Designing the Model Predictive Control for Interval Type-2 Fuzzy T-S Systems Involving Unknown Time-Varying Delay in Both States and Input Vector

In this paper, the model predictive control is designed for an interval type-2 Takagi-Sugeno (T-S) system with unknown time-varying delay in state and input vectors. The time-varying delay is a weird phenomenon that is appeared in almost all systems. It can make many problems and instability while the system is working. In this paper, the time-varying delay is considered in both states and input vectors and is the sensible difference between the proposed method here and previous algorithms, besides, it is unknown but bounded. To solve the problem, the Razumikhin approach is applied to the proposed method since it includes a Lyapunov function with the original nonaugmented state space of system models compared to Krasovskii formula. On the other hand, the Razumikhin method act better and avoids the inherent complexity of the Krasovskii specifically when large delays and disturbances are appeared. To stabilize output results, the model predictive control (MPC) is designed for the system and the considered system in this paper is interval type-2 (IT2) fuzzy T-S that has better estimation of the dynamic model of the system. Here, online optimization problems are solved by the linear matrix inequalities (LMIs) which reduce the burdens of the computation and online computational costs compared to the offline and non-LMI approach. At the end, an example is illustrated for the proposed approach

Implementing SVPWM Technique to an Axial Flux Permanent Magnet Synchronous Motor Drive with Internal Model Current Controller

This paper presents a study of axial flux permanent magnet synchronous motor (AFPMSM) drive system. An internal model control (IMC) strategy is introduced to control the AFPMSM drive through currents, leading to an extension of PI control with integrators added in the off-diagonal elements to remove the cross-coupling effects between the applied voltages and stator currents in a feed-forward manner. The reference voltage is applied through a space vector pulse width modulation (SVPWM) unit. A diverse set of test scenarios has been realized to comparatively evaluate the state estimation of the sensor-less AFPMSM drive performances under the implemented IMCbased control regime using a SVPWM inverter. The resulting MATLAB simulation outcomes in the face of no-load, nominal load and speed reversal clearly illustrate the well-behaved performances of IMC controller and SVPWM technique to an Axial Flux PM Motor Drive system

Hierarchical Optimization-Based Model Predictive Control for a Class of Discrete Fuzzy Large-Scale Systems Considering Time-Varying Delays and Disturbances

Altres ajuts: Acord transformatiu CRUE-CSICIn this manuscript, model predictive control for class of discrete fuzzy large-scale systems subjected to bounded time-varying delay and disturbances is studied. The considered method is Razumikhin for time-varying delay large-scale systems, in which it includes a Lyapunov function associated with the original non-augmented state space of system dynamics in comparison with the Krasovskii method. As a rule, the Razumikhin method has a perfect potential to avoid the inherent complexity of the Krasovskii method especially in the presence of large delays and disturbances. The considered large-scale system in this manuscript is decomposed into several subsystems, each of which is represented by a fuzzy Takagi-Sugeno (TS) model and the interconnection between any two subsystems is considered. Because the main section of the model predictive control is optimization, the hierarchical scheme is performed for the optimization problem. Furthermore, persistent disturbances are considered that robust positive invariance and input-to-state stability under such circumstances are studied. The linear matrix inequalities (LMIs) method is performed for our computations. So the closed-loop large-scale system is asymptotically stable. Ultimately, by two examples, the effectiveness of the proposed method is illustrated, and a comparison with other papers is made by remarks

Decentralized robust interval type-2 fuzzy model predictive control for Takagi–Sugeno large-scale systems

Here, decentralized robust interval type-2 (IT2) fuzzy model predictive control (MPC) for Takagi–Sugeno (T-S) large-scale systems is studied. The large-scale system consists of many IT2 fuzzy T–S subsystems. Important necessities that limit the practical application of MPC are the online computational cost and burden of the frameworks. For MPC of T–S fuzzy large-scale systems, the online computational burden is even worse, and in some cases, they cannot be solved timely. Especially for severe, large-scale systems with disturbances, the MPC of T–S fuzzy large-scale systems usually give a conservative solution. So, researchers have many challenges and in finding a reasonable solution in a short time. Although more comfortable results can be achieved by the proposed fuzzy MPC approach, which adopts T–S large-scale systems with nonlinear subsystems, many restrictions are not considered. In this paper, challenges are solved, and the MPC is designed for a nonlinear IT2 fuzzy large-scale system with uncertainties and disturbances. Besides, the online optimization problem is solved, and results are proposed. Consequently, the online computational cost of the optimization problem is reduced considerably. Finally, the effectiveness of the proposed algorithm is illustrated with two practical examples

Nonlinear Pseudo State-Feedback Controller Design for Affine Fuzzy Large-Scale Systems with H∞ Performance

Acord transformatiu CRUE-CSICThis paper treats robust controller design for Affine Fuzzy Large-Scale Systems (AFLSS) composed of Takagi-Sugeno-Kang type fuzzy subsystems with offset terms, disturbances, uncertainties, and interconnections. Instead of fuzzy parallel distributed compensation, a decentralized nonlinear pseudo state-feedback is developed for each subsystem to stabilize the overall AFLSS. Using Lyapunov stability, sufficient conditions with low codemputational effort and free gains are derived in terms of matrix inequalities. The proposed controller guarantees asymptotic stability, robust stabilization, and H∞ control performance of the AFLSS. A numerical example is given to illustrate the feasibility and effectiveness of the proposed approach

Effects of sexual education mobile applications on men’s sexual awareness and satisfaction: A randomized controlled trial

BACKGROUND: Sexual education programs can improve sexual awareness and satisfaction. Yet, sex education is ignored in developing countries. Under such circumstances, we have used IT tools to improve sexual education. OBJECTIVE: In this article, we used a mobile application (mHealth) to impart sex education. Methods: A randomized controlled trial was held, in which participants were randomly assigned to one of two groups: The control group, with 25 participants, which received only counseling from sex therapists, and the intervention group, with 25 participants, which received the mobile application system in addition to counseling from sex therapists. Participants were persons referred to sex therapists at a clinic. In each group, sexual satisfaction and awareness were evaluated. We measured sexual satisfaction with the help of the Larson questionnaire and sexual awareness by the Ann Hooper questionnaire. Results: Our data demonstrated that sexual satisfaction was not statistically significant (P=0.44), but awareness showed statistically significant differences (P=0.007) in the intervention vs. the control group. Also, the mean in both groups had statistically significant differences before and after the intervention (P=0.001). Conclusion: Our results showed that mobile applications can improve sexual awareness but cannot affect sexual satisfaction in the short term. Trial Registration: The clinical trial was registered with the Iranian Registry of Clinical Trials (IRCT) under registration ID:  IRCT2016110130640N

A novel robust extended dissipativity state feedback control system design for interval type-2 fuzzy Takagi-Sugeno large-scale systems

Recently, systems have become large in their model and dynamic. To apply control algorithms, serious problems appear that need to be solved. Two significant problems are modelling the dynamics of the large-scale system and reducing effects of perturbations. In this paper, we use the advantage of large-scale systems modelling based on the type-2 fuzzy Takagi–Sugeno model to cover the uncertainties caused by large-scale systems modelling. The advantage of using membership function information is the reduction of conservatism resulting from stability analysis. Also, this paper uses the extended dissipativity robust control performance index to reduce the effect of external perturbations on the large-scale system, which is a generalization of [Formula: see text], [Formula: see text], passive and dissipativity performance indexes and control gains can be achieved through solving linear matrix inequalities (LMIs). Hence, the whole closed-loop system is asymptotically stable. Finally, the effectiveness of the proposed method is demonstrated by two practical examples

Medical Information Sources Used by Specialists and Residents in Mashhad, Iran

Background: Physicians continually need to update their knowledge to ensure appropriate decision making about patient care. Objectives: We aimed to identify and compare information sources used by specialists and residents, their reasons for choosing these sources, and the level of their confidence in these sources. Materials and Methods: We conducted a cross-sectional study among specialists and residents using a validated questionnaire in the five academic hospitals affiliated with Mashhad University of Medical Sciences (in northeast Iran). We compared the specialists with residents in terns of gender, age, years since graduation, use of information sources, confidence in use of information sources, and reasons for selecting the information sources. Within each group, we also investigated the effect of work experience and gender on frequently used information sources and users' confidence in them. Results: The questionnaire was sent to 315 physicians, including 155 specialists and 160 residents. One hundred twenty-six specialists (response rate: 81 %) and 126 residents (response rate: 79%) completed it. The most frequently mentioned sources by all specialists included "English textbooks" (84.9%), "web/internet" (74.6%), "English medical journals" (62.3 %), and "discussions with colleagues" (57%). Among residents, "web/internet" ( 65.9%), "discussion with colleagues" (61.3%), and "Persian textbooks" (50.4%) were the most frequently used sources of information. In both groups, high confidence was demonstrated in "English textbooks," "English medical journals," and "international instructions/guidelines." Both groups counted reliability, easy accessibility, and being up to date as their primary reasons for the selection of their information sources. There was also a significantly negative correlation between using the internet as an information source and age in specialists (Spearman's rho=-0.238, p=0.01), but not in residents. Conclusions: Reliability, easy accessibility, and being up to date should be considered in establishing information sources for physician

Artificial Intelligence Literacy Among Healthcare Professionals and Students: A Systematic Review

Introduction: In the digital age, since the application of artificial intelligence (AI) is increasingly penetrating the world, the cultivation of AI literacy has become increasingly important for everyone. This systematic review investigated the level of AI literacy among healthcare professionals and students. Material and Methods: We searched the databases PubMed, Embase, Scopus, and Web of Science for relevant material. The evidence gathered from the studies included in this systematic review was reported in this study using preferred reporting items for systematic reviews and meta-analyses (PRISMA). Studies that assessed the level of AI literacy among medical and healthcare professionals and students met the inclusion criteria for this study. The quality of the included study for this review was assessed using the analytical cross-sectional critical assessment checklist developed by the Joanna Briggs Institute (JBI). The same standard checklist was used for data extraction. Results: Of the 10 included studies, 4 (40%) reported a low level of preparation, knowledge, and literacy. In a study, it was also shown that radiologists had acceptable literacy about AI, and it seems that they had a better study of this field compared to other specialists. Another study showed that initially the level of AI literacy was not acceptable but improved significantly after training. Two studies also hailed AI's contribution to improving healthcare. Conclusion: Evidence from this review indicated that half of the studies on the AI literacy of professionals and students were very low, and other included studies also reported the basic literacy of AI acceptably. Finally, in all included studies, AI training courses and their application in healthcare were considered necessary for professionals and students, and they were trying to improve the educational infrastructure