Lyndon J. Brown

Hashim A. Hashim, Lyndon J. Brown, Kenneth McIsaac

Two nonlinear stochastic complimentary filters are developed on SO(3). They guarantee that errors in the Rodriguez vector and estimates are semi-globally uniformly ultimately bounded in mean square, and they converge to a small neighborhood of the origin. Simulation results are presented to illustrate the effectiveness of the proposed filters considering high level of uncertainties in angular velocity as well as body-frame vector measurements. Keywords: Attitude estimate, Attitude estimator, Attitude observer, Attitude filter, Nonlinear stochastic filter, stochastic differential equations, Brownian motion process, Ito, Stratonovich, Wong Zakai, Rodriguez vector, unit-quaternion, special orthogonal group 3, Euclidean, Euler angles, Angle-axis, Mapping, Parameterization, Representation, Robust, Invariant, Kalman Filter, Extended Kalman Filter, Multiplicative Extended Kalman Filter, Unscented Kalman Filter, Particle Filter, KF, EKF, MEKF, IEKF, first, second, Partial derivative, operator, probability, small, error, dynamics, kinematics, equilibrium, asymptotic, covariance, mean square, expected value, zero, unknown, time-varying, global, semi-global, stable, stability, uncertain, white noise, Gaussian noise, colored noise, bias, vectorial, vector measurement, angular velocity, singular value decomposition, bounded, rotational matrix, identity, deterministic, orientation, body frame, comparison, inertial frame, rigid body, three dimensional, 3D, space, Attitude Control, Lie algebra, Lie group, projection, Gyroscope, Inertial measurement units, micro electromechanical systems, sensor, IMUs, MEMS, Roll, Pitch, Yaw, UAVs, QUAV, SVD, Fixed, Moving, Vehicles, Robot, Robotic System, Spacecraft, submarine, Underwater vehicle, Problem, advantage, integral, integration, passive complementary filter, Disadvantage, autonomous, Review, Overview, Survey, comparative study, pose, SDEs, SE(3), SO(3).

Hashim A. Hashim, Lyndon J. Brown, Kenneth McIsaac

This paper formulates the pose estimation problem as nonlinear stochastic filter kinematics evolved directly on the Special Euclidean Group SE(3). Proposed filter guarantees that the errors present in position and Rodriguez vector estimates are semi-globally uniformly ultimately bounded (SGUUB) in mean square, and that they converge to small neighborhood of the origin in probability. Simulation results show the robustness and effectiveness of the proposed filter in presence of high levels of noise and bias associated with the velocity vector as well as body-frame measurements. Keywords: Pose estimator, pose observer, attitude estimate, control, estimator, observer, Nonlinear stochastic pose filter, stochastic differential equations, Brownian motion process, Ito, Stratonovich, Wong Zakai, unit-quaternion, special orthogonal group, homogeneous transformation matrix, complimentary filter, Euler angles, Angle-axis, mapping, Parameterization, Representation, Robust, Multiplicative Extended Kalman Filter, Unscented Kalman Filter, Particle filter, KF, EKF, IEKF, UKF, MEKF, partial derivative, small, dynamics, equilibrium, asymptotic, covariance, expected value, zero, unknown, time-varying, global, semi-global, stable, stability, uncertain, Gaussian, colored, white, noise, vectorial measurement, vector measurement, translational velocity, angular velocity, singular value decomposition, rotational matrix, identity, deterministic, comparison, inertial frame, rigid body, three dimensional, 3D, space, adjoint, Lie group, projection, landmark, feature, Gyroscope, micro electromechanical systems, Inertial measurement units, sensor, IMUs, Fixed, moving, orientation, Roll, Pitch, Yaw, SVD, UAVs, QUAV, unmanned, underwater vehicle, robot, Robotic System, Spacecraft, quadrotor, quadcopter, integral, advantage, disadvantage, Comparative study, Review, Overview, Survey, autonomous, xyz, axis, SO(3), SE(3).

Qimin Gao, Lyndon J. Brown, Luiz Fernando Capretz

There is a growing interest in adopting object technologies for the development of real-time control systems. Several commercial tools, currently available, provide object-oriented modeling and design support for real-time control systems. While these products provide many useful facilities, such as visualization tools and automatic code generation, they are all weak in addressing the central characteristic of real-time control systems design, i.e., providing support for a designer to reason about timeliness properties. We believe an approach that integrates the advancements in both object modeling and design methods and real-time scheduling theory is the key to successful use of object technology for real-time software. Surprisingly several past approaches to integrate the two either restrict the object models, or do not allow sophisticated schedulability analysis techniques. This study shows how schedulability analysis can be integrated with UML for Real-Time (UML-RT) to deal with timing properties in real time control systems. More specifically, we develop the schedulability and feasibility analysis modeling for the external messages that may suffer release jitter due to being dispatched by a tick driven scheduler in real-time control system and we also develop the scheduliablity modeling for sporadic activities, where messages arrive sporadically then execute periodically for some bounded time. This method can be used to cope with timing constraints in realistic and complex real-time control systems. Using this method, a designer can quickly evaluate the impact of various implementation decisions on schedulability. In conjunction with automatic code-generation, we believe that this will greatly streamline the design and development of real-time control systems software.