Journal of Applied Dynamic Systems and Control
Volume:4 Issue: 2, Summer and Autumn 2021

Biomass is considered as an effective energy carrier to meet the needs of clean energy for the whole world, which need to have sustainable renewable energy. Among the various methods of biomass, gasification is commendable. It is considered as one of the most important restoration and thermochemical methods for converting biomass energy into gaseous fuels, thermal and electrical energies, as well as its use for the production of biofuels. But there are some obstacles, which can be solve by more research in this area. In this article, various obstacles such as supply chain management include harvesting the waste, collection on the site, transportation to gasification site and storage are each a part of this chain. biomass pretreatment, generic low biomass resources and syngas conditioning from biomass energy conversion have been mentioned. Based on recent studies, the biggest challenges for biomass gasification is to produce heat and power. Also, different technologies of reactor design until reaching to the most efficient and high-efficiency reactor have been discussed in this paper. Ultimately, the most advanced gasification system with the most efficient gas conditioning technology can overcome all the mentioned obstacles.

In this paper we treat the problem of cancer control by chemotherapy, through general model in ordinary differential equation form of tumor dynamics. The model is augmented by an ordinary linear differential equation of chemotherapy drugs, and the control problem is reset in the framework of the viability theory. Set-valued analysis method is applied to design procedures leading to the formulation of treatment protocols, which are single-valued selections of set-valued maps, and divide in two categories according to the advancement of initial state cancer, which is characterized by specific set-valued map, upon the strict negativity of the dynamic tumor function at the initial state. Protocols corresponding to non-advanced stage cancer, ensures the decreasing of tumor cells, unlike the ones of advanced stage. Logistic model is considered from the literature to illustrate effects of feedback protocols, by which tumor cells is controlled to be on exponentially decreasing all over chemotherapy horizon, under normalized carrying capacity to reach infinitesimal values.

Iran is located between the orbits of 25 to 40 degrees north latitude and is located in a region that is among the highest in terms of solar energy among the parts of the world. The amount of solar radiation in Iran is estimated between 1800 to 2200 kWh per square meter per year, which is higher than the global average. In Iran, on average, more than 300 sunny days are reported annually, which is very significant. This energy can be used in different ways, such as electricity generation, heating and cooling, fresh water production, hot water supply, etc. In this paper, using T*SOL software, a solar heating system (including solar water heater, space heating) has been designed for laboratory complex No. 3 of Islamic Azad University, Ahvaz Branch and has been simulated for different time periods such as annually.

The Operational Trans- conductance Amplifier (OTA)is a main building block in several analog signal and mixed- signal integrated circuits. This paper, a novel low power Class- AB CMOS Operational trans- conductance amplifier (OTA) with High gain and high slew rate is presented. The proposed two-stage OTA, the characteristics of class-AB are applied in both of the stages. The Use of active loads for the first stage provides the effective trans-conductance boosting and increased,DC-gain product. The nonlinear current mirrors boost the current of the second stage leading to the increase of the slew rate. The OTA canbe employed in low- voltage low- power circuits requiring a good performance/power tradeoff.Theoretical analysis and Cadence simulations prove the performance of the new OTA. The simulation results indicate that the DC gain is improved by abot 13db.The UGBW and phase margin of the proposed OTA are 305 MHZ and 65º ,respectively.

In this study, artificial neural networks, artificial neural network combination with genetic algorithm and neural network combination with Kalman filter were used to optimally model and control a real air conditioning system. Using the above methods, the system is first trained and after verifying the modeling accuracy, the capability of this modeling to predict the future conditions of the system is investigated. In addition to the subsystems investigated in both heating and cooling phases by mass and energy equations in Simulink simulated by Matlab software, the results of this section are finally compared with the optimal modeling results. The most important advantage of artificial neural network modeling over mass and energy equation modeling approaches is that it captures all the uncertainties and nonlinear properties of the air conditioning system due to the use of real data for modeling. It takes. Therefore, this method can optimize energy consumption in air conditioners by predicting the future conditions of the system and by precisely adjusting the time of turning on and off the main energy consuming equipment. The most important achievement of this research is more accurate and realistic modeling of the nonlinear air conditioning system.Comparing the methods used in the research for simulation methods using mass and energy equations, modeling using Bayesian trained neural network, artificial neural network modeling using MLP, modeling using neural network and genetic algorithm, modeling Using neural network and Kalman filter, the square error is equal to 0.006, 0.18, 0.056, 0.1456 and more than 0.5, respectively.

The use of renewable resources in the power system is increasing day by day. Wind energy is one of the forms of renewable energy sources that has been widely available to humans due to the common nature of renewable energy with low concentration (low density). Due to the constant changes of wind and as a result of changes in the power produced by wind farms, uncertainty in the power of the power system will become an integral part. Now, if the permeability of these resources increases, they can directly affect the dynamic stability of the system and the margin of stability of the system will change in power systems expansion, instability was often due to a lack of synchronizing torque. Issues such as the small perturbation stability of local oscillation modes and low-frequency inter-zone oscillation modes became apparent with a significant improvement in power system performance. The paper presents an optimal and coordinated power oscillation damper based on a wind turbine and power system stabilizer (PSS) to maintain the stability of power system and damp inter-area oscillations. The optimal and coordinated design of the PSS located at the generator site and the damper installed in the control section of the doubly-fed induction generator (DFIG) is defined as an optimization problem.

In this paper, an observer based sliding mode method is used to control the heart rhythm system. For this purpose, nonlinear and uncertain dynamics of a sick human heart are considered. The output of the three main parts of the heart is assumed to be the output of the controlled system and the electrical signal applied to the three main parts of the heart is also considered as the input vector. Hence the controller is designed using the MIMO sliding mode method. The control signals applied to the three points of the heart are determined in such a way that the electrocardiogram signal behaves desirable. An observer is also used to estimate unmeasurable state variables and uncertain functions of the heart. Continuous approximation method has been used to produce smooth control signals and remove chattering. The simulation results show the good performance of the proposed control system to control the heart rate behavior of a person with tachycardia disease.

This paper was dealt with the optimization of energy for tracking the magnetic levitation ball by using the technique of State-Dependent Riccati Equation. The magnetic levitation ball is widely used in various fields. This system includes a steel ball suspended by electromagnetic force. The differential equations of this system are nonlinear. Generally, first, these nonlinear equations are linearized around an equilibrium point. Then, a Linear Quadratic Tracker controller is designed for this system. Note that this system has a non-zero equilibrium point. However, in the technique of State-Dependent Riccati Equation, the nonlinear equations are linearized by using the method of State-Dependent Coefficients. If the system is pointwise stabilizable and detectable, the State-Dependent Riccati Equation has an answer. Then, an optimal control law is extracted so that the energy of tracking is minimized. In the end, it has been shown that four different trajectories are tracked appropriately using the proposed method.

In this paper, three methods of nonparametric fuzzy regression with crisp input and asymmetric trapezoidal fuzzy output, are compared. It analyzes the three nonparametric techniques in statistics, namely local linear smoothing (L-L-S), K- nearest neighbor Smoothing (K-NN) and kernel smoothing (K-S) with trapezoidal fuzzy data to obtain the best smoothing parameters. In addition, it makes an analysis on three real-world datasets and calculates the goodness of fit to illustrate the application of the proposed method.In this paper, we propose to analyze the three nonparametric regression techniques in statistical regression, namely local linear smoothing (L-L-S), the K- nearest neighbor smoothing (K-NN) and the kernel smoothing techniques (K-S) with trapezoidal fuzzy data.This article is organized as follows: In section 2, we have some preliminaries about fuzzy nonparametric regression and trapezoidal fuzzy data. In section 3, smoothing methods for trapezoidal fuzzy numbers are proposed and in section 4, two numerical examples are solved.

In this article, to reduce energy consumption and manage its consumption in smart residential buildings, considering the convenience of people, a set of rules for determining intelligent temperature has been selected. For this purpose, expert rules and questionnaires have been prepared and used to make the indoor temperature intelligent based on individuals' emotional components, including clothing, outdoor temperature, age, body mass index, humidity, and the number of inhabitants. For this purpose, the ideal temperature under normal conditions of 22 degrees Celsius is considered by existing standards. The standard for determining the thermal indexes of PMV4 and PPD5 is used to validate the rules, and the result is acceptable compliance of these rules with the existing standard. According to the intervals set for the characteristics used, 1215 rules are defined for this system. A dashboard has been prepared in Excel software to adjust the temperature according to the existing rules, which is displayed as output by entering each available data based on qualitative and quantitative amounts of appropriate temperature. To evaluate the energy consumption, the two modes of temperature regulation with intelligent systems and manual temperature regulation have been compared. Results. For example, manually adjusting the temperature in 12 to 18 hours is a constant consumption pattern. By adjusting the temperature of the expert system per second, the consumption pattern changes based on residents’ satisfy.

This paper explores the inherent characteristics of multigrounded three-phase four-wire distribution systems under unbalanced situations. As a result, the mechanism of profile voltage in MGN feeders becomes difficult to understand. The simulation tool that been used for this paper is Matlab under Windows platform. In this paper the equivalent model of a full-scale multi-grounded distribution system implemented by Matlab is introduced. The results are expected to help utility engineers to understand the impact of MGN on distribution system operations.This paper explores the inherent characteristics of multigrounded three-phase four-wire distribution systems under unbalanced situations. As a result, the mechanism of profile voltage in MGN feeders becomes difficult to understand. The simulation tool that been used for this paper is Matlab under Windows platform. In this paper the equivalent model of a full-scale multi-grounded distribution system implemented by Matlab is introduced. The results are expected to help utility engineers to understand the impact of MGN on distribution system operations.

In this paper, the speed control of a permanent magnet synchronous motor is performed in a desired finite time. Due to the nonlinearity of the dynamics of this type of motors and the form of the state equations, a back-stepping strategy has been chosen to design the control system. In the proposed method, in each design step, the finite time stability condition is used, so the nonlinear controller has the ability to guarantee finite time convergence of output tracking error. The finite time stability of the proposed control method is proved based on Lyapunov theory. Adjusting the convergence time of system outputs can be done by changing the gain of the controllers. Furthermore, the proposed controller generates smooth control signal that can be implemented. The simulation results show that the proposed method is able to control the speed and current of a permanent magnet synchronous motor in desired finite time.