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Hamed Jabbari Asl - One of the best experts on this subject based on the ideXlab platform.

  • Bounded-Input prescribed performance control of uncertain Euler–Lagrange systems
    IET Control Theory & Applications, 2019
    Co-Authors: Hamed Jabbari Asl, Tatsuo Narikiyo, Michihiro Kawanishi
    Abstract:

    This study proposes a novel saturated prescribed performance (PP) controller for Euler–Lagrange dynamic systems. The design of Bounded-Input controller is facilitated by means of introduction of auxiliary dynamics in the closed-loop system. The controller takes advantages of using an adaptive multilayer neural network and a robust term to deal with uncertainties of the system. Through the stability analysis, it is shown that PPwith saturated control command is feasible having certain constraints on initial conditions and external disturbances. The proposed controller is validated through experimental and simulation studies conducted on a lower-limb robotic exoskeleton.

  • Bounded Input prescribed performance control of uncertain euler lagrange systems
    Iet Control Theory and Applications, 2019
    Co-Authors: Hamed Jabbari Asl, Tatsuo Narikiyo, Michihiro Kawanishi
    Abstract:

    This study proposes a novel saturated prescribed performance (PP) controller for Euler–Lagrange dynamic systems. The design of Bounded-Input controller is facilitated by means of introduction of auxiliary dynamics in the closed-loop system. The controller takes advantages of using an adaptive multilayer neural network and a robust term to deal with uncertainties of the system. Through the stability analysis, it is shown that PPwith saturated control command is feasible having certain constraints on initial conditions and external disturbances. The proposed controller is validated through experimental and simulation studies conducted on a lower-limb robotic exoskeleton.

  • Bounded Input control of the quadrotor unmanned aerial vehicle a vision based approach
    Asian Journal of Control, 2017
    Co-Authors: Hamed Jabbari Asl, Jungwon Yoon
    Abstract:

    In this paper, a Bounded-Input controller is designed for the quadrotor vertical take-off and landing unmanned aerial vehicle (UAV). Visual information is used to localize the aircraft with respect to its environment and an image-based visual servo scheme is developed to navigate the motion of it. The visual features are selected from perspective image moments and projected on a rotated image plane, which simplifies the controller design. The flow of the features is used as the linear velocity information, and the controller assumes angular velocity and attitude information available for feedback. To design the controller, the dynamics of the quadrotor are decoupled into two parts: translational dynamics and rotational dynamics. First visual data are used to design a Bounded-Input controller for the translational dynamics, and then a saturated controller is designed for the rotational dynamics. The Boundedness of the controller increases the chance of keeping the visual features in the field of view of the camera. Furthermore, the controllers also cope with the unknown depth of the image, and the external disturbances. The complete stability analysis of the overall system is presented to show that all states are Bounded and the error signals converge to zero asymptotically. Simulation examples are provided in both nominal and perturbed conditions which show the effectiveness of the proposed theoretical results.

  • Bounded‐Input Control of the Quadrotor Unmanned Aerial Vehicle: A Vision‐Based Approach
    Asian Journal of Control, 2016
    Co-Authors: Hamed Jabbari Asl, Jungwon Yoon
    Abstract:

    In this paper, a Bounded-Input controller is designed for the quadrotor vertical take-off and landing unmanned aerial vehicle (UAV). Visual information is used to localize the aircraft with respect to its environment and an image-based visual servo scheme is developed to navigate the motion of it. The visual features are selected from perspective image moments and projected on a rotated image plane, which simplifies the controller design. The flow of the features is used as the linear velocity information, and the controller assumes angular velocity and attitude information available for feedback. To design the controller, the dynamics of the quadrotor are decoupled into two parts: translational dynamics and rotational dynamics. First visual data are used to design a Bounded-Input controller for the translational dynamics, and then a saturated controller is designed for the rotational dynamics. The Boundedness of the controller increases the chance of keeping the visual features in the field of view of the camera. Furthermore, the controllers also cope with the unknown depth of the image, and the external disturbances. The complete stability analysis of the overall system is presented to show that all states are Bounded and the error signals converge to zero asymptotically. Simulation examples are provided in both nominal and perturbed conditions which show the effectiveness of the proposed theoretical results.

Michihiro Kawanishi - One of the best experts on this subject based on the ideXlab platform.

  • Bounded-Input prescribed performance control of uncertain Euler–Lagrange systems
    IET Control Theory & Applications, 2019
    Co-Authors: Hamed Jabbari Asl, Tatsuo Narikiyo, Michihiro Kawanishi
    Abstract:

    This study proposes a novel saturated prescribed performance (PP) controller for Euler–Lagrange dynamic systems. The design of Bounded-Input controller is facilitated by means of introduction of auxiliary dynamics in the closed-loop system. The controller takes advantages of using an adaptive multilayer neural network and a robust term to deal with uncertainties of the system. Through the stability analysis, it is shown that PPwith saturated control command is feasible having certain constraints on initial conditions and external disturbances. The proposed controller is validated through experimental and simulation studies conducted on a lower-limb robotic exoskeleton.

  • Bounded Input prescribed performance control of uncertain euler lagrange systems
    Iet Control Theory and Applications, 2019
    Co-Authors: Hamed Jabbari Asl, Tatsuo Narikiyo, Michihiro Kawanishi
    Abstract:

    This study proposes a novel saturated prescribed performance (PP) controller for Euler–Lagrange dynamic systems. The design of Bounded-Input controller is facilitated by means of introduction of auxiliary dynamics in the closed-loop system. The controller takes advantages of using an adaptive multilayer neural network and a robust term to deal with uncertainties of the system. Through the stability analysis, it is shown that PPwith saturated control command is feasible having certain constraints on initial conditions and external disturbances. The proposed controller is validated through experimental and simulation studies conducted on a lower-limb robotic exoskeleton.

  • Neural network velocity field control of robotic exoskeletons with Bounded Input
    2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), 2017
    Co-Authors: Tatsuo Narikiyo, Michihiro Kawanishi
    Abstract:

    Velocity field control (VFC) is an alternative approach for motion control of robotic systems. It has advantages over the trajectory tacking problem when the timing in the desired task is of less importance in the application of interest. Recently, this control strategy has been emerged as a promising control method in robot-aided rehabilitation. Therefore, this paper addresses the problem of VFC for robotic exoskeletons with dynamic uncertainties. Most existing VFC methods require some knowledge of the dynamic model of the robot, which is usually difficult in practice to precisely identify. Consequently, this paper design an adaptive neural network VFC method to compensate for the dynamic uncertainties. The controller gives a priori Bounded control command in order to take into account the saturation of actuators. The controller performance is validated through simulation and experimental studies on a two-degree-of-freedom lower-limb robotic exoskeleton.

Alec Yasinsac - One of the best experts on this subject based on the ideXlab platform.

  • Applications for Provably Secure Intent Protection with Bounded Input-Size Programs
    The Second International Conference on Availability Reliability and Security (ARES'07), 2007
    Co-Authors: Todd J. Mcdonald, Alec Yasinsac
    Abstract:

    The de facto standard program obfuscation security model, termed the virtual black box (VBB), declares a program to be securely obfuscated if and only if an adversary can prove no more when given the obfuscated code than it can when only given oracle access to the original program. In this paper, we define and give methodology for a perfectly secure program intent obfuscation that is general and practical for Bounded Input-size programs, including those with Input/output relationships that are easily learned. We also lay foundations for how to embed a key securely in a private-key encryption setting using such constructions

  • ARES - Applications for Provably Secure Intent Protection with Bounded Input-Size Programs
    The Second International Conference on Availability Reliability and Security (ARES'07), 2007
    Co-Authors: J.t. Mcdonald, Alec Yasinsac
    Abstract:

    The de facto standard program obfuscation security model, termed the virtual black box (VBB), declares a program to be securely obfuscated if and only if an adversary can prove no more when given the obfuscated code than it can when only given oracle access to the original program. In this paper, we define and give methodology for a perfectly secure program intent obfuscation that is general and practical for Bounded Input-size programs, including those with Input/output relationships that are easily learned. We also lay foundations for how to embed a key securely in a private-key encryption setting using such constructions

Tatsuo Narikiyo - One of the best experts on this subject based on the ideXlab platform.

  • Bounded-Input prescribed performance control of uncertain Euler–Lagrange systems
    IET Control Theory & Applications, 2019
    Co-Authors: Hamed Jabbari Asl, Tatsuo Narikiyo, Michihiro Kawanishi
    Abstract:

    This study proposes a novel saturated prescribed performance (PP) controller for Euler–Lagrange dynamic systems. The design of Bounded-Input controller is facilitated by means of introduction of auxiliary dynamics in the closed-loop system. The controller takes advantages of using an adaptive multilayer neural network and a robust term to deal with uncertainties of the system. Through the stability analysis, it is shown that PPwith saturated control command is feasible having certain constraints on initial conditions and external disturbances. The proposed controller is validated through experimental and simulation studies conducted on a lower-limb robotic exoskeleton.

  • Bounded Input prescribed performance control of uncertain euler lagrange systems
    Iet Control Theory and Applications, 2019
    Co-Authors: Hamed Jabbari Asl, Tatsuo Narikiyo, Michihiro Kawanishi
    Abstract:

    This study proposes a novel saturated prescribed performance (PP) controller for Euler–Lagrange dynamic systems. The design of Bounded-Input controller is facilitated by means of introduction of auxiliary dynamics in the closed-loop system. The controller takes advantages of using an adaptive multilayer neural network and a robust term to deal with uncertainties of the system. Through the stability analysis, it is shown that PPwith saturated control command is feasible having certain constraints on initial conditions and external disturbances. The proposed controller is validated through experimental and simulation studies conducted on a lower-limb robotic exoskeleton.

  • Neural network velocity field control of robotic exoskeletons with Bounded Input
    2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), 2017
    Co-Authors: Tatsuo Narikiyo, Michihiro Kawanishi
    Abstract:

    Velocity field control (VFC) is an alternative approach for motion control of robotic systems. It has advantages over the trajectory tacking problem when the timing in the desired task is of less importance in the application of interest. Recently, this control strategy has been emerged as a promising control method in robot-aided rehabilitation. Therefore, this paper addresses the problem of VFC for robotic exoskeletons with dynamic uncertainties. Most existing VFC methods require some knowledge of the dynamic model of the robot, which is usually difficult in practice to precisely identify. Consequently, this paper design an adaptive neural network VFC method to compensate for the dynamic uncertainties. The controller gives a priori Bounded control command in order to take into account the saturation of actuators. The controller performance is validated through simulation and experimental studies on a two-degree-of-freedom lower-limb robotic exoskeleton.

Mauro Lopezrodriguez - One of the best experts on this subject based on the ideXlab platform.

  • finite time control for rigid robots with Bounded Input torques
    Control Engineering Practice, 2020
    Co-Authors: Javier Pliegojimenez, Marco A Arteagaperez, Mauro Lopezrodriguez
    Abstract:

    Abstract The problem of finite-time trajectory tracking of robot manipulators with uncertain dynamics, external Bounded disturbances, and Bounded torque Inputs is addressed in this paper. In order to achieve finite-time convergence a nonlinear control algorithm based on a second-order sliding mode controller in combination with nonsingular terminal sliding mode is proposed. The proposed controller also exploits the properties of the hyperbolic tangent function. As a result, the control algorithm generates a continuous Bounded signal. In addition, the controller structure is simple since it does not require the knowledge of the robot dynamic model. Experimental results are provided to show the performance of the proposed control algorithm.