing has become prevalent. However, concerns have been raised about the potential negative impact of these practices on consumers\u27 fairness perceptions. Using attribution theory as the underlying framework, we explore how AI disclosure moderates the relationship between AI pricing type (unified/personalized dynamic pricing) and fairness perceptions (procedural/distributive fairness) and how this moderation effect is further moderated by the perceived typicality of AI pricing. An online scenario-based experiment was carried out with 145 participants. The results reveal that personalized dynamic pricing elicits lower fairness perceptions than unified dynamic pricing. Furthermore, we observe a significant moderated moderation effect, indicating that the negative impact of personalized dynamic pricing can be mitigated by AI disclosure for consumers who perceive AI pricing as typical. These findings contribute to AI pricing literature and the development of fairer platform designs

Follow-up observation of three operative treatments for primary infantile glaucoma

AIM: To compare the efficacy and complication of extra-trabeculotomy in combination with trabeculectomy and trabeculectomy and compound trabeculectomy in the treatment of primary infantile glaucoma. <p>METHODS: Patients with primary infantile glaucoma undergone one of the three procedures from Jan 2006 to Jan 2014 were selected. Among them, group A(20 patients, 31 eyes)underwent extra-trabeculotomy in combination with trabeculectomy, group B(20 patients, 32 eyes)underwent trabeculectomy, while group C(20 patients, 30 eyes)underwent compound trabeculectomy <p>RESULTS: The success rates in group A were 96.8% at the time of discharge and 90.3% during follow-up(mean 24mo); the rates in group B were 96.9% and 81.2%(mean 24mo)the rates in group C were 83.3% and 76.7%(mean 24mo)respectively, the differences being significant(<i>P </i><0.05). In group A and group B, there was no severe complications, while in group C, one case had vitreous prolapse.<p>CONCLUSION: Extra-trabeculotomy in combination with trabeculectomy is more efficacious and safer than trabeculectomy and compound trabeculectomy in the treatment of primary infantile glaucoma. It should be the first choice for primary infantile glaucoma