The increasing demand for multi-degree-offreedom (DOF) actuators in a number of industries has motivated a flurry of research in the development of non-conventional actuators, spherical motor. This motor is capable of provid ing smooth and isotropic threedimensional motion in a single joint. Not only can the spherical motor combine 3-DOF motion in a single joint, it has a large range of motion with no singularities in its workspace. The spherical motor, however, exhib its coupled, nonlinear and very complex dynamics that make the design and implementation of feedback controllers very challenging. The orientationvarying torque generated by the spherical motor also contributes to the challenges in controller design. This paper contributes to the ongoing research effort by exploring alternate methods for nonlinear and robust controlling the motor. The robust sliding mode controller proposed in this paper is used to further demonstrate the appealing features exhibited by the spherical motor. In opposition, sliding mode controller is used in many applications especially to control of highly uncertain systems; it has two significant drawbacks namely; chattering phenomenon and nonlinear equivalent dynamic formu lation in uncertain dynamic parameter. The nonlinear equivalent dynamic formulat ion problem and chattering phenomenon in uncertain system (e.g., spherical motor) can be solved by using artificial intelligence theorem and applied a modified linear controller to switching part of sliding mode controller. Using Lyapunov-type stability arguments, a robust modified linear fuzzy sliding mode controller is designed to achieve this objective. The controller developed in this paper is designed in a robust stabilizing torque is designed for the nominal spherical motor dynamics derived using the constrained Lagrangian formulation. The eventual stability of the controller depends on the torque generating capabilities of the spherical motor.

No abstract

No abstract

Fuzzy logic controller (FLC) is an important nonlinear controller in an uncertain dynamic system's parameters. This controller is used to control of nonlinear dynamic systems particularly for spherical motor, because it has a suitable control performance and it is a stable. Conversely pure fuzzy logic controller is a high-quality intelligent nonlinear controller; it has two important problems; reliability and robustness in uncertain dynamic parameter. To increase the reliability and robustness, this research is focused on applied feedback linearization method in pure fuzzy logic controller. In this research the nonlinear equivalent dynamic (equivalent part) formulation problem in uncertain condition is also solved by combine pure fuzzy logic control and feedback linearization method. In this method feedback linearization theorem is applied to fuzzy logic controller to increase the stability, reliability and robustness, which it is based on nonlinear dynamic formulation. To achieve this goal, the dynamic-based formulation feedback linearization method is design. This method is robust and model-based nonlinear control therefore can reduce the nonlinearity term of system and reduce the effect of coupling. In this research MAMDANI fuzzy inference system is used as a main controller. It has minimum rule base to practical implementation. This technique was employed to obtain the desired control behavior with a number of information about dynamic model of system and a feedback linearization control was applied to reinforce system performance.

Purpose The purpose of this paper is to examine the effect of green coffee extract on anthropometric index and lipid profile, fasting blood sugar, chemerin and malondialdehyde on subjects with metabolic syndrome. Design/methodology/approach A randomized, double-blind, placebo-controlled clinical trial was conducted in Sheikh Al Raise Clinic from September 2016 to March 2017. The participants were randomly divided into green coffee group and placebo group. Green coffee group (n = 24) received green coffee extract (GCE), while placebo group (n = 24) took cellulose as a placebo, two capsules (400 mg) two times each day for eight weeks. The anthropometric index and lipid profile, fasting blood sugar, chemerin and malondialdehyde were measured at the beginning of the study and after eight weeks of treatment with GCE. Blood samples were collected before and after eight weeks of supplementation. Findings Significant weight loss, from 84.80 ± 2.12 kg to 80.94 ± 2.10 kg (ptime = 0.030, pGC = 0.007), as well as decreases in body mass index (ptime = 0.034, pGC = 0.006) were detected in the green coffee group after eight weeks. Also, the green coffee group has significant lower (pgroup = 0.029, ptime = 0.013) malondialdehyde (MDA) compared to the placebo group, and there was a significant difference between two groups at the insulin level and homeostatic model assessment of insulin resistance (HOMA-IR) (ptime = 0.001, pgroup = 0.048), (ptime = 0.012, pgroup = 0.007). However, there was no significant difference in lipid profile, fasting blood sugar and serum chemerin between two groups after eight weeks of supplementation. Originality/value This paper showed the statistical difference in body weight, malondialdehyde, insulin and insulin resistance after eight weeks of treatment. GCE might be associated to reduction in the carbohydrate absorption and the enhancement of lipid metabolism.

No abstract

Background: To investigate the effects of probiotics on glucose metabolism and body mass index (BMI), and compare the efficacy of probiotic food with probiotic supplement in patients with type 2 diabetes mellitus using a metaanalysis of randomized, controlled trials. Methods: Online databases Embase, Web of Science, and PubMed were searched until November 2019 to identify eligible articles. Fourteen trials were included. Results: Probiotic consumption significantly changed fasting plasma glucose (FPG) (SMD=-0.38, 95% CI: -0.76 to 0.01), glycosylated hemoglobin (HbA1c) (SMD=-0.64, 95% CI: -0.91 to -0.38), fasting insulin concentration (SMD=-0.48, 95% CI, -0.81 to -0.15), and HOMA-IR (SMD=-1.01, 95% CI, -1.51 to -0.52) compared with control groups. Probiotics made a non-significant reduction of BMI (SMD=-0.02, 95% CI, -0.17 to 0.13) compared with control groups. Subgroup analysis was conducted to trials with probiotic foods and probiotic supplement. Both of probiotic foods (SMD: -0.65, 95% CI: - 1.04 to -0.26; SMD: -1.17, 95% CI: -2.14 to -0.20, respectively) and supplements (SMD: -0.64, 95% CI: -1.01 to -0.27; SMD: -0.98, 95% CI: -1.55 to -0.40, respectively) made significant reduction in HbA1c and HOMA.IR. Meta-analysis of trials with probiotic foods found non-significant changes in FBG and fasting insulin (SMD: 0.11, 95% CI: -0.52 to 0.75; SMD: -0.14, 95% CI: -0.48 to 0.20, respectively); however the reductions in trials with probiotic supplement were significant (SMD: -0.73, 95% CI: -1.22 to -0.23; SMD: -0.57, 95% CI: -0.97 to -0.17, respectively). Probiotic foods cause a non-significant raise in BMI (SMD: 0.23, 95% CI: -0.03 to 0.49); however, meta-analysis of trials with probiotic supplementation found a non-significant reduction in BMI (SMD: -0.13, 95% CI: -0.31 to 0.04). Conclusions: The present meta-analysis suggests that consuming probiotics could improve glucose metabolism and affect body weight, with a potentially greater effect when the probiotics are used as supplement.

No abstract