855 resultados para Nonlinear control systems
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This paper introduces Periodically Controlled Hybrid Automata (PCHA) for describing a class of hybrid control systems. In a PCHA, control actions occur roughly periodically while internal and input actions may occur in the interim changing the discrete-state or the setpoint. Based on periodicity and subtangential conditions, a new sufficient condition for verifying invariance of PCHAs is presented. This technique is used in verifying safety of the planner-controller subsystem of an autonomous ground vehicle, and in deriving geometric properties of planner generated paths that can be followed safely by the controller under environmental uncertainties.
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Networked control systems (NCSs) have attracted much attention in the past decade due to their many advantages and growing number of applications. Different than classic control systems, resources in NCSs, such as network bandwidth and communication energy, are often limited, which degrade the closed-loop system performance and may even cause the system to become unstable. Seeking a desired trade-off between the closed-loop system performance and the limited resources is thus one heated area of research. In this paper, we analyze the trade-off between the sensor-to-controller communication rate and the closed-loop system performance indexed by the conventional LQG control cost. We present and compare several sensor data schedules, and demonstrate that two event-based sensor data schedules provide better trade-off than an optimal offline schedule. Simulation examples are provided to illustrate the theories developed in the paper. © 2012 AACC American Automatic Control Council).
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Operation of induction machines in the high-speed and/or high-torque range requires field-weakening to comply with voltage and current physical limitations. This paper presents an anti-windup approach to this problem: rather than developing an ad-hoc field weakening strategy in the high-speed region, we equip an unconstrained vector-control design with an anti-windup module that automatically adjusts the current and flux set-points so that voltage and current constraints are satisfied at every operating point. The anti-windup module includes a feedforward modification of the set point aimed at maximizing the available torque in steady-state and a feedback modification of the controller based on an internal model-based antiwindup scheme. This paper includes a complete stability analysis of the proposed solution and presents encouraging experimental results on an industrial drive. © 2012 IEEE.
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This paper studies some extensions to the decentralized attitude synchronization of identical rigid bodies. Considering fully actuated Euler equations, the communication links between the rigid bodies are limited and the available information is restricted to relative orientations and angular velocities. In particular, no leader nor external reference dictates the swarm's behavior. The control laws are derived using two classical approaches of nonlinear control - tracking and energy shaping. This leads to a comparison of two corresponding methods which are currently considered for distributed synchronization - consensus and stabilization of mechanical systems with symmetries. © 2007 IEEE.
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Processing networks are a variant of the standard linear programming network model which are especially useful for optimizing industrial energy/environment systems. Modelling advantages include an intuitive diagrammatic representation and the ability to incorporate all forms of energy and pollutants in a single integrated linear network model. Added advantages include increased speed of solution and algorithms supporting formulation. The paper explores their use in modelling the energy and pollution control systems in large industrial plants. The pollution control options in an ethylene production plant are analyzed as an example. PROFLOW, a computer tool for the formulation, analysis, and solution of processing network models, is introduced.
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The properties of positively invariant sets are involved in many different problems in control theory, such as constrained control, robustness analysis, synthesis and optimization. In this paper we provide an overview of the literature concerning positively invariant sets and their application to the analysis and synthesis of control systems.
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针对具有有界时延和数据包丢失的网络控制系统,提出了一种新的稳定性判据.基于Lyapunov方法和图论理论,给出非线性离散和连续网络控制系统渐近稳定的充分条件,获得保持这两类系统稳定的最大允许时延界,得到控制器设计方法.并且,利用区间矩阵的谱特征,给出网络控制系统区间稳定的充分条件.设计算法,获得比例积分反馈控制器增益.算例表明所提方法的有效性。
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系统地回顾了近年来奇异摄动控制技术的发展 ,主要包括线性奇异摄动系统的稳定性分析与镇定、最优控制、H∞ 控制 ,非线性奇异摄动系统的镇定、优化控制和基于积分流形的几何方法 ,以及奇异摄动技术在实际工业 ,例如机器人领域、航天技术领域和工程工业、制造业等中的成功应用 .并指出了这一领域进一步研究的方向
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近年来,机器人、数控机床等机电系统在国民生产及生活中得到了越来越广泛的应用,与之相对应的,机电系统的控制无形中也逐渐成为机电一体化和自动控制的研究热点。另一方面,非线性特性是任何实际系统普遍存在的现象,在机电系统中尤其如此。本文从控制器设计的角度研究非线性机电系统的两个典型问题:系统闭环优化性能的改善;控制器鲁棒性的增强。这也是当前自动控制研究领域的两个重点及热点问题。 最优性是闭环系统性能最实用的评价指标之一。最优控制及预测控制是试图实现控制性能优化的两种典型方法。但前者因本身不构成闭环而严重缺乏鲁棒性,在实践中很少能得到应用;后者作为前者理念的推广,在实践中已经得到了较为广泛地应用,并取得了不错的效果,但在实现某种程度的鲁棒性时依然面临困难。除最优性外,闭环控制的鲁棒性也是非线性系统控制中亟待解决的问题之一,这是由于实际的系统几乎不可能避免模型不确定性。 现有的非线性预测控制及鲁棒控制方法无论在方法的广泛适用性还是在可行性方面都还远非完备。据此,本论文沿鲁棒性和最优性两条主线,以典型的机电系统(无人直升机模型)为研究对象,分别进行了深入的理论和实验研究,并最终形成一种同时兼顾最优性和鲁棒性的控制器设计框架,以期在一定程度上解决现有方法中存在的问题,并为以后更深入的研究工作奠定基础。 鉴于此,本论文分别针对鲁棒控制和预测控制展开讨论,其中前者主要解决基于加速度反馈实现鲁棒控制的方法,内容为第二章和第三章;后者则旨在解决基于控制Lyapunov函数方法实现实时稳定预测控制,主要内容为第四章和第五章。本论文的具体内容安排如下: 论文的第一章综述了控制理论在鲁棒性与最优性两个方向的发展概况(主要针对非线性系统),包括其发展历史,现存方法的局限性等。从而引出本论文的研究内容及研究意义。 第二章,研究了基于加速度反馈的控制器鲁棒增强方法。在深入分析常规加速度反馈控制方法的基础上,指出其存在的三方面主要问题:代数环问题;高增益实现问题和不能用于欠驱动非线性系统等。并针对两种典型的非线性系统(以无人直升机模型为代表)将新的加速度反馈控制方法与H∞控制相结合,得到了一种能够保证输入输出稳定的扰动抑制方法。大量的仿真结果验证了方法的可行性及有效性。 随后,在第三章研究了加速度的估计问题。基于加速度反馈的鲁棒控制器增强技术得以实现的前提是加速度信号的获取,本章在分析了现有加速度估计方法存在严重的滞后问题的同时,提出了将Kalman滤波方法同牛顿预测方法相结合以改善相位滞后问题的方法。实验及仿真结果验证了方法的有效性。 第四章提出了基于控制Lyapunov函数的稳定闭环控制器设计框架。本章利用集值分析理论研究了控制Lyapunov函数具有的一些性质及其在控制器设计中的应用。随后,介绍了两种典型的根据控制Lyapunov函数设计控制器的方法。接着,将引导函数的概念引入到Freeman的逐点最小范数控制方法中,形成了一种新的利用控制Lyapunov函数设计非线性控制器的方法—广义逐点最小范数控制器。最后指出,在这种框架下,鲁棒控制器设计也可以实现,并针对三种不同的不确定性系统给出了鲁棒广义逐点最小范数控制器设计方法。 最后,在第五章,将前面提出的广义逐点最小范数控制引入到非线性预测控制中去,以期利用控制Lyapunov函数保证闭环稳定性,同时利用控制器中的参数化变量作为优化对象以减轻预测控制算法的计算负担,从而达到实时稳定预测控制的目的。另外,在这一章我们还在第二章和第四章的基础上,结合加速度反馈思想和鲁棒控制Lyapunov函数的概念,提出了一种用于扰动抑制的鲁棒实时预测控制算法。同样,仿真实验验证了方法的有效性和可行性。
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Alexander, Nicholas, Doherty, Anne Marie, 'Power and control in international retail franchising', European Journal of Marketing (2006) 40(11-12) pp.1292-1316 RAE2008
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Both animals and mobile robots, or animats, need adaptive control systems to guide their movements through a novel environment. Such control systems need reactive mechanisms for exploration, and learned plans to efficiently reach goal objects once the environment is familiar. How reactive and planned behaviors interact together in real time, and arc released at the appropriate times, during autonomous navigation remains a major unsolved problern. This work presents an end-to-end model to address this problem, named SOVEREIGN: A Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goal-oriented Navigation system. The model comprises several interacting subsystems, governed by systems of nonlinear differential equations. As the animat explores the environment, a vision module processes visual inputs using networks that arc sensitive to visual form and motion. Targets processed within the visual form system arc categorized by real-time incremental learning. Simultaneously, visual target position is computed with respect to the animat's body. Estimates of target position activate a motor system to initiate approach movements toward the target. Motion cues from animat locomotion can elicit orienting head or camera movements to bring a never target into view. Approach and orienting movements arc alternately performed during animat navigation. Cumulative estimates of each movement, based on both visual and proprioceptive cues, arc stored within a motor working memory. Sensory cues are stored in a parallel sensory working memory. These working memories trigger learning of sensory and motor sequence chunks, which together control planned movements. Effective chunk combinations arc selectively enhanced via reinforcement learning when the animat is rewarded. The planning chunks effect a gradual transition from reactive to planned behavior. The model can read-out different motor sequences under different motivational states and learns more efficient paths to rewarded goals as exploration proceeds. Several volitional signals automatically gate the interactions between model subsystems at appropriate times. A 3-D visual simulation environment reproduces the animat's sensory experiences as it moves through a simplified spatial environment. The SOVEREIGN model exhibits robust goal-oriented learning of sequential motor behaviors. Its biomimctic structure explicates a number of brain processes which are involved in spatial navigation.
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This work considers the effect of hardware constraints that typically arise in practical power-aware wireless sensor network systems. A rigorous methodology is presented that quantifies the effect of output power limit and quantization constraints on bit error rate performance. The approach uses a novel, intuitively appealing means of addressing the output power constraint, wherein the attendant saturation block is mapped from the output of the plant to its input and compensation is then achieved using a robust anti-windup scheme. A priori levels of system performance are attained using a quantitative feedback theory approach on the initial, linear stage of the design paradigm. This hybrid design is assessed experimentally using a fully compliant 802.15.4 testbed where mobility is introduced through the use of autonomous robots. A benchmark comparison between the new approach and a number of existing strategies is also presented.
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This is a user manual for your electronic assistive technology environmental control system trial pack or in simple words – a few bits of technology that can let you control some household appliances. This information is intended for you, your family and carers.