1,720,966 research outputs found

    Graph-based algorithms for the efficient solution of optimization problems involving monotone functions

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    In this paper, we address a class of specially structured problems that include speed planning, for mobile robots and robotic manipulators, and dynamic programming. We develop two new numerical procedures, that apply to the general case and to the linear subcase. With numerical experiments, in the linear case we show that the proposed algorithms outperform generic commercial solvers

    A Consensus Approach to Dynamic Programming

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    Motivated by the finite element formulation of the Hamilton-Jacobi-Bellman (HJB) equation, we introduce a consensus algorithm to compute the solution of a class of optimization problems that can be solved with a fixed point iteration. The proposed algorithm reduces the computational cost in terms of elementary operations with respect to a complete fixed point iteration. We provide theoretical results on maximum error rate and on the convergence of the algorithm. As an application, we compute the minimum-time solution for a parking maneuver of a car-like vehicle, comparing the fixed point iteration with the consensus iteration

    A Jacobi-like acceleration for dynamic programming

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    The Hamilton-Jacobi-Bellman (HJB) equation provides a general method to solve optimal control problems. Since the HJB equation is a nonlinear partial differential equation, a closed form solution does not exist for the general case and various numerical procedures have been developed for its solution. Some recent approaches, after some simplifications, convert the problem into a fixed-point iteration. One problem related to the iteration is that its convergence speed is rather poor. We propose a Jacobi-like acceleration that allows to improve the convergence speed. As an application, we compute the minimum-time solution of a parking maneuver for a car-like vehicle with bounded velocity and steering angle

    用于计算适于道路车辆的最优停车操纵的 路径规划方法和相应系统

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    一种用于计算适于道路车辆的最优停车操 纵 的 路 径 规 划 方 法 ,包 括 计 算 车 辆 控 制 集 及 达 到 状 态 目 标 集 ,停 车 操 纵 是 通 过 方 程 式 系 统 获 得 的 轨迹,方程式系统根据车辆控制对道路车辆的状 态 的 演 变 进 行 建 模 ;还 包 括 :将 达 到 状 态 目 标 集 的停车操纵的成本函数的值函数集计算为哈密 顿 雅 克 比 贝 尔 曼 方 程 的 唯 一 粘 性 解 ,成 本 函 数 考 虑 车 辆 对 于 给 定 停 车 操 纵 的 到 达 时 间 ;将 值 函 数 集连同车辆的起始状态一起作为输入提供给计 算 至 少 车 辆 控 制 集 的 动 态 编 程 计 算 过 程 ;道 路 车 辆的状态演变的方程式集模型是在车辆处于前 向运动的第一子系统和车辆处于倒车或向后运 动 的 第 二 子 系 统 之 间 的 方 程 式 的 切 换 系 统 ;成 本 函数还考虑在前向运动和倒车运动之间道路车 辆的方向改变次数

    A minimum Time-to-Target MPC approach for depth of hypnosis in total intravenous anesthesia

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    In this paper we propose a new approach for the Depth-of-Hypnosys (DoH) control in Total Intravenous Anesthesia (TIVA), where the bispectral index (BIS) is the process variable and the infusion rate of propofol is the control variable. In particular, a Proportional-Integral-Derivative (PID) controller is employed when the BIS is inside the specified range from 60 to 40. Then, a model predictive control (MPC) technique is employed when the BIS is higher than 60 with the aim of minimizing the time-to-target, thus reducing the risk of awareness for the patient during the maintenance phase. The same approach is also effective in the induction phase, reducing its duration. Simulation results show the effectiveness of the methodology

    System realizations by mammillary models with an application to propofol pharmacokinetics

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    This work addresses the problem of linear system realizations by mammillary and mammillary-like models, offering necessary and sufficient conditions under which a given transfer function can be represented in this form. Compartmental models, particularly mammillary ones, reflect the physiological dynamics of distribution and elimination. This is especially relevant in clinical pharmacology, where model parameters correspond to meaningful biological processes to support interpretability, personalization, and safe drug delivery, such as in total intravenous anesthesia. To conclude, an application to a propofol infusion model illustrates how mammillary realizations can support physiologically interpretable system representations

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Human-Imitating Control of Depth of Hypnosis Combining MPC and Event-Based PID Strategies

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    In this letter we propose a human-imitating control methodology for the Depth-of-Hypnosys (DoH) in total intravenous anesthesia (TIVA) where the bispectral index (BIS) is used as process variable. The method suitably combines a move-blocking model predictive controller (MPC) that minimizes the time-to-target when the BIS value is not in the required range and an event-based Proportional-Integral-Derivative (PID) controller that provides a strong filtering action when the DoH is satisfactory. A fast induction is achieved and awareness episodes are avoided with a control action that is piecewise constant so that it mimics the behavior of the anesthesiologist and is more likely to be accepted in the clinical practice
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