ORCID Profile
0000-0001-9429-7164
Current Organisations
University of Luxembourg
,
Curtin University
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Publisher: Springer Science and Business Media LLC
Date: 20-04-2017
Publisher: Elsevier BV
Date: 2018
Publisher: Springer Science and Business Media LLC
Date: 07-08-2013
Publisher: IEEE
Date: 12-2017
Publisher: ASME International
Date: 18-02-2022
DOI: 10.1115/1.4053159
Abstract: This paper proposed a systematic framework to automatically design and fabricate optimized soft robotic fingers. The soft finger is composed of a soft silicone structure with inner air chambers and a harder outer layer, which are fabricated by molding process and 3D printing, respectively. The softer layer is utilized for actuation while the supportive hard structure is used to impose constraints. The framework applies a topology optimization approach based on rational approximation of material properties (RAMP) method to obtain an optimal design of the outer layer of the soft fingers. Two basic motion primitives (bending and twisting) of the soft finger were explored. A multi-segmented soft bending finger and a soft twisting finger were designed and fabricated through the proposed framework. This work also explored the combination of bending and twisting primitives by developing a combined bending-twisting soft finger. The soft fingers were characterized by free and blocked movement tests. The experiments showed that the triple-segmented soft finger can achieve a maximum of 50.5 deg no-load bending under the actuation pressure of 53 kPa. The blocked movement test on the multi-segmented soft actuating finger showed that this finger could generate up to a maximum of 0.63 N force under 57 kPa actuation pressure in 7 s of inflating time. The developed twisting soft finger was shown to achieve tip rotation of up to 219 deg under 29 kPa actuation pressure. Finally, the potential capability of the bending-twisting soft fingers was verified through applications like screwing and object grasping.
Publisher: Wiley
Date: 20-02-2019
DOI: 10.1002/ASJC.2066
Publisher: Springer Berlin Heidelberg
Date: 2008
Publisher: Elsevier BV
Date: 05-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: Informa UK Limited
Date: 02-10-2014
Publisher: Springer Science and Business Media LLC
Date: 08-01-2013
Publisher: Elsevier BV
Date: 05-2018
Publisher: ASMEDC
Date: 2009
Abstract: Finding optimal trajectory is critical in several applications for robots from payload transport between two given states in a prescribed time such that a cost functional is minimized. This paper is concerned with the path planning of flexible robotic arms in point-to-point motion, based on indirect solution of optimal control problem. Dynamic modelling technique based on the combined Euler–Lagrange formulation and assumed modes method is applied, then by implementing the Pontryagin’s minimum principle necessary conditions for optimality are derived. Nonlinear states and control constraints are treated without any simplifications or transforming them into sequences of systems with linear equations. By these means, the modelling of the complete optimal control problem and the accompanying boundary value problem is automated to a great extent. Finally, the performance of method is illustrated through the computer simulations.
Publisher: Springer Science and Business Media LLC
Date: 17-05-2011
Publisher: SAGE Publications
Date: 2012
DOI: 10.5772/50308
Abstract: In this work, a computational algorithm is developed for the smooth-jerk optimal path planning of tricycle wheeled mobile manipulators in an obstructed environment. Due to a centred orientable wheel, the tricycle mobile manipulator exhibits more steerability and manoeuvrability over traditional mobile manipulators, especially in the presence of environmental obstacles. This paper presents a general formulation based on the combination of the potential field method and optimal control theory in order to plan the smooth point-to-point path of the tricycle mobile manipulators. The nonholonomic constraints of the tricycle mobile base are taken into account in the dynamic formulation of the system and then the optimality conditions are derived considering jerk restrictions and obstacle avoidance. Furthermore, by means of the potential field method, a new formulation of a repulsive potential function is proposed for collision avoidance between any obstacle and each part of the mobile manipulator. In addition, to ensure the accurate placement of the end effector on the target point an attractive potential function is applied to the optimal control formulation. Next, a mixed analytical-numerical algorithm is proposed to generate the point-to-point optimal path. Finally, the proposed method is verified by a number of simulations on a two-link tricycle manipulator.
Publisher: Elsevier BV
Date: 07-2012
Publisher: SAGE Publications
Date: 2011
DOI: 10.5772/10524
Abstract: Finding optimal trajectory is critical in several applications of robot manipulators. This paper is applied the open-loop optimal control approach for generating the optimal trajectory of the flexible mobile manipulators in point-to-point motion. This method is based on the Pontryagin's minimum principle that by providing a two-point boundary value problem is solved the problem. This problem is known to be complex in particular when combined motion of the base and manipulator, nonholonomic constraint of the base and highly non-linear and complicated dynamic equations as a result of flexible nature of links are taken into account. The study emphasizes on modeling of the complete optimal control problem by remaining all nonlinear state and costate variables as well as control constraints. In this method, designer can compromise between different objectives by considering the proper penalty matrices and it yields to choose the proper trajectory among the various paths. The effectiveness and capability of the proposed approach are demonstrated through simulation studies. Finally, to verify the proposed method, the simulation results obtained from the model are compared with the results of those available in the literature.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: MDPI AG
Date: 10-12-2019
DOI: 10.3390/EN12244712
Abstract: This paper presents a novel adaptive fault-tolerant neural-based control design for wind turbines with an unknown dynamic and unknown wind speed. By utilizing the barrier Lyapunov function in the analysis of the Lyapunov direct method, the constrained behavior of the system is provided in which the rotor speed, its variation, and generated power remain in the desired bounds. In addition, input saturation is also considered in terms of smooth pitch actuator bounding. Furthermore, by utilizing a Nussbaum-type function in designing the control algorithm, the unpredictable wind speed variation is captured without requiring accurate wind speed measurement, observation, or estimation. Moreover, with the proposed adaptive analytic algorithms, together with the use of radial basis function neural networks, a robust, adaptive, and fault-tolerant control scheme is developed without the need for precise information about the wind turbine model nor the pitch actuator faults. Additionally, the computational cost of the resultant control law is reduced by utilizing a dynamic surface control technique. The effectiveness of the developed design is verified using theoretical analysis tools and illustrated by numerical simulations on a high-fidelity wind turbine benchmark model with different fault scenarios. Comparison of the achieved results to the ones that can be obtained via an available industrial controller shows the advantages of the proposed scheme.
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: IEEE
Date: 12-2017
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: Informa UK Limited
Date: 15-10-2013
Publisher: Sciyo
Date: 12-08-2010
DOI: 10.5772/10187
Publisher: Elsevier BV
Date: 11-2018
Publisher: AIP Publishing
Date: 11-2017
DOI: 10.1063/1.5003380
Abstract: The operational wind turbine efficiency in the power maximization regions and reliability improvement to reduce the produced power cost can both be enhanced by using an appropriate controller to cope with the highly nonlinear behavior of wind turbines in the presence of wind speed variation and actuator faults. In this regard, a nonlinear controller is proposed to make the wind turbine operate effectively despite some of the actuator faults, similar to the fault-free case. The considered actuator faults are pitch and generator actuator biases, as well as pitch actuator dynamic change, including pump wear, hydraulic leak, and high air content in the oil. Also, the wind speed is assumed to be an unmeasurable disturbance, and, accordingly, when using the neural network scheme, the unknown desired trajectory is reconstructed, so that the captured power is maximized. The proposed controller is shown to be able to keep the wind turbine tracking the reconstructed desired trajectory with sufficient accuracy. By using the Lyapunov analysis, the boundedness of the closed-loop system with the proposed controller is proven. The designed controller is verified via numerical simulations. The effectiveness of the proposed controller is evaluated in comparison with industrial constant gain controller results.
Publisher: Elsevier BV
Date: 05-2020
Publisher: Springer Science and Business Media LLC
Date: 03-2012
Location: Iran (Islamic Republic of)
No related grants have been discovered for Hamed Rahimi Nohooji.