کنترل

Microgrid is a system of generating and distributing electrical energy. Microgrids include various power systems, each of which has different power capacity and produces different oscillations. By producing reliable and flexible power, microgrids can ensure the safety and electrical reliability of the network and reduce energy costs. A microgrid is a small power system with distributed energy sources and loads, which can work in two modes connected to the grid and island. The controller in a microgrid must provide a seamless transition between different modes of operation. By reviewing the studies, the application of microgrids has expanded to respond to the growing energy demand and solve environmental pollution problems. In this paper, a brief overview of the effectiveness of direct current microgrids in the power system has been provided. Direct current microgrids do not need frequency synchronization and reactive power management, and in terms of stability, flexibility, and complexity, they are superior to alternating current microgrids. The source voltages are the variables that control the direct current microgrid power, so they must be well managed to achieve the desired voltage regulation. Various classifications have been stated for microgrids based on control methods, structures, performance, and other parameters. This review can be considered as an initial platform for research study in the development of direct current microgrids based on centralized and intelligent control.

The progress of science and technology in various fields, including the command and control system, has led to the improvement of the combat power of the forces. New systems are able to directly transfer information between components and avoid wasting time in the traditional structure. The current research was carried out with the aim of compiling the cyber command and control architecture in combat and is of an applied-developmental type. The statistical sample of the research is 60 experts and professors in the fields related to command and control and cyber, which were selected by simple random method and Cochran's formula. In this research, information and data have been collected from library sources, questionnaires and interviews. After the information was collected, it was classified and evaluated, and then a descriptive analysis was performed with a qualitative approach. In the quantitative stage, mixed analysis has been done using inferential statistics. The validity and reliability of the tools for collecting information and data have been checked in research using interviews, documents and questionnaires, and methods such as appropriate distribution of questions and comparison of answers have been used to verify the validity and reliability of these tools, and its reliability with the method Cronbach's alpha (0.995) has been obtained. The architecture presented in this research, using the cycle of observation, evaluation, decision and execution in interaction with the 4 dimensions of operations, battle levels, communication networks and technology, emphasizes to improve and upgrade cyber command and control in combat in the face of challenges. A way to enable joint operations between land, defense, naval and air arrays with a single combat formation.

In the training phase of learning algorithms, it is always important to have a suitable training data set. The presence of outliers, noise data, and inappropriate data always affects the performance of existing algorithms. The active learning method (ALM) is one of the powerful tools in soft computing inspired by the computation of the human brain. The operation of this algorithm is completely based on simple calculations and tries to model a Multi-Input Single-Output (MISO) system as a set of Single-Input Single-Output (SISO) subsystems and breaks a complex problem into several simpler problems. Each of the subsystems is then modeled by an Ink Drop Spread (IDS) plane. In this paper, to improve the performance of ALM, with changes in how it works, data called negative data has been used. In the ALM, it is possible to use negative data in the training phase by using the IDS operator. By doing so, a policy similar to the reward and punishment policy is in reinforcement learning methods is used. To investigate the accuracy of the proposed algorithm, some simulations in control have been done on an inverted pendulum system and the FVU value is 0.0143. The simulations results confirm the proper performance and increase the computational power of the proposed method compared to the existing method.

In this paper, a model-free reinforcement learning-based controller is designed to extract a treatment protocol because the design of a model-based controller is complex due to the highly nonlinear dynamics of cancer. The Q-learning algorithm is used to develop an optimal controller for cancer chemotherapy drug dosing. In the Q-learning algorithm, each entry of the Q-table is updated using data from states, action, and reward. The action is the chemo-drug dose. The proposed controller is implemented on a four states mathematical model including immune cells, tumor cells, healthy cells, and chemo-drug concentration in the bloodstream. Three different treatment strategies are proposed for three young, old, and pregnant patients considering his/her age. Chemotherapy is used in all cases.  In the older patient, immunotherapy is also used for modifying the dynamics of cancer by reinforcing his/her weak immune system. A Mamdani fuzzy inference system is designed to limit the maximum chemo-drug dose by regarding the age of the patients. Simulation results show the effectiveness of the proposed treatment strategy. It is also shown that immunotherapy is necessary for finite duration cancer treatment in patients with a weak immune system. The used strategy is a model-free method which is the main advantage of this method.

This paper presents design and implementation of Model Based Predictive Controller (MPC) for a novel Bi-Rotor Moving Mass Controlled (MMC) Unmanned Aerial Vehicle (UAV). Due to the strict constrained control inputs in this type of UAV, it is necessary to take into account the constrained controller design and un-constrained control methods are not applicable. MPC controller which is designed based on the linear model by considering control constraints, is implemented on the nonlinear model of the UAV’s planar motion and compared with LQR controller, the simulation results show significant performance of this controller in control of the UAV while respecting control constraints.

: The Robust Cooperative Output Consensus (RCOC) in continuous time Heterogeneous Multi-Agent Systems with the directed graph is addressed. In the standard solution of the RCOC, the p-copy internal model method is used. This method requires dynamical equations of the agents and the leader. In the present paper, based on the equivalent auxiliary system method, a new auxiliary system is obtained. Then, the RCOC is transformed to a control problem. Moreover, a model-free algorithm is proposed to solve the Robust Algebraic Riccati Equation using the Integral Reinforcement Learning (IRL) method. It is shown that the proposed method satisfies the output regulation equations. A simulation example verifies the effectiveness of the proposed method.

Flight control system is a unit of the air defense and missile system that takes commands prescribed by the guideline law and operates due to the operators embedded in the system. Missile physical system includes nonlinear aerodynamic coefficients and other physical dependent variables, so accurate identification of them is difficult. This issue makes deference between real and mathematic model of missile equations of motion and causes designed linear controller performance degradation. In this paper, inverse dynamic approach is used for uncertainty identifying and mathematic modeling of missile defense system. Then, this model is used for optimizing and controlling the flight of a missile with nonlinear 6 DOF (Degrees of freedom) equations of motion. Thus, the designed controller is a nonlinear fuzzy-adaptive controller which has high adaption and robustness against the parametric changes during missile’s flight. Using the invers dynamic method for modeling motion equations of missile defense is the innovation of this research.

This paper reviews the service quality management control and upgrade as well as the communications and information technology enhancement. The purpose of this research is the control and improvement of the service quality management as well as the enhancement of the parent telecommunications network of I.R.Iran that finally, taking the specific conditions into consideration, the quality management service model of the telecommunications parent network of Iran will precisely be used as the whole in the format of the communications and information technology enhancement model after identifying and specifying the levels of the relationships existing among the models, and the standards of the communications and information technology management. The study shows developing such a model in the industry of ICT with emphasis and establishment in the parent telecommunications network of Iran, benefit of human capital with the latest technology and presenting modern services to the customers, the service quality management will be upgraded and will lead to the improvement in quality management in the field of ICT.

Due to the uniqueness of the production process in each organization, the analysis of this process is also unique. The main issue of this research is to provide a set of coherent routines for designing a production control system that meets the real needs of industries.
In this paper, after providing general information and information on the current state of production control in an industry, a production control system based on coverage of its weaknesses and requirements has been presented. For analyzing the existing situation, modeling tools such as flow diagram, data flow diagram and entity relationship graph are used. A questionnaire based on the main axes of the problem was designed to collect information about the current status of the fieldwork. Based on this, the strengths and weaknesses of the existing system and its system requirements were extracted. The proposed system is presented in the form of various diagrams and executive method. Finally, the database specifications and the design capabilities of the software are mentioned.
The evaluation of the proposed system and the production software shows their superiority to the existing situation through analytical statistics provided in the final section of the article.

The aim of this study was to identify and analyze the factors affecting the performance of integrated network of command and control for overall understanding, explanation, forecasting and efficiency improvement in the integrated network of command and control. The statistical population consisted of 100 expert staff (randomly selected) from Khatam-ol-anbiya Air Defense Base. In this research, 44 indicators were detected exploratively, validity of the questionnaire was verified by the professors and reliability was calculated by Cronbach's alpha of 0.85. Then, by factor analysis, factors were reduced to 16 items and classified into 4 hidden factors, and then ranking of variables was done by Friedman test. It was showed that the integrated operation of command and control network from various factors such as agility, network security, practice and repetition, interactions between systems and systems, status awareness, battle scene simulation, reaction steps, inertial defense systems, doctrine and successful experiences, Common language, system intelligence, power at the edge, network-eccentricity, large-scale data systems, stability and durability, rebuilding and re-structuring structures. In terms of application, data collection, observation method, interviews, questionnaires and documents the current study is based on philosophical foundations in the scope of verifiable paradigm.

Data fusion techniques combine raw data of multiple sources and gather related information to achieve more specific inferences than could be achieved by using a single source. In the fusion research community, JDL is a common model, but it suffers from semantics issues. Using Semantic Web (SW) technologies for the extraction of implicit knowledge is a new approach to overcome this problem. SW technologies purpose to describe and represent the semantics related with data or information in order to facilitate automatic processing, integration, sharing and reuse of the data. So in this paper, a semantic fusion model is proposed based on JDL, which can overcome the semantic problems in heterogeneous systems by using SW technologies including ontology and semantic reasoning. Finally, military scenario is designed and implemented to display the functionality of the proposed model practically. In implementation, Jena framework was utilized for semantic programming to describe ontology and have a semantic reasoner.

As increases the presence of information systems in accomplishing every unit’s mission, the command and control system finds a more highlighted place and the requirements for its implementation have been enlisted in agendas of military organizations. The present paper looks in search of C&C potentials to bring the system in practice. In terms of objectives, the study is descriptive and in terms of use, it is practical in which the questionnaire designed by the researcher is used for the purpose of data collection. The statistical population includes a number of relatable experts and managers selected using categorized random sampling and with reference to Morgan’s chart. For the purpose of data analysis, confirmative factor analysis testing is incorporated resulting that there are six side commanding characteristics: financial, infrastructural and structural features in the control section and human, cultural and information features in the command section, and in the end, fundamental challenges in the development of C&C systems are identified.

Froth flotation is the most widely used technique for the separation of valuable minerals from gangue ones. Changeable nature of feed, interaction of variables and weakness of accurate measurement equipment have made the development of monitoring methods and continues control of flotation circuits to an important issue. Today with the advance of technology, machine vision systems based on image processing methods are considered a rapid, cheap and safe detection device in mineral processing industries. The appearance of flotation froth surface consists of significant information process which easily distinguishes the process operation condition. Size distribution of froth bubbles is the reflection of froth stability and velocity and is the best criterion for the efficiency estimation of flotation operation. This paper is the updated review of the most common methods of size estimation of flotation froth bubbles along with their benefits and shortcomings and ideas for future studies in this area. Likewise, the correlation between concentrate grade and recovery with the froth bubble size is investigated.

Nowadays, due to significant increase in demands of electric motors for residential, commercial and industrial applications, and for optimum consumption of electrical energy, the design and manufacturing of high efficiency motors and related variable speed drives have been regarded by many suppliers. Among several kinds of motors, the brushless DC (BLDC) motor is employed in many applications due to its high efficiency, high power and torque density, and ease in control, simple fabrication, high reliability, and lower maintenance. This motor is similar to PMSM in construction, while is controlled as easy as of DC motor. This paper to help for development and employing BLDC motors, reviews the different aspects of BLDC motors including performance, modeling, employed inverters, assessment of control methods for BLDC motor and implementation of its drive. Advantages and disadvantages of different control methods, remarks on various position sensorless methods, the effectiveness of various minimization schemes for commutation torque ripple, and control of BLDC motor in constant power region or flux-weakening are described in more details. Finally, some practical points are suggested for manufacturing of a commercial BLDC motor drive.

In this paper, a data driven method for fault estimation in control systems is proposed. The fault estimation problem is formulated as a time domain control problem and the H∞ technique is applied for solving it. The mathematical model is assumed to be unknown and only input/output (I/O) data are used for detector design. Minimizing the fault estimation error is considered as the fault detection performance measure. Also, since the estimated fault plays the role of a virtual control input, a cost is defined on it to avoiding the H∞ control problem being singular. These measures are achieved by tuning a scalar parameter and some weighting matrices. An easily implementable design algorithm summarizes the methodology presented in the paper. The proposed algorithm is applied to a numerical example in order to illustrate its effectiveness.

Nowadays, due to significant increase in demands of electric motors for residential, commercial and industrial applications, and for optimum consumption of electrical energy, the design and manufacturing of high efficiency motors and related variable speed drives have been regarded by many suppliers. Among several kinds of motors, the brushless DC (BLDC) motor is employed in many applications due to its high efficiency, high power and torque density, and ease in control, simple fabrication, high reliability, and lower maintenance. This motor is similar to PMSM in construction, while is controlled as easy as of DC motor. This paper to help for development and employing BLDC motors, reviews the different aspects of BLDC motors including performance, modeling, employed inverters, assessment of control methods for BLDC motor and implementation of its drive. Advantages and disadvantages of different control methods, remarks on various position sensorless methods, the effectiveness of various minimization schemes for commutation torque ripple, and control of BLDC motor in constant power region or flux-weakening are described in more details. Finally, some practical points are suggested for manufacturing of a commercial BLDC motor drive.

Cable-driven robots are a class of parallel robots in which the rigid links are replaced by cables. Using cables instead of rigid links in parallel robots makes them a suitable choice to remedy some of the traditional shortcoming of the conventional robots. However، this introduces new challenges in the study of cable-driven robots. This paper presents a survey of cable-driven robots and addresses numerous challenging open problems in this field. The paper consists of an overview of both applications and theoretical issues of cable-driven robots such as workspace، dynamics and control، and furthermore some open challenging issues in this field of research.

In this paper، a method to track the maximum power of solar panels based on fuzzy logic is presented. The proposed method is based on the relationship between radiation intensity and the voltage of maximum power operating point. With this relationship، at any time by measuring the light intensity، voltage can be calculated at the maximum power point by using fuzzy approximation function. In order to verify the proposed method، simulation results are presented.

This paper is concerned with the generation control in small stand-alone MicroGrids consisting of inverter interfaced Distributed Generation (DG) units. An intelligent and on line Microgrid Management System (MGMS) using Artificial Neural Network (ANN) controller is used in this study and it determines the amount of power produced from generation units in a stand-alone MicroGrid. The ANN trained with a data generated from a Genetic Algorithm (GA) solved optimal power flow problem, which defines generation unit’s power in order to have a minimum power loss in the system, considering normal buses voltage and rating of generation units. Simulation results in a typical distribution system consisting two DG units show that the proposed method can meet the requirements of the system and DG units rating in stand alone operations. In this way the system is managed in an on-line, optimal, and reliable situation that guarantee the continuity of power to loads in stand-alone mode of a MicroGrid.