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Estimating model parameters is a crucial step to understand the behavior of biological systems. To perform parameter estimation, a commonly used formulation is the least square method that minimizes the mean squared error. This method finds the model parameters that minimize the sum of the squared error between experimental data and model predictions. However, such a formulation can misguide parameter...
This paper presents a new method for designing the weights used for development of robust controllers for a quadrotor model with parameter uncertainty. The weights alongside the controllers are developed for attitude and altitude tracking by resolving a constrained non-linear minimization problem formulated over the conventional mixed sensitivity optimization S over T method. The optimization routine...
In the field of architecture, 3D printing technology has the advantage of shortening the construction period by continuous addition and installing the desired shape and structure directly on site. However, the conventional 3D printer structure has limitations in practical use because of its versatility, mobility, and limited accessibility. In this study, a 3-axis gantry robot type 3D printing simulator...
A major limitation of mobile Crowd Sourcing (CS) applications is the generation of false (or spam) contributions due to selfish and malicious behaviors of users, or wrong perception of an event. Such false contributions induce loss of revenue through disbursement of undue incentives and also negatively affects the application's operational reliability. In this work, we propose a reputation model,...
In this paper, we propose a straightforward method to select the parameters of the PI controllers in Field Oriented Control (FOC) scheme for Permanent Magnet Synchronous Motor (PMSM) based on geometric model reduction and structured H∞-synthesis. The main contribution of this paper is that, by recognizing the essential linear system structure of PMSM model and using mature robust control method, the...
In this paper, an optimal retail market pricing design for demand response in day-ahead scheduling of smart distribution networks is investigated. Through the well-designed retail market electricity price, the profit of each user is maximized; while the profit of the Distribution Network Operator (DNO) is guaranteed and the risk management model based on the Information Gap Decision Theory (IGDT)...
In this paper, we consider the design problem of a decentralized variable gain robust controller that provides practical tracking for a class of large-scale interconnected systems with mismatched uncertainties. Furthermore, we show that sufficient conditions for the existence of the proposed decentralized variable gain robust controller are reduced to the feasibility of linear matrix inequalities...
This paper presents a design methodology with uncertainty quantification to estimate the required margin for two main design variables in a modular multilevel converter (MMC). In this methodology, the minimum required design margins are calculated by quantifying all sources of uncertainty in the modeling and simulation of MMCs. To this end, an enhanced modeling framework is presented to take into...
This paper deals with a robust input-output feedback linearization control technique for induction motors. The idea arises from the observation that classic feedback linearization suffers primarily from two disadvantages: the accuracy of the dynamic model and the corresponding correct knowledge of the model parameters. To cope with the limit of the feedback linearization control, intrinsically connected...
In conditions of a mass character of higher education, the problems of student identification are relevant because of the differences in the contingent of students in terms of level of training, personal and cognitive characteristics. The learning process is characterized by the presence of uncertainty factors, which requires modeling and control of the application process of methods and tools of...
According to uncertainties of the load and leakage inductance in the output transformer, this paper uses the μ analysis and synthesis method to design a robust controller for the three-phase medium frequency power supply. The controller not only enables the closed-loop system to do the non-static error tracking and to be asymptotic stability, but also is good in robustness and able to suppress the...
This paper presents a self-memory prediction model to mitigate the effects of image based visual servoing (IBVS) system under uncertainty. The performance of IBVS system is easily influenced by different tasks, diverse environments and uncertain disturbances. Through building a self-memory prediction model to keep previous movement tendency in the every current movement, the framework of a self-memory...
A DC/DC boost converter exhibits highly nonlinear properties and subjects to certain uncertainties, like load change, input voltage variation, and parametric uncertainties. This paper first presents an improved accurate model of the converters, including the parasitic elements and model uncertainties, which are usually existed in actual systems but not (or not sufficiently) considered in most of the...
This paper is concerned with the problem of stabilization and tracking for a class of underactuated systems subjected to external disturbances. Based on the mathematical model of a 4 degrees of freedom (4DOF) ball and plate system, a robust backstepping controller with disturbance rejection is developed. The proposed controller is capable of handling bounded uncertainties with unknown periodicity...
This paper presents an adaptive nonsingular terminal sliding mode formation control by means of output recurrent fuzzy wavelet neural networks for a group of networked heterogeneous Mecanum-wheeled omnidirectional robots with uncertainties. The dynamic behavior of each uncertain heterogeneous omnidirectional robot is modelled by a reduced three-input-three-output second-order state equation with uncertainties...
The need to improve the quality of management at minimum costs, the complexity of the structure of the management object, the functions performed by it, leads to an increase in uncertainties that need to be taken into account. The use of fuzzy logic to control pumping equipment will reduce the likelihood of erroneous decisions, which will increase the life of technological equipment.
This paper presents an analyzing on the prediction of a primary signal in cognitive radio networks using a hybrid algorithm based on two parts, know as: an alpha-beta filter and a neyman-pearson (NP) detector. Today, it is important to predict a primary signal in a cluttered environment and especially when the secondary user (SU) is moving. However, the challenges of this contribution are based on...
This paper presents the implementation of a nonlinear robust controller in a boost converter, which operates in an uncertain environment. The proposed controller deals with uncertainties, which are unknown but bounded, and occur in the input voltage and the output pure resistive load. Mathematical proof of the efficiency of the controller and quantitative results about the amount of the uncertainty...
In this paper, we propose a mechanism for cancer cell differentiation therapy based on a game-theoretic rough set model with intuitionistic fuzzy set. We introduce an intuitionistic fuzzy relation with the help of fuzzy compatibility relation. The approximation space classification is controlled with a pair of intuitionistic fuzzy thresholds. It provides a flexibility to set up tolerance level depending...
The ability to conduct fast and reliable simulations of dynamic systems is of special interest to many fields of operations. Such simulations can be very complex and, to be thorough, involve millions of variables, making it prohibitive in CPU time to run repeatedly for many different configurations. Reduced-Order Modeling (ROM) provides a concrete way to handle such complex simulations using a realistic...
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