Controle de um sistema de eletroestimulação funcional.

Esta Dissertação irá apresentar a utilização de técnicas de controle nãolinear, tais como o controle adaptativo e robusto, de modo a controlar um sistema de Eletroestimulação Funcional desenvolvido pelo laboratório de Engenharia Biomédica da COPPE/UFRJ. Basicamente um Eletroestimulador Funcional (Functional Electrical Stimulation FES) se baseia na estimulação dos nervos motores via eletrodos cutâneos de modo a movimentar (contrair ou distender) os músculos, visando o fortalecimento muscular, a ativação de vias nervosas (reinervação), manutenção da amplitude de movimento, controle de espasticidade muscular, retardo de atrofias e manutenção de tonicidade muscular. O sistema utilizado tem por objetivo movimentar os membros superiores através do estímulo elétrico de modo a atingir ângulos-alvo pré-determinados para a articulação do cotovelo. Devido ao fato de não termos conhecimento pleno do funcionamento neuro-motor humano e do mesmo ser variante no tempo, não-linear, com parâmetros incertos, sujeito a perturbações e completamente diferente para cada indivíduo, se faz necessário o uso de técnicas de controle avançadas na tentativa de se estabilizar e controlar esse tipo de sistema. O objetivo principal é verificar experimentalmente a eficácia dessas técnicas de controle não-linear e adaptativo em comparação às técnicas clássicas, de modo a alcançar um controle mais rápido, robusto e que tenha um desempenho satisfatório. Em face disso, espera-se ampliar o campo de utilização de técnicas de controle adaptativo e robusto, além de outras técnicas de sistemas inteligentes, tais como os algoritmos genéticos, provando que sua aplicação pode ser efetiva no campo de sistemas biológicos e biomédicos, auxiliando assim na melhoria do tratamento de pacientes envolvidos nas pesquisas desenvolvidas no Laboratório de Engenharia Biomédica da COPPE/UFRJ.

Robotics and neuroscience: A rhythmic interaction

At the crossing between motor control neuroscience and robotics system theory, the paper presents a rhythmic experiment that is amenable both to handy laboratory implementation and simple mathematical modeling. The experiment is based on an impact juggling task, requiring the coordination of two upper-limb effectors and some phase-locking with the trajectories of one or several juggled objects. We describe the experiment, its implementation and the mathematical model used for the analysis. Our underlying research focuses on the role of sensory feedback in rhythmic tasks. In a robotic implementation of our experiment, we study the minimum feedback that is required to achieve robust control. A limited source of feedback, measuring only the impact times, is shown to give promising results. A second field of investigation concerns the human behavior in the same impact juggling task. We study how a variation of the tempo induces a transition between two distinct control strategies with different sensory feedback requirements. Analogies and differences between the robotic and human behaviors are obviously of high relevance in such a flexible setup. © 2008 Elsevier Ltd. All rights reserved.

无人三体船试验平台的设计与实现

三体船特殊的构型使其非常适合用作水面无人平台(USV)的实验载体,本文介绍了一种自制的三体船型水面无人实验平台的系统设计、控制系统硬件以及实验结果,为以后开展三体船水动力建模、鲁棒控制方法的研究以及水面无人平台的开发提供依据。同时采用基于backstepping的控制方法对三体船进行了实验验证,实验结果表明控制方法的有效性以及平台的可靠性。

基于LMI全方位移动机器人H_∞鲁棒控制

针对机器人控制领域中一类多输入多输出(MIMO)高阶线性时不变系统,根据模型自身的结构特点,给出了基于线性矩阵不等式(LMI)的通过局部反馈H∞控制实现整个系统对不确定扰动具有鲁棒性的充分条件及相关推论,并在此基础上提出了一种解决该类型系统H∞控制问题的新算法。通过对一完整约束移动机器人系统的局部输出反馈H∞控制仿真,说明了此算法具有良好的控制效果和实用性。

具有自适应机制的鲁棒控制方法研究

近年来，复杂机电系统，特别是移动机器人、地面/水面/水下空中以及空间无人平台等，对高性能控制系统提出了迫切的需求。对控制系统的设计而言，这类系统的共性特点可以归纳为两方面：动力学复杂，包括非线性、交叉耦合、时变参数等；工作在动态环境中，存在大量未建模的时变扰动与不确定性。目前，由于非线性系统控制规律设计的理论和方法还不成熟，现在一般的做法是将非线性动力学模型在某些特定的状态下线性化，然后基于线性化模型利用线性控制理论设计控制器。但是，由于复杂机电系统动力学的复杂性会导致各种不确定性的出现；而且，扰动、传感器噪声、执行器饱和、各种摩擦和时滞等等都有可能使闭环系统的性能降低、甚至偏离稳定域，因此控制策略必须要具有一定的鲁棒性能。如何增强控制策略面对模型不确定性及时变扰动时的鲁棒性与自适应性，是当前控制领域研究的核心问题之一。 由于固定增益鲁棒控制方法具有固有的保守性，如何降低其保守性是设计鲁棒控制器需要考虑的重要问题。另一方面，自适应理论也是一种已有的具有长足发展的控制策略，应对参数不确定性是其典型应用。然而，即便是在理想情况下，一个稳定的自适应控制器也不能保证系统良好的瞬态特性。本论文提出将鲁棒控制和自适应机制相结合，给出了针对一类具有仿射不确定性线性系统的具有自适应机制的鲁棒控制器设计方法，并将这种控制策略应用到旋翼飞行机器人航向控制中。本论文的具体内容安排如下： 第一章，系统地分析和归纳了鲁棒控制理论中H∞控制、H2控制及鲁棒保性能控制等三种控制方法的发展现状以及其用于复杂机电系统时所存在的问题，同时简要介绍了旋翼飞行机器人控制领域的发展现状及现有方法。 第二章，基于线性矩阵不等式理论，分别研究了具有时不变不确定性和具有时变不确定性两类系统的鲁棒H∞控制问题。在传统固定增益鲁棒控制器设计方法的基础上，引入自适应机制设计变增益鲁棒控制器。该控制器的特点是控制器的参数可以根据不确定参数在线估计的结果自动调节以补偿不确定性对系统的影响；同时可以确保闭环系统渐近稳定且其H∞性能指标可以在线性矩阵不等式的框架中进行优化。 第三章，以自适应H∞控制为基础，提出了具有自适应机制的鲁棒H2控制方法。H∞控制系统具有较好的鲁棒性和较强的扰动抑制能力，但其动态品质较差；与其相反，H2控制可以使系统获得很好的动态、稳态性能。该控制器设计方法将线性矩阵不等式与自适应方法相结合，控制器参数仿射依赖于由自适应律在线调节的不确定性参数估计，所得到的自适应鲁棒H2控制器设计条件比固定增益鲁棒控制器设计条件保守性要小。 第四章，为了使系统不仅能鲁棒稳定而且动态响应满足一定的性能指标，进一步提出了具有自适应机制的鲁棒保性能控制方法。保性能控制方法提供一个性能指标上界，保证即使存在不确定性的情况下，系统性能衰减不会超过这个指标上界。在线性矩阵不等式方法框架下，将自适应控制方法与保性能控制方法相结合，获得了一种新的控制器设计方法。仿真实验表明了该方法的有效性。 第五章，介绍了本人参与设计的飞行机器人实验系统以及部分初步实验结果。 最后对全文作出总结，并提出了下一步研究的方向。

非完整系统鲁棒控制方法及在水面移动机器人中的应用

近年来，随着机器人技术的发展，各种各样的移动机器人系统正在开始应用于工业、国防安全、公共安全、灾难救援、科学探测等领域；但是，遥控作业仍然是制约移动机器人广泛应用的一个核心问题。如何使机器人系统摆脱遥控的束缚而具有全自主行为能力，是目前机器人学领域重点研究的关键问题之一。自主环境适应能力是移动机器人最基本的自主能力之一。机器人系统需要面对不可预知的、动态的、存在时变扰动和噪声的工作环境，这通常会导致机器人动力学参数的变化，从而使传统的机器人控制技术很难得到满意的控制效果并达到自主环境适应的目的。同时，目前的移动机器人系统大都受非完整约束的影响，由于其约束的不可积性，使其控制与规划变得异常困难，因此研究移动机器人在存在不确定情况下的鲁棒控制问题，以及存在非完整约束条件下的镇定问题和规划问题具有非常重要的理论意义和实际应用价值。本文以沈阳自动化所与大连理工大学联合研制的三体船型水面移动机器人（UTV）这个典型的受不确定以及非完整约束影响的系统为背景，研究其在存在大量不确定因素及外界环境干扰条件下的鲁棒控制问题和其在受制于非完整约束情况下的镇定和运动规划问题，其中前者主要针对系统在受风、流、浪等外界干扰下的鲁棒控制问题；后者旨在解决满足非完整约束条件下的非线性系统规划与控制问题。本论文的具体内容安排如下：第1章，简单介绍了非完整系统的概念，归纳出非完整系统在控制上的两方面核心问题，即：不确定性及扰动的抑制问题和运动规划与控制问题。对解决这两类问题的现有方法进行了深入分析和综述，包括动态模型的在线估计共性方法、非完整约束系统运动控制方法、以及优化与预测控制方法，同时，介绍了本文作为仿真与实验对象的三体船型水面平台的发展概况。针对现有方法存在的问题有针对性地提出了本论文的研究内容。第2章，首先简要介绍了机器人学国家重点实验室与大连理工大学联合研制的三体船型水面移动机器人试验平台，作为本论文后续仿真与实验研究的对象，介绍了该平台的动力系统与控制系统。从运动控制的角度出发，综合考虑推力、水动力等对整个系统的动力学进行了分析，建立了完整的6自由度动力学模型以及水平面运动的简化模型。在此基础上，分析了三体船型水面移动机器人的非完整约束特性和能控性，为后续方法研究奠定了基础。第3章，提出了一种基于主动建模的鲁棒控制设计方法。对于包含难以准确建模动力学以及外来扰动等不确定性的系统，可以将其动力学模型合理简化，而将所有不确定因素以模型差的形式引入到系统中；将引入的模型差与系统原有状态组合成增广状态，构造出联合估计模型；再利用在线估计方法实时估计这个模型差；同时，将估计出的模型差利用某种控制策略反馈到控制量中，达到增强系统鲁棒性的目的。针对三体船型水面移动机器人，在理论上分析了上述方法的稳定性，并在实际三体船型水面机器人上开展了实验比较研究。实验结果表明此方法对系统中存在的各种不确定因素具有很好的抑制作用。第4章，重点研究非线性系统在线估计以及将在线与控制相结合的问题。在简要介绍可以用于非线性估计的UKF方法的基础上，针对其性能严重依赖噪声先验知识的问题，提出了一种基于主从结构的自适应滤波器设计方法。同时针对三体船型水面机器人非线性系统模型中存在的不确定性因素，提出了一种基于自适应UKF的指数跟踪控制器设计方法。仿真结果验证了自适应UKF算法的性能提高，同时验证了基于在线估计的指数跟踪控制器对时变参数与扰动的抑制作用。第5章，研究了非完整约束系统的镇定控制问题。提出了一种高维流形嵌入法；通过把二阶非完整约束系统嵌入到高维流形中，将在原空间中镇定到一个点的问题转化成在扩展的状态空间中镇定到一个子流形的问题；从而，可以将原空间不可连续反馈镇定的控制问题转化为高维流形中可连续反馈镇定控制问题，理论上证明了该方法的正确性和完备性。针对三体船型水面移动机器人的仿真结果验证了该方法的正确性。第6章，针对非完整约束对移动机器人可执行轨迹的制约问题，提出了跟踪控制Lyapunov函数的概念，并将其引入到非完整系统地运动规划中，用跟踪控制Lyapunov函数来保证规划算法的收敛性和可执行性。该方法将非线性预测控制与基于跟踪控制Lyapunov函数的广义逐点最小范数控制相结合，得到了一种在保证闭环稳定性前提下的运动规划算法；理论上证明了该方法的正确性，并针对三体船型水面移动机器人动力学进行仿真验证。

基于混合灵敏度的水下机器人鲁棒控制研究

为了使水下机器人(AUV,autonomous underwater vehicle)在多环节不确定条件下满足水下作业时动力定位的控制精度要求,深入研究了混合灵敏度鲁棒控制中各加权函数的选取原则后,设计了基于混合灵敏度的 AUV 鲁棒控制器。通过 AUV 半物理仿真平台上的动力定位试验和控制算法对比试验,证明了所设计的鲁棒控制器对于水下机器人系统的外界扰动和参数变化不确定性具有良好的抑制作用,控制效果令人鼓舞。

一类时滞不确定非线性系统的鲁棒控制器设计

针对一类具有单输入滞后不确定非线性系统 ,采用精确反馈线性化方法和 Lyapunov方法设计出一种使系统终极有界 ( UUB)的无记忆光滑状态反馈鲁棒控制器 .仿真算例表明了本文所采用方法的有效性 .

滑动控制理论在海洋机器人动态定位系统中的应用

本文论述了一种新的鲁棒性控制方法——滑动控制理论.并将该方法应用于海洋机器人的动态定位系统设计.仿真结果表明该方法是相当成功和有效的,对系统的参数变化有强鲁棒性.

Disturbance attenuation in linear systems via dynamical compensators: A parametric eigenstructure assignment approach

A simple approach is proposed for disturbance attenuation in multivariable linear systems via dynamical output compensators based on complete parametric eigenstructure assignment. The basic idea is to minimise the H-2 norm of the disturbance-output transfer function using the design freedom provided by eigenstructure assignment. For robustness, the closed-loop system is restricted to be nondefective. Besides the design parameters, the closed-loop eigenvalues are also optimised within desired regions on the left-half complex plane to ensure both closed-loop stability and dynamical performance. With the proposed approach, additional closed-loop specifications can be easily achieved. As a demonstration, robust pole assignment, in the sense that the closed-loop eigenvalues are as insensitive as possible to open-loop system parameter perturbations, is treated. Application of the proposed approach to robust control of a magnetic bearing with a pair of opposing electromagnets and a rigid rotor is discussed.

Projetos de controladores para sistemas de potência utilizando LMI'S

A presente dissertação tem como objetivo estudar e aprimorar métodos de projetos de controladores para sistemas de potência, sendo que esse trabalho trata da estabilidade dinâmica de sistemas de potência e, portanto, do projeto de controladores amortecedores de oscilações eletromecânicas para esses sistemas. A escolha dos métodos aqui estudados foi orientada pelos requisitos que um estabilizador de sistemas de potência (ESP) deve ter, que são robustez, descentralização e coordenação. Sendo que alguns deles tiveram suas características aprimoradas para atender a esses requisitos. A abordagem dos métodos estudados foi restringida à análise no domínio tempo, pois a abordagem temporal facilita a modelagem das incertezas paramétricas, para atender ao requisito da robustez, e também permite a formulação do controle descentralizado de maneira simples. Além disso, a abordagem temporal permite a formulação do problema de projeto utilizando desigualdades matriciais lineares (LMI’s), as quais possuem como vantagem o fato do conjunto solução ser sempre convexo e a existência de algoritmos eficientes para o cálculo de sua solução. De fato, existem diversos pacotes computacionais desenvolvidos no mercado para o cálculo da solução de um problema de inequações matriciais lineares. Por esse motivo, os métodos de projeto para controladores de saída buscam sempre colocar o problema na forma de LMI’s, tendo em vista que ela garante a obtenção de solução, caso essa solução exista.

Controlador em modo dual adaptativo robusto - DMARC

The so-called Dual Mode Adaptive Robust Control (DMARC) is proposed. The DMARC is a control strategy which interpolates the Model Reference Adaptive Control (MRAC) and the Variable Structure Model Reference Adaptive Control (VS-MRAC). The main idea is to incorporate the transient performance advantages of the VS-MRAC controller with the smoothness control signal in steady-state of the MRAC controller. Two basic algorithms are developed for the DMARC controller. In the first algorithm the controller's adjustment is made, in real time, through the variation of a parameter in the adaptation law. In the second algorithm the control law is generated, using fuzzy logic with Takagi-Sugeno s model, to obtain a combination of the MRAC and VS-MRAC control laws. In both cases, the combined control structure is shown to be robust to the parametric uncertainties and external disturbances, with a fast transient performance, practically without oscillations, and a smoothness steady-state control signal

Algoritmos genéricos para otimização de uma arquitetura de controle inteligente híerárquico

A hierarchical fuzzy control scheme is applied to improve vibration suppression by using an electro-mechanical system based on the lever principle. The hierarchical intelligent controller consists of a hierarchical fuzzy supervisor, one fuzzy controller and one robust controller. The supervisor combines controllers output signal to generate the control signal that will be applied on the plant. The objective is to improve the performance of the electromechanical system, considering that the supervisor could take advantage of the different techniques based controllers. The robust controller design is based on a linear mathematical model. Genetic algorithms are used on the fuzzy controller and the supervisor tuning, which are based on non-linear mathematical model. In order to attest the efficiency of the hierarchical fuzzy control scheme, digital simulations were employed. Some comparisons involving the optimized hierarchical controller and the non-optimized hierarchical controller will be made to prove the efficiency of the genetic algorithms and the advantages of its use

Active flutter suppression in a 2-D airfoil using linear matrix inequalities techniques

Flutter is an in-flight vibration of flexible structures caused by energy in the airstream absorbed by the lifting surface. This aeroelastic phenomenon is a problem of considerable interest in the aeronautic industry, because flutter is a potentially destructive instability resulting from an interaction between aerodynamic, inertial, and elastic forces. To overcome this effect, it is possible to use passive or active methodologies, but passive control adds mass to the structure and it is, therefore, undesirable. Thus, in this paper, the goal is to use linear matrix inequalities (LMIs) techniques to design an active state-feedback control to suppress flutter. Due to unmeasurable aerodynamic-lag states, one needs to use a dynamic observer. So, LMIs also were applied to design a state-estimator. The simulated model, consists of a classical flat plate in a two-dimensional flow. Two regulators were designed, the first one is a non-robust design for parametric variation and the second one is a robust control design, both designed by using LMIs. The parametric uncertainties are modeled through polytopic uncertainties. The paper concludes with numerical simulations for each controller. The open-loop and closed-loop responses are also compared and the results show the flutter suppression. The perfomance for both controllers are compared and discussed. Copyright © 2006 by ABCM.

A genetic neuro-model reference adaptive controller for petroleum wells drilling operations

Motivated by rising drilling operation costs, the oil industry has shown a trend towards real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated to parameters modeling. One of the drill-bit performance evaluators, the Rate of Penetration (ROP), has been used in the literature as a drilling control parameter. However, the relationships between the operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on the Auto-Regressive with Extra Input Signals model, or ARX model, to accomplish the system identification and on a Genetic Algorithm (GA) to provide a robust control for the ROP. Results of simulations run over a real offshore oil field data, consisted of seven wells drilled with equal diameter bits, are provided. © 2006 IEEE.