A stochastic optimal control based model with velocity tracking and internal feedback for saccadic eye movements is presented in this paper. Recent evidence from neurophysiological studies of superior colliculus suggests the presence of a dynamic input to the saccade generation system that encodes saccade velocity, rather than just the saccade amplitude and direction. The new evidence makes it imperative to test if saccade control can use a desired velocity input which is the basis for the proposed velocity tracking model. The model is validated using behavioral data of saccades generated by healthy human subjects. It generates trajectories of horizontal saccades made to different amplitudes as well as predicts vertical and oblique saccade behavior. This paper presents the first-ever model of the saccadic system in an optimal control framework using an alternate interpretation of velocity-based control, contrary to the dominant end-point based models available in the literature.
Aerobatic maneuvers in insect-scale flapping-wing aerial robots via deep-learned robust tube model predictive control
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology（电气工程与计算机科学系，麻省理工学院）；Department of Aeronautics and Astronautics, Massachusetts Institute of Technology（航空宇航系，麻省理工学院）
The paper solves the problem of tracking control of a quadrotor with unmeasurable pitch and roll angles based on the geometric approach with the use of the enhanced extended observer and the internal model. The proposed approach makes it possible to ensure the movement of a quadrotor in a horizontal plane along a trajectory given in the form of a sinusoidal or second-order polynomial function with semiglobal asymptotic convergence of the tracking errors to zero.
Robustness is a basic property of any control system. In the context of linear output regulation, it was proved that embedding an internal model of the exogenous signals is necessary and sufficient to achieve tracking of the desired reference signals in spite of external disturbances and parametric uncertainties. This result is commonly known as "internal model principle". A complete extension of such linear result to general nonlinear systems is still an open problem, which is exacerbated by the large number of alternative definitions of uncertainty and desired control goals that are possible…
This paper studies the time-optimal path tracking problem for a team of cooperating robotic manipulators carrying an object. Considering the problem for rigidly grasped objects, we show that it can be cast as a convex optimization problem and solved efficiently with a guarantee of optimality. When formulating the problem, we avoid using a particular wrench distribution and exploit the full actuation available to the system. Then, we consider the problem for grasps using frictional forces and show that this problem also, under a force-closure grasp assumption, can be formulated as a convex opti…
University of Pennsylvania（宾夕法尼亚大学）；Instituto de Ciencias Matematicas (CSIC-UAM-UCM-UC3M)（数学科学研究所（西班牙国家研究委员会-马德里自治大学-马德里康普顿斯大学-卡洛斯三世大学））；Technical University of Munich（慕尼黑工业大学）
Underactuated vehicles have gained much attention in the recent years due to the increasing amount of aerial and underwater vehicles as well as nanosatellites. Trajectory tracking control of these vehicles is a substantial aspect for an increasing range of application domains. However, external disturbances and parts of the internal dynamics are often unknown or very time-consuming to model. To overcome this issue, we present a tracking control law for underactuated rigid-body dynamics using an online learning-based oracle for the prediction of the unknown dynamics. We show that Gaussian proce…
Trajectory Tracking Control with Flat Inputs and a Dynamic Compensator
Institute of Control Engineering, Universität der Bundeswehr München（德国联邦国防军慕尼黑大学控制工程系）；Institute of Electrical Drive Systems and Power Electronics, Technische Universität München（慕尼黑工业大学电气驱动系统与电力电子研究所）
