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

The effect of peanut pod on performance, small intestine pH and ileum bacteria population in broiler chickens

This experiment was designed to assess the hypothesis that feeding broilers with peanut pod as an insoluble fibre source will result in improved gut digestive capacity growth performance. The experimental diets consisted of a control diet and three diets containing 25, 50, or 75 g peanut pod /kg. The dietary peanut pod, especially at the 50 g/kg level decreased feed intake of the experimental groups. In grower phase, the best weight gain was recorded in the broiler chickens fed the diet containing 75 g peanut pod /kg. All the peanut pod containing diets decreased grower phase feed conversion ratio compared to the control group. In the finisher phase, the growth rate and feed conversion ratio were not affected by the experimental diets. The gizzard weight and gastrointestinal length was increased in the chickens fed 75 g peanut pod /kg, and these groups showed the lowest pH for gizzard content. In the ileum, the birds fed 25 g peanut pod /kg had a higher Lactobacillus population than the 75 g peanut pod /kg group; and the birds fed 25 g peanut pod had lower Escherichia coli (E. coli) population, compared to the control group. The positive effects of dietary insoluble fibre on the growth performance of broilers in this study were probably a result of favourable changes in the bacteria populations and also an increase in digestive capacity of gastrointestinal.Keywords: Broilers, gut pH, ileum bacteria, peanut po

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

Forward Bifurcation with Hysteresis Phenomena from Atherosclerosis Mathematical Model

Atherosclerosis is a non-communicable disease (NCDs) which appears when the blood vessels in the human body become thick and stiff. The symptoms range from chest pain, sudden numbness in the arms or legs, temporary loss of vision in one eye, or even kidney failure, which may lead to death. Treatment in cases with severe symptoms requires surgery, in which the number of doctors or hospitals is limited in some countries, especially countries with low health levels. This article aims to propose a mathematical model to understand the impact of limited hospital resources on the success of the control program of atherosclerosis spreads. The model was constructed based on a deterministic model, where the hospitalization rate is defined as a time-dependent saturated function concerning the number of infected individuals. The existence and stability of all possible equilibrium points were shown analytically and numerically, along with the basic reproduction number. Our analysis indicates that our model may exhibit various types of bifurcation phenomena, such as forward bifurcation, backward bifurcation, or a forward bifurcation with hysteresis depending on the value of hospitalization saturation parameter and the infection rate for treated infected individuals. These phenomenon triggers a complex and tricky control program of atherosclerosis. A forward bifurcation with hysteresis auses a possible condition of having more than one stable endemic equilibrium when the basic reproduction number is larger than one, but close to one. The more significant value of hospitalization saturation rate or the infection rate for treated infected individuals increases the possibility of the stable endemic equilibrium point even though the disease-free equilibrium is stable. Furthermore, the Pontryagin Maximum Principle was used to characterize the optimal control problem for our model. Based on the results of our analysis, we conclude that atherosclerosis control interventions should prioritize prevention efforts over endemic reduction scenarios to avoid high intervention costs. In addition, the government also needs to pay great attention to the availability of hospital services for this disease to avoid the dynamic complexity of the spread of atherosclerosis in the field

Assessing The Impact of Medical Treatment and Fumigation on The Superinfection of Malaria: A Study of Sensitivity Analysis

Malaria is a disease caused by the parasite Plasmodium, transmitted by the bite of an infected female Anopheles. In general, five species of Plasmodium that can cause malaria. Of the five species, Plasmodium falciparum and Plasmodium vivax are two species of Plasmodium that can allow malaria superinfection in the human body. Typically, the popular intervention for malaria eradication is the use of fumigation to control the vector population and provide good medical services for malaria patients. Here in this article, we formulate a mathematical model based on a host-vector interaction. Our model considering two types of plasmodium in the infection process and the use of medical treatment and fumigation for the eradication program. Our analytical result succeeds in proving the existence of all equilibrium points and how their existence and local stability criteria depend not only on the control reproduction number but also in the invasive reproduction number. This invasive reproduction number represent how one plasmodium can dominate other plasmodium. Our sensitivity analysis shows that fumigation is the most influential parameter in determining all control reproduction numbers. Furthermore, we find that the order in which numerous intervention measures are taken will be very crucial to determine the level of success of our malaria eradication program

Impact of Nitrogen Nutrition through Organic and Inorganic Sources of Fertilizer on Growth Phenology and Yield of Wheat (Triticum aestivum L.)

The field experiment was conducted at wheat research farm of CCS Haryana Agriculture University during Rabi season of 2019-20 to study nitrogen nutrition through organic and inorganic source of fertilizer on growth phenology, yield and quality of wheat (Triticum aestivum L.) The experiment was laid out in randomized block design with three replications containing 16 treatments combination i.e T1-Control; T2-100% RDN through urea; T3- 100% RDN through FYM; T4-100% RDN through vermicompost; T5-50% RDN through urea+ 50% RDN through FYM; T6-50% RDN through urea+ 50% RDN through vermicompost; T7-25% RDN through urea+ 75% RDN through FYM; T8-25% RDN through urea 75% RDN through vermicompost; T9-100% RDN through urea + Azotobacter; T10-100% RDN through FYM + Azotobacter; T11-100% RDN through vermicompost + Azotobacter; T12-50% RDN through urea+ 50% RDN through FYM + Azotobacter; T13-50% RDN through urea+ 50% RDN through vermicompost + Azotobacter; T14-25% RDN through urea+ 75% RDN through FYM + Azotobacter; T15-25% RDN through urea+ 75% RDN through vermicompost + Azotobacter; T16- Azotobacter. Treatment T9, 100% nitrogen nutrition through chemical fertilizer (urea) with seed treatment of Azotobacter has taken significantly maximum days to emergence (5.3). Days taken to 50% spike emergence (94.7) and days taken to maturity (148.0) respectively. Similarly T9 had significantly higher grain yield (5640 kg/ha), hectoliter weight (83.167 kg/ha), grain appearance score (7.933 scale/10) and protein content (12.90 %) of wheat during the research period respectively. View Article DOI: 10.47856/ijaast.2021.v08i12.00