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model-uncertainties
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Patient-Robot-therapist collaboration using resistive impedance controlled tele-robotic systems subjected to time delays
, Article Journal of Mechanisms and Robotics ; Volume 10, Issue 6 , 2018 ; 19424302 (ISSN) ; Salarieh, H ; Behzadipour, S ; Tavakoli, M ; Sharif University of Technology
Abstract
In this paper, an approach to physical collaboration between a patient and a therapist is proposed using a bilateral impedance control strategy developed for delayed tele-robotic systems. The patient performs a tele-rehabilitation task in a resistive virtual environment with the help of online assistive forces from the therapist being provided through teleoperation. Using this strategy, the patient's involuntary hand tremors can be filtered out and the effort of severely impaired patients can be amplified in order to facilitate their early engagement in physical tasks. The response of the first desired impedance model is tracked by the master robot (interacting with the patient), and the...
Probabilistic hierarchical bayesian framework for time-domain model updating and robust predictions
, Article Mechanical Systems and Signal Processing ; 2018 ; 08883270 (ISSN) ; Papadimitriou, C ; Katafygiotis, L. S ; Sharif University of Technology
Abstract
A new time-domain hierarchical Bayesian framework is proposed to improve the performance of Bayesian methods in terms of reliability and robustness of estimates particularly for uncertainty quantification and propagation in structural dynamics. The proposed framework provides a reliable approach to account for the variability of the inference results observed when using different data sets. The proposed formulation is compared with a state-of-the-art Bayesian approach using numerical and experimental examples. The results indicate that the hierarchical Bayesian framework provides a more realistic account of the uncertainties, whereas the non-hierarchical Bayesian approach severely...
Adaptive robust control of fractional-order swarm systems in the presence of model uncertainties and external disturbances
, Article IET Control Theory and Applications ; Volume 12, Issue 7 , 2018 , Pages 961-969 ; 17518644 (ISSN) ; Tavazoei, M. S ; Sharif University of Technology
Institution of Engineering and Technology
2018
Abstract
This study investigates the asymptotic swarm stabilisation of fractional-order swarm systems in the presence of two different kinds of model uncertainties and external disturbances while the upper bound of the uncertainties is a linear function of pseudo-states norms with unknown coefficients. To this end, first a fractional-integral sliding manifold is constructed and then an adaptive-robust sliding mode controller is designed to guarantee the asymptotic swarm stability in a fractional-order linear time-invariant swarm system. The stability analysis of the proposed control system is done based on the Lyapunov stability theorem. Using the proposed controller, the coefficients of the upper...
Robust-fuzzy model for supplier selection under uncertainty: an application to the automobile industry
, Article Scientia Iranica ; Volume 25, Issue 4 , 2018 , Pages 2297-2311 ; 10263098 (ISSN) ; Modarres, M ; Azar, A ; Sharif University of Technology
Sharif University of Technology
2018
Abstract
This paper proposes an innovative robust-fuzzy method for multi-objective, multi-period supplier selection problem under multiple uncertainties. This approach integrates robust optimization and fuzzy programming. Uncertain parameters are modeled as random variables that take value within a symmetrical interval. However, due to the complexity or ambiguity of some real world problems and especially the nature of some of the available input data, the length of interval is also highly uncertain. This ambiguity motivated us to present a new approach, which could be applicable to multiple uncertainties conditions. Thus, in our approach, the half-length of these intervals is also represented by...
Smooth residual generation for robust isolation of faults in manipulators using joint torque sensors
, Article 58th IEEE Conference on Decision and Control, CDC 2019, 11 December 2019 through 13 December 2019 ; Volume 2019-December , 2019 , Pages 2922-2927 ; 07431546 (ISSN); 9781728113982 (ISBN) ; Namvar, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
Reliability of model-based failure detection and isolation (FDI) methods depends on the amount of uncertainty in a system model. Recently, it has been shown that the use of joint torque sensing results in a simplified manipulator model that excludes hardly identifiable link dynamics and other nonlinearities. We present a geometric approach to fault detection and isolation (FDI) for robotic manipulators using joint torque sensor in presence of model uncertainty. A systematic procedure is introduced for representing a robotic system model using joint torque sensor being affine with respect to faults and disturbances. The proposed FDI filter has smooth dynamics with freely selectable functions...
Probabilistic hierarchical bayesian framework for time-domain model updating and robust predictions
, Article Mechanical Systems and Signal Processing ; Volume 123 , 2019 , Pages 648-673 ; 08883270 (ISSN) ; Papadimitriou, C ; Katafygiotis, L. S ; Sharif University of Technology
Academic Press
2019
Abstract
A new time-domain hierarchical Bayesian framework is proposed to improve the performance of Bayesian methods in terms of reliability and robustness of estimates particularly for uncertainty quantification and propagation in structural dynamics. The proposed framework provides a reliable approach to account for the variability of the inference results observed when using different data sets. The proposed formulation is compared with a state-of-the-art Bayesian approach using numerical and experimental examples. The results indicate that the hierarchical Bayesian framework provides a more realistic account of the uncertainties, whereas the non-hierarchical Bayesian approach severely...
Using sliding mode control to adjust drum level of a boiler unit with time varying parameters
, Article ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis ; Vol. 5 , 2010 , pp. 29-33 ; ISBN: 9780791849194 ; Bakhtiari-Nejad, F ; Saffar-Avval, M ; Alasty, A ; Sharif University of Technology
Abstract
Stable control of water level of drum is of great importance for economic operation of power plant steam generator systems. In this paper, a linear model of the boiler unit with time varying parameters is used for simulation. Two transfer functions between drum water level (output variable) and feed-water and steam mass rates (input variables) are considered. Variation of model parameters may be arisen from disturbances affecting water level of drum, model uncertainties and parameter mismatch due to the variant operating conditions. To achieve a perfect tracking of the desired drum water level, two sliding mode controllers are designed separately. Results show that the designed controllers...
Design of a robust model predictive controller with reduced computational complexity
, Article ISA Transactions ; Volume 53, Issue 6 , 1 November , 2014 , Pages 1754-1759 ; ISSN: 00190578 ; Haeri, M ; Sharif University of Technology
Abstract
The practicality of robust model predictive control of systems with model uncertainties depends on the time consumed for solving a defined optimization problem. This paper presents a method for the computational complexity reduction in a robust model predictive control. First a scaled state vector is defined such that the objective function contours in the defined optimization problem become vertical or horizontal ellipses or circles, and then the control input is determined at each sampling time as a state feedback that minimizes the infinite horizon objective function by solving some linear matrix inequalities. The simulation results show that the number of iterations to solve the problem...
Sensorless control of PMSMs with tolerance for delays and stator resistance uncertainties
, Article IEEE Transactions on Power Electronics ; Volume 28, Issue 3 , 2013 , Pages 1391-1399 ; 08858993 (ISSN) ; Tahami, F ; Sharif University of Technology
2013
Abstract
Position sensorless control of ac machines at zero and low speed is possible using high-frequency carrier injection methods. These methods utilize anisotropic properties of rotor. Therefore, they may lose their efficiency for nonsalient machines or machines with small rotor saliency. In these machines, measurement noise and offset, existing delays, as well as model uncertainties may lead to inaccurate estimation of rotor position. Stator resistance which is usually neglected in these methods may also lead to a considerable error especially in machines with small rotor saliency. In this paper, a new position estimation method is presented, and it is shown that in comparison to conventional...
Model reference adaptive impedance control of rehabilitation robots in operational space
, Article Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, 24 June 2012 through 27 June 2012 ; June , 2012 , Pages 1698-1703 ; 21551774 (ISSN) ; 9781457711992 (ISBN) ; Behzadipour, S ; Vossoughi, G. R ; Sharif University of Technology
2012
Abstract
A new nonlinear model reference adaptive impedance controller is presented for the control of robot manipulators with uncertainties in model parameters such as friction coefficients. This method provides asymptotic tracking of a reference impedance model for the robot end-effector in operational space which is more sensible for the patient compared to the joint space impedance used in previous works. The model uncertainties such as friction coefficients are compensated using an adaptation law. The asymptotic tracking of the reference impedance model is shown using a Lyapunov function. The tracking performance and friction compensation are also demonstrated through simulation on a...
A novel robust decentralized adaptive fuzzy control for swarm formation of multiagent systems
, Article IEEE Transactions on Industrial Electronics ; Volume 59, Issue 8 , 2012 , Pages 3124-3134 ; 02780046 (ISSN) ; Shabaninia, F ; Nemati, A ; Stan, S. D ; Sharif University of Technology
IEEE
2012
Abstract
In this paper, a novel decentralized adaptive control scheme for multiagent formation control is proposed based on an integration of artificial potential functions with robust control techniques. Fully actuated mobile agents with partially unknown models are considered, where an adaptive fuzzy logic system is used to approximate the unknown system dynamics. The robust performance criterion is used to attenuate the adaptive fuzzy approximation error and external disturbances to a prescribed level. The advantages of the proposed controller can be listed as robustness to input nonlinearity, external disturbances, and model uncertainties, and applicability on a large diversity of autonomous...
Comprehensive fuzzy multi-objective multi-product multi-site aggregate production planning decisions in a supply chain under uncertainty
, Article Applied Soft Computing Journal ; Volume 37 , 2015 , Pages 585-607 ; 15684946 (ISSN) ; Mahdavi, I ; Tavakkoli-Moghaddam, R ; Mahdavi Amiri, N ; Sharif University of Technology
Elsevier Ltd
2015
Abstract
The main focus of this paper is to develop a model considering some significant aspects of real-world supply chain production planning approved by industries. To do so, we consider a supply chain (SC) model, which contains multiple suppliers, multiple manufactures and multiple customers. This model is formulated as a fuzzy multi objective mixed-integer nonlinear programming (FMOMINLP) to address a comprehensive multi-site, multi-period and multi-product aggregate production planning (APP) problem under uncertainty. Four conflicting objectives are considered in the presented model simultaneously, which are (i) to minimize the total cost of the SC (production costs, workforce wage,...
Using sliding mode control to adjust drum level of a boiler unit with time varying parameters
, Article ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis, ESDA2010, 12 July 2010 through 14 July 2010, Istanbul ; Volume 5 , 2010 , Pages 29-33 ; 9780791849194 (ISBN) ; Bakhtiari Nejad, F ; Saffar Avval, M ; Alasty, A
2010
Abstract
Stable control of water level of drum is of great importance for economic operation of power plant steam generator systems. In this paper, a linear model of the boiler unit with time varying parameters is used for simulation. Two transfer functions between drum water level (output variable) and feed-water and steam mass rates (input variables) are considered. Variation of model parameters may be arisen from disturbances affecting water level of drum, model uncertainties and parameter mismatch due to the variant operating conditions. To achieve a perfect tracking of the desired drum water level, two sliding mode controllers are designed separately. Results show that the designed controllers...
Design of an RMPC with a time-varying terminal constraint set for tracking problem
, Article International Journal of Robust and Nonlinear Control ; Volume 26, Issue 12 , 2016 , Pages 2623-2642 ; 10498923 (ISSN) ; Haeri, M ; Sharif University of Technology
John Wiley and Sons Ltd
2016
Abstract
This paper presents a robust model predictive control algorithm with a time-varying terminal constraint set for systems with model uncertainty and input constraints. In this algorithm, the nonlinear system is approximated by a linear model where the approximation error is considered as an unstructured uncertainty that can be represented by a Lipschitz nonlinear function. A continuum of terminal constraint sets is constructed off-line, and robust stability is achieved on-line by using a variable control horizon. This approach significantly reduces the computational complexity. The proposed robust model predictive controller with a terminal constraint set is used in tracking set-points for...
A comprehensive review on uncertainty modeling techniques in power system studies
, Article Renewable and Sustainable Energy Reviews ; Volume 57 , 2016 , Pages 1077-1089 ; 13640321 (ISSN) ; Hajebrahimi, A ; Fotuhi Firuzabad, M ; Sharif University of Technology
Elsevier Ltd
Abstract
As a direct consequence of power systems restructuring on one hand and unprecedented renewable energy utilization on the other, the uncertainties of power systems are getting more and more attention. This fact intensifies the difficulty of decision making in the power system context; therefore, the uncertainty analysis of the system performance seems necessary. Generally, uncertainties in any engineering system study can be represented probabilistically or possibilistically. When sufficient historical data of the system variables is not available, a probability density function (PDF) might not be defined, they must be represented in another manner i.e. using possibilistic theory. When some...
Fuzzy dynamic thermal rating of transmission lines
, Article IEEE Transactions on Power Delivery ; Volume 27, Issue 4 , 2012 , Pages 1885-1892 ; 08858977 (ISSN) ; Fotuhi Firuzabad, M ; Aminifar, F ; Sharif University of Technology
Abstract
Dynamic thermal rating (DTR) of transmission system facilities is a way to maximally realize the equipment capacities while not threatening their health. With regards to transmission lines, the allowable current of conductors is forecasted based on the environmental situations expected in some forthcoming time periods. Due to the fact that weather conditions continuously vary, sampling points are very limited against many line spans, and the measurements have an inherent error, uncertainties must be appropriately included in the DTR determination. This paper adopts the fuzzy theory as a strong and simple tool to model uncertainties in the DTR calculation. Since DTR intends to determine the...
Zero-gravity emulation of satellites in present of uncalibrated sensors and model uncertainties
, Article Proceedings of the IEEE International Conference on Control Applications, 8 July 2009 through 10 July 2009, Saint Petersburg ; 2009 , Pages 1063-1068 ; 9781424446025 (ISBN) ; Namvar, M ; Sharif University of Technology
Abstract
Recently, an alternative to the standard passive zero gravity emulation testbeds is developed which uses robotic technology. It is comprised of a manipulator whose end-effector rigidly grasps a satellite mock up, a six-axis force/moment (F/M) sensor placed at the interface of the satellite and the manipulator, and a control system. Despite significant advantages of the approach there exist practical problems such as the existence of uncertainty in the robot dynamic model as well as uncalibrated force/moment sensor measurements. In this paper, new adaptive methods based on the Lyapunov theory are proposed to deal with the model uncertainty and imperfect sensor measurements. Simulations which...
Nonlinear adaptive control method for treatment of uncertain hepatitis B virus infection
, Article Biomedical Signal Processing and Control ; Volume 38 , 2017 , Pages 174-181 ; 17468094 (ISSN) ; Sharifi, M ; Tashakori, S ; Zohoor, H ; Sharif University of Technology
Abstract
In this paper, a nonlinear adaptive control method is presented for the treatment of the Hepatitis B Virus (HBV) infection. Nonlinear dynamics of the HBV, modeling uncertainties and three state variables (the numbers of uninfected and infected cells and free viruses) are taken into account. The proposed control law is designed for the antiviral drug input such that the number of free viruses and consequently the number of infected cells decrease to the desired values. An adaptation law is also presented to overcome modeling uncertainties by updating estimations of the system parameters during the treatment period. The stability of the process and convergence to desired state values are...
Adaptive model predictive control-based attitude and trajectory tracking of a VTOL aircraft
, Article IET Control Theory and Applications ; Volume 12, Issue 15 , 2018 , Pages 2031-2042 ; 17518644 (ISSN) ; Rezaeizadeh, A ; Sharif University of Technology
Institution of Engineering and Technology
2018
Abstract
A novel adaptive model-based predictive controller for attitude and trajectory tracking of a vertical take-off and landing(VTOL) aircraft in the simultaneous presence of model uncertainties and external disturbances is introduced in this study. Animportant challenge of designing the model-based controllers is developing an accurate model, especially in the presence ofmodel uncertainties. In this study, first, the nominal model of a ducted-fan air vehicle, which is a multi-input multi-outputnonlinear system with non-minimum phase behaviour, is given as the test case of this research. After that, two modified robustand adaptive model predictive controllers are proposed for tracking a...
In-flight estimation of time-varying aircraft center of gravity position based on kinematics approach
, Article Journal of Aircraft ; Volume 55, Issue 5 , 2018 , Pages 2037-2049 ; 00218669 (ISSN) ; Saghafi, F ; Sharif University of Technology
American Institute of Aeronautics and Astronautics Inc
2018
Abstract
In-flight aircraft center of gravity (COG) position estimation is investigated in this study based on the kinematics approach. The Quad-M basics of system identification requirements are carefully investigated for time-invariant and time-varying COG estimation during airdrop maneuver as a case study that contains both conditions. Modeling and simulation of airdrop maneuver are employed to prepare the required maneuver and measurement data for this investigation. The relative-acceleration equation, as a model structure, and parameter modeling of time-varying COG location and acceleration are introduced into the system identification and parameter estimation framework. The Kalman filter method...