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In this paper, we develop an optimal control strategy on inventory systems with uncertain demand. To deal with these uncertainties we use a synthesis of robust model predictive control with linear matrix inequalities. The goal is to minimize the difference between the prediction and the reference trajectory subject to the objective function of each period, based on the input and output constraints. Using standard techniques, the optimization problem that minimizes the difference between the prediction and the reference trajectory, is reduced to a convex optimization problem involving linear matrix inequalities (LMIs). We provide numerical simulations on this system using MATLAB and then observe how robust predictive control models produce optimized strategy at the inventory level. In the simulation results, robust predictive control models provide an optimal strategy for controlling inventory levels with minimum total cost and inventory levels following inventory levels on issues.

This paper describes flying multi-vehicle control strategies and its benefit for saving fuel. Exposition starts from inspiration of flying multi-vehicle in daily life. Furthermore, from model of single flying vehicle, we construct the model of multi-vehicle and cost functional model that describe the state of the cost to be met the flying vehicle. The flying multi-vehicle control designed with optimal control strategy. The design of optimal control is done through the Pontryagin Maximum Principle, brings the model to a system of equations consisting of state equations and costate equations. In the system of states equations, each having initial and final condition, in the costate equations system has no requirements at all. The next problem is converted to the initial value problem and search for the approximate initial condition equation of costate equations system which has no requirements using a modified method of steepest descent. Thus, the control of multi-vehicle successfully performed and the simulation results presented on the results and discussion section. In addition, we also calcute the fuel which used by multi-vehicle, compared by the fuel which used by each vehicle in solo flying. The result can be conclude that the fuel more efficient if the flying vehicles in formation flying.

<span lang="EN-US">The fuzzy time series (FTS) is a forecasting model based on linguistic values. This forecasting method was developed in recent years after the existing ones were insufficiently accurate. Furthermore, this research modified the accuracy of existing methods for determining and the partitioning universe of discourse, fuzzy logic relationship (FLR), and variation historical data using intervals ratio, cross association relationship, and rubber production Indonesia data, respectively. The modified steps start with the intervals ratio to partition the determined universe discourse. Then the triangular fuzzy sets were built, allowing fuzzification. After this, the FLR are built based on the cross-association relationship, leading to defuzzification. The average forecasting error rate (AFER) was used to compare the modified results and the existing methods. Additionally, the simulations were conducted using rubber production Indonesia data from 2000-2020. With an AFER result of 4.77%&lt;10%, the modification accuracy has a smaller error than previous methods, indicating very good forecasting criteria. In addition, the coefficient values of </span><em><span lang="EN-US">D₁</span></em><span lang="EN-US"> and </span><em><span lang="EN-US">D₂</span></em><span lang="EN-US"> were automatically obtained from the intervals ratio algorithm. The future works modified the partitioning of the universe of discourse using frequency density to eliminate unused partition intervals.</span>

The majority of an immune system infected by HIV (Human Immunodeficiency Virus) is CD4 + T cells. The HIV-1 transmission through cell to cell of CD4 + T cells supports the productive infection. On the other hand, infected CD4 + T cells stimulate cytotoxic T-lymphocytes cells to control HIV-1 infection. We develop and analyze a mathematical model incorporating the infection process through cell to cell contact of CD4 + T cells, CTL compartment and the combination of RTI and PI treatments. By means of the alternative reproduction ratio, it is analyzed the stability criteria and the existence of endemic equilibrium. Numerical simulations are presented to study the implication of the combination of RTI and PI therapy. The results indicate that RTI drug shows more significant effect in reducing HIV-1 infection compared to PI drug.