The Experts below are selected from a list of 285 Experts worldwide ranked by ideXlab platform

Raluca Lefticaru - One of the best experts on this subject based on the ideXlab platform.

  • Design and implementation of membrane controllers for trajectory tracking of nonholonomic wheeled mobile robots
    Integrated Computer-Aided Engineering, 2015
    Co-Authors: Xueyuan Wang, Gexiang Zhang, Ferrante Neri, Tao Jiang, Junbo Zhao, Marian Gheorghe, Florentin Ipate, Raluca Lefticaru
    Abstract:

    This paper proposes a novel trajectory tracking control approach for nonholonomic wheeled mobile robots. In this approach, the integration of feed-forward and feedback controls is presented to design the kinematic controller of wheeled mobile robots, where the control law is constructed on the basis of Lyapunov stability theory, for generating the precisely desired veloc- ity as the input of the dynamic model of wheeled mobile robots; a proportional-integral-derivative based membrane controller is introduced to design the dynamic controller of wheeled mobile robots to make the actual Velocity follow the desired Velocity Command. The proposed approach is defined by using an enzymatic numerical membrane system to integrate two proportional- integral-derivative controllers, where neural networks and experts' knowledge are applied to tune parameters. Extensive experi- ments conducted on the simulated wheeled mobile robots show the effectiveness of this approach.

Randal W Beard - One of the best experts on this subject based on the ideXlab platform.

  • ACC - Relative Moving Target Tracking and Circumnavigation
    2019 American Control Conference (ACC), 2019
    Co-Authors: Jerel Nielsen, Randal W Beard
    Abstract:

    This paper develops observers and controllers for relative estimation and circumnavigation of a moving ground target using bearing-only measurements or range with bearing measurements. A bearing-only observer, range with bearing observer, a general circumnavigation Velocity Command for an arbitrary aircraft, and nonlinear Velocity-based multirotor controller are developed. The observers are designed in the body-fixed reference frame, while the Velocity Command and multirotor controller are developed in the body-level frame, independent of aircraft heading. This enables target circumnavigation in GPS-denied environments when only a camera-IMU estimator is used for state estimation and ensures observable conditions for the estimator. Simulation results demonstrate the effectiveness of the observers, Velocity Command, and multirotor controller under various target motions.

  • Trajectory tracking for unmanned air vehicles with Velocity and heading rate constraints
    IEEE Transactions on Control Systems Technology, 2004
    Co-Authors: Wei Ren, Randal W Beard
    Abstract:

    This paper considers the problem of constrained nonlinear trajectory tracking control for unmanned air vehicles (UAVs). We assume that the UAV is equipped with longitudinal and lateral autopilots which reduces the 12-state model to a six-state model with altitude, heading, and Velocity Command inputs. One of the novel features of our approach is that we explicitly account for heading rate and Velocity input constraints. For a UAV, the Velocity is constrained to lie between two positive constants, and therefore presents particular challenges for the control design. We propose a control Lyapunov function (CLF) approach. We first introduce a CLF for the input constrained case, and then construct the set of all constrained inputs that are feasible with respect to this CLF. The control input is then selected from this "feasible" set. The proposed approach is applied to a simulation scenario, where the UAV is assigned to transition through several targets in the presence of multiple dynamic threats.

Olav Egeland - One of the best experts on this subject based on the ideXlab platform.

  • Vision-Based Control of a Knuckle Boom Crane With Online Cable Length Estimation
    IEEE ASME Transactions on Mechatronics, 2021
    Co-Authors: Geir Ole Tysse, Andrej Cibicik, Olav Egeland
    Abstract:

    A vision-based controller for a knuckle boom crane is presented. The controller is used to control the motion of the crane tip, and at the same time, compensate for payload oscillations. The oscillations of the payload are measured with three cameras that are fixed to the crane king, and are used to track two spherical markers fixed to the payload cable. Based on color and size information, each camera identifies the image points corresponding to the markers. The payload angles are then determined using linear triangulation of the image points. An extended Kalman filter is used for the estimation of payload angles and angular Velocity. The length of the payload cable is also estimated using the least-squares technique with projection. The crane is controlled by a linear cascade controller where the inner control loop is designed to damp out the pendulum oscillation, and the crane tip is controlled by the outer loop. The control variable of the controller is the Commanded crane tip acceleration, which is converted to a Velocity Command using a Velocity loop. The performance of the control system is studied experimentally using a scaled laboratory version of a knuckle boom crane.

  • vision based control of a knuckle boom crane with online cable length estimation
    IEEE-ASME Transactions on Mechatronics, 2020
    Co-Authors: Geir Ole Tysse, Andrej Cibicik, Olav Egeland
    Abstract:

    A vision-based controller for a knuckle boom crane is presented. The controller is used to control the motion of the crane tip and at the same time compensate for payload oscillations. The oscillations of the payload are measured with three cameras that are fixed to the crane king and are used to track two spherical markers fixed to the payload cable. Based on color and size information, each camera identifies the image points corresponding to the markers. The payload angles are then determined using linear triangulation of the image points. An extended Kalman filter is used for estimation of payload angles and angular Velocity. The length of the payload cable is also estimated using a least squares technique with projection. The crane is controlled by a linear cascade controller where the inner control loop is designed to damp out the pendulum oscillation, and the crane tip is controlled by the outer loop. The control variable of the controller is the Commanded crane tip acceleration, which is converted to a Velocity Command using a Velocity loop. The performance of the control system is studied experimentally using a scaled laboratory version of a knuckle boom crane.

Lei Guo - One of the best experts on this subject based on the ideXlab platform.

  • H∞ Sampled-Data Fuzzy Control for Attitude Tracking of Mars Entry Vehicles With Control Constraints
    Information Sciences, 2019
    Co-Authors: Zi-peng Wang, Lei Guo
    Abstract:

    Abstract In this paper, the problem of designing an H ∞ sampled-data fuzzy controller is investigated for attitude tracking of Mars entry vehicles with control constraints. Initially, to overcome the difficulty of Takagi-Sugeno (T-S) fuzzy modeling, the original nonlinear error system is divided into a fast subsystem and a slow subsystem on the basis of two time-scale decomposition technique, where the fast subsystem describes the attitude dynamics and the slow subsystem describes the attitude kinematics. Dynamic inversion control method is subsequently employed to obtain the angular Velocity Command for the slow subsystem. Then, based on the angular Velocity Command and the T-S fuzzy model of the fast subsystem, a tracking error fuzzy system is derived for the sampled-data fuzzy control design. The existence condition of the constrained H ∞ sampled-data fuzzy controllers is provided in terms of linear matrix inequalities (LMIs). The proposed controller can exponentially stabilize the original nonlinear error system with an H ∞ tracking performance, provided that the timescale separation between the fast and slow subsystems is valid. Finally, simulation results illustrate the effectiveness of the proposed method.

  • Fault tolerant attitude tracking control for Mars entry vehicles via Takagi-Sugeno model
    Proceedings of 2014 IEEE Chinese Guidance Navigation and Control Conference, 2014
    Co-Authors: Bo Jiang, Lei Guo
    Abstract:

    In this paper, a fault tolerant fuzzy tracking controller is designed for Mars entry vehicles during the entry phase in the presence of actuator failures. The original nonlinear attitude dynamics are divided into two subsystems based on the concept of time-scale decomposition. Dynamic inversion method is employed for the slow kinematic subsystem to give the angular Velocity Command by taking the attitude Command as its input. The Takagi-Sugeno (T-S) fuzzy model based control method is applied for the fast kinetic subsystem by taking angular Velocity Command as its input to derive the desired control torque in the presence of actuator failures. Finally, the simulation results are given to demonstrate the effectiveness of the developed method for the Mars entry fault tolerant attitude control problem.

  • CDC - Attitude tracking of mars entry vehicles via fuzzy sampled-data control approach
    53rd IEEE Conference on Decision and Control, 2014
    Co-Authors: Zi-peng Wang, Bo Jiang, Lei Guo
    Abstract:

    In this paper, a fuzzy sampled-data attitude tracking controller is designed for Mars entry vehicles. Initially, to reduce the complexity of fuzzy modeling, the original nonlinear attitude system is divided into two subsystems by using two time-scale decomposition method. Subsequently, the dynamic inversion control technique is applied to the slow subsystem to generate the angular Velocity Command. Then, based on the Takagi-Sugeno (T-S) fuzzy model of the fast subsystem and the angular Velocity Command, the fuzzy sampled-data controller is designed for the fuzzy tracking error system to derive the desired control torques by using a time-dependent Lyapunov functional. Finally, the simulation results on the Mars entry vehicles are given to illustrate the feasibility and effectiveness of the proposed method.

Xueyuan Wang - One of the best experts on this subject based on the ideXlab platform.

  • Design and implementation of membrane controllers for trajectory tracking of nonholonomic wheeled mobile robots
    Integrated Computer-Aided Engineering, 2015
    Co-Authors: Xueyuan Wang, Gexiang Zhang, Ferrante Neri, Tao Jiang, Junbo Zhao, Marian Gheorghe, Florentin Ipate, Raluca Lefticaru
    Abstract:

    This paper proposes a novel trajectory tracking control approach for nonholonomic wheeled mobile robots. In this approach, the integration of feed-forward and feedback controls is presented to design the kinematic controller of wheeled mobile robots, where the control law is constructed on the basis of Lyapunov stability theory, for generating the precisely desired veloc- ity as the input of the dynamic model of wheeled mobile robots; a proportional-integral-derivative based membrane controller is introduced to design the dynamic controller of wheeled mobile robots to make the actual Velocity follow the desired Velocity Command. The proposed approach is defined by using an enzymatic numerical membrane system to integrate two proportional- integral-derivative controllers, where neural networks and experts' knowledge are applied to tune parameters. Extensive experi- ments conducted on the simulated wheeled mobile robots show the effectiveness of this approach.