Active vibration control of a fluid/plate system using a pole placement controller

We consider the problem of active reduction of the structural vibrations induced by the sloshing of large masses of fuel inside a partly full tank. The proposed study focuses on an experimental device mimicking an aircraft wing made of an aluminium rectangular plate equipped with piezoelectric patches at the clamped end and with a cylindrical tip tank, more or less filled with liquid. After deriving a representative finite-dimensional model of the complete system, containing the first five structural modes of the plate and the first three liquid sloshing modes, a controller is computed. Since our main scope is to control the most energetic mode of the structure, a full state-feedback method coupled with an observer is used. Finally, the controller is also tested for different initial conditions/perturbations and the results are compared with the ones obtained with an H _∞ controller. Experimental results illustrate the relevance of the chosen strategy.     

Adaptive back-stepping pitch angle control for wind turbine based on a new electro-hydraulic pitch system

A new electro-hydraulic pitch system is proposed to smooth the output power and drive-train torque fluctuations for wind turbine. This new pitch system employs a servo-valve-controlled hydraulic motor to enhance pitch control performances. This pitch system is represented by a state-space model with parametric uncertainties and nonlinearities. An adaptive back-stepping pitch angle controller is synthesised based on this state-space model to accurately achieve the desired pitch angle control regardless of such uncertainties and nonlinearities. This pitch angle controller includes a back-stepping procedure and an adaption law to deal with such uncertainties and nonlinearities and hence to improve the final pitch control performances. The proposed pitch system and the designed pitch angle controller have been validated for achievable and efficient power and torque regulation performances by comparative experimental results under various operating conditions.     

高阶耦合机器人的自适应模糊滑模分散控制

针对一类存在模型不确定性和未知非线性扰动的机器人系统,考虑其不确定项和未知扰动项的上界是关于系统状态的普通高阶多项式,结合模糊系统的逼近能力,提出了一种基于滑模控制原理的自适应模糊分散控制方法.该方法不仅能够使得关节之间相互耦合的机器人各关节的控制器仅由本关节的信息就能完全确定,而且消除了现存文献在设计机器人分散控制器...     

Adaptive synchronization control of networked robot systems without velocity measurements

This paper addresses the adaptive synchronization control problem of networked robot systems characterized by the Lagrangian function, where exact dynamic models are unknown and velocity measurements are unavailable. A class of distributed observers, comprised of multiple dynamic variables and static variables, are established based on no a priori restriction on the boundness of the observer states. The observer is compatible for different control schemes with or without structure uncertainties. Using the estimated states given by the observer, adaptive distributed control input is developed, and then, closed‐loop dynamic models for filtered vectors are established. It is proven that our proposed control scheme permits global exact state estimation and global asymptotic synchronization while compensating for structure uncertainties. Simulations are provided to demonstrate the effectiveness of the results.     

Dominant pole placement for multi-loop control systems

This paper proposes a method for multi-loop PI controller design which can achieve dominant pole placement for two input two output processes. It is an extension of the original dominant pole design (PID Controllers: Theory, Design, and Tuning, Instrument Society of America, Research Triangle park, NC, 1995.) for SISO systems. Unlike its SISO counterpart, where the controller parameters can be obtained analytically, the multi-loop version amounts to solving some coupled nonlinear equation with complex coefficients, for which closed-form formulae are not possible. A novel approach is developed to solve the equation using a “root trajectory” method, in which the solution to our pole placement problem is found from intersection points between the “root trajectories” and the positive real axis. The design procedure is given and simulation examples are provided to show the effectiveness of the proposed method and comparisons are made with the BLT method.     

不确定机器人的自适应神经网络控制与学习

针对具有未知动态的电驱动机器人,研究其自适应神经网络控制与学习问题.首先,设计了稳定的自适应神经网络控制器,径向基函数(RBF)神经网络被用来逼近电驱动机器人的未知闭环系统动态,并根据李雅普诺夫稳定性理论推导了神经网络权值更新律.在对回归轨迹实现跟踪控制的过程中,闭环系统内部信号的部分持续激励(PE)条件得到满足.随着PE条件的满足,设计的自适应神经网络控制器被证明在稳定的跟踪控制过程中实现了电驱动机器人未知闭环系统动态的准确逼近.接着,使用学过的知识设计了新颖的学习控制器,实现了闭环系统稳定、改进了控制性能.最后,通过数字仿真验证了所提控制方法的正确性和有效性.     

基于线驱转向的仿蝴蝶扑翼飞行机器人系统设计与控制

作为一种新型飞行机器人, 仿蝴蝶扑翼飞行机器人模仿自然界蝴蝶的生物结构和飞行方式, 能够有效地融入并适应复杂环境, 在军民融合领域具有广阔的应用前景. 目前针对仿蝴蝶扑翼飞行机器人的研究大多停留在对生物蝴蝶飞行机理的研究, 鲜有能够实现自由可控飞行的机器人系统. 本文设计了一款基于线驱转向的仿蝴蝶扑翼飞行机器人, 名为USTButterfly-S, 其翼展50 cm, 重50 g, 可实现长达5分钟的自由可控飞行. 首先结合生物蝴蝶翅膀的扑动特征, 设计了双曲柄双摇杆对称扑翼驱动机构. 然后模仿凤蝶的翅翼形状, 设计了仿蝴蝶翼型. 对翅膀的几何学分析表明, USTButterfly-S的翅膀与凤蝶具有较好的形态相似性. 接着针对仿蝴蝶扑翼飞行机器人的转向控制问题,首次采用线驱动机构拉动翅膀调节翅翼面积, 进而实现了USTButterfly-S的无尾航向控制. 最后集成自主设计的飞控系统, USTButterfly-S能够实现室内盘旋飞行并进行实时航拍. 在实际飞行实验中, USTButterfly-S展现出类似生物蝴蝶的飞行特征.     

Feedback norm minimisation with regional pole placement

This article proposes a convex algorithm for minimising an upper bound of the state feedback gain matrix norm with regional pole placement for linear time-invariant multi-input systems. The inherent non-convexity in this optimisation is resolved by a combination of two separate approaches: (1) an inner convex approximation of the polynomial matrix stability region due to Henrion and (2) a novel convex parameterisation of column reduced matrix fraction system representations. Using a sequence of approximations enabled by the above two methods, it is shown that the constraints on closed-loop poles (both pre-specified exact locations and regional placement) define linear matrix inequalities. Finally, the effectiveness of the proposed algorithm is compared with similar pole placement algorithms through numerical examples.     

具有传感器故障的可靠圆盘极点配置

针对线性定常系统，提出了考虑传感器故障的指定圆盘极点配置可靠控制问题，在考虑更一般、更实际的传感器故障模型的基础上，给出了系统将极点配置到指定圆盘内的充分条件，通过求解LMI完成状态反馈控制器的设计，仿真例子验证了该结果的可行性，并进一步说明了对系统进行可靠设计的必要性。     

基于Fuzzy–CPG的双足机器人适应性行走控制

为提高双足机器人的环境适应性,本文提出了一种基于模糊控制与中枢模式发生器(CPG)的混合控制策略,称之为Fuzzy–CPG算法.高层控制中枢串联模糊控制系统,将环境反馈信息映射为行走步态信息和CPG幅值参数.低层控制中枢CPG根据高层输出命令产生节律性信号,作为机器人的关节控制信号.通过机器人运动,获取环境信息并反馈给高层控制中枢,产生下一步的运动命令.在坡度和凹凸程度可变的仿真环境中进行混合控制策略的实验验证,结果表明,本文提出的Fuzzy–CPG控制方法可以使机器人根据环境的变化产生适应的行走步态,提高了双足机器人的环境适应性行走能力.     

机器人自适应PID饱和输出反馈控制

针对机器人系统在仅有位置传感、驱动器饱和、存在建模不确定性及干扰等条件下的轨迹跟踪控制问题,提出了一种新的自适应PID控制方案。采用高精度滤波器估计机器人关节速度,采用带饱和函数的控制器限制输出力矩,采用自适应PID控制器补偿建模不确定性和干扰。通过Lyapunov直接法,证明系统的稳定性。最后以两关节机器人为例,给出仿真实验结果,验证了算法的有效性。     

Output feedback pole placement for linear time-varying systems with application to the control of nonlinear systems

The output feedback pole placement problem is solved in an input-output algebraic formalism for linear time-varying (LTV) systems. The recent extensions of the notions of transfer matrices and poles of the system to the case of LTV systems are exploited here to provide constructive solutions based, as in the linear time-invariant (LTI) case, on the solutions of diophantine equations. Also, differences with the results known in the LTI case are pointed out, especially concerning the possibilities to assign specific dynamics to the closed-loop system and the conditions for tracking and disturbance rejection. This approach is applied to the control of nonlinear systems by linearization around a given trajectory. Several examples are treated in detail to show the computation and implementation issues.     

直接辨识扰动模型的内模极点配置自适应控制

给出了直接在辨识器中估计扰动模型和过程模型参数的算法,扰动模型用于极点配置自适应控制,根据内部模型原理消除未知确定扰动.由于使用了与常规方法不同的观测向量,因而省去了分离扰动模型的计算过程.这种方法可适用于多个扰动频率的情况,且辨识器的阶数不超过常规辨识器.分析了参数的可辨识性和系统的稳定性.     

线性离散系统具有闭环极点约束的输出反馈H∞ 控制

对一类线性离散系统, 研究了具有闭环圆盘极点约束的输出反馈H_∞ 控制问题. 基于线性矩阵不等式处理方法, 导出了输出反馈控制器的存在条件和设计方法. 和现有方法相比, 本文的方法具有更小的保守性.     

基于多模型切换的多变量直接自适应极点配置控制器

提出一种基于多模型切换的多变量直接自适应控制器,控制器参数模型集可由系统参数模型集直接得到,不但仍为一紧集并且被其模型子集完全覆盖.该多模型控制器不仅改善了控制系统的暂态响应,而且可以实现极点配置,最后给出了全局收敛性分析.     

Adaptive pole placement control of MIMO systems

An adaptive pole-assignment controller design for an MIMO (multi-input-multi-output) system is with unknown observability indexes or with an overparameterized system model is presented. The controller design algorithm and stability issues are addressed     

Two adaptive control structures of robot manipulators

This paper proposes two simple adaptive control schemes of robot manipulators. The first one is the state feedback control which consists of feedforward from the desired position trajectory, PD feedback from the actual trajectory, and an auxiliary input. The second one is the feedforward/feedback control which consists of a feedforward term from the desired position, velocity, and acceleration trajectory based on the inverse of robot dynamics. The feedforward, feedback, and auxiliary gains are adapted using simple equations derived from the decentralized adaptive control theory based on Lyapunov's direct method, and using only the local information of the corresponding joint. The proposed control schemes are computationally fast and do not require a priori knowledge of the detail parameters of the manipulator or the payload. Simulation results are presented in support of the proposed schemes. The results demonstrate that both controllers perform well with bounded adaptive gains.     

Fuzzy pole placement based on piecewise Lyapunov functions

This paper presents a controller design method for fuzzy dynamic systems based on piecewise Lyapunov functions with constraints on the closed‐loop pole location. The main idea is to use switched controllers to locate the poles of the system to obtain a satisfactory transient response. It is shown that the global fuzzy system satisfies the requirements for the design and that the control law can be obtained by solving a set of linear matrix inequalities, which can be efficiently solved with commercially available softwares. An example is given to illustrate the application of the proposed method. Copyright © 2009 John Wiley & Sons, Ltd.     

Voltage-based adaptive impedance force control for a lower-limb rehabilitation robot

This paper presents a novel voltage-based adaptive impedance force control for a lower limb rehabilitation robot. The impedance parameters are adaptively regulated by a gradient descent algorithm for adjusting the human force in performing therapeutic exercises. Although the proposed control is based on voltage control strategy, it differs from the common torque control strategy. One of the advantages is that it is free from the dynamical models of the robot and patient. Compared with a torque control scheme, it is simpler, less computational, and more efficient while it considers the actuators. The control approach is verified by stability analysis. Simulation results show the efficiency of the control approach applied on a lower limb rehabilitation robot driven by an electric motor. A comparison on performing isometric exercise shows that the voltage-based adaptive impedance force control is superior to both voltage-based impedance control and torque-based impedance control.     

Adaptive hybrid force/position control of robot manipulators using an adaptive force estimator in the presence of parametric uncertainty

This study is devoted to sensorless adaptive force/position control of robot manipulators using a position-based adaptive force estimator (AFE) and a force-based adaptive environment compliance estimator. Unlike the other sensorless method in force control that uses disturbance observer and needs an accurate model of the manipulator, in this method, the unknown parameters of the robot can be estimated along with the force control. Even more, the environment compliance can be estimated simultaneously to achieve tracking force control. In fact, this study deals with three challenging problems: No force sensor is used, environment stiffness is unknown, and some parametric uncertainties exist in the robot model. A theorem offers control laws and updating laws for two control loops. In the inner loop, AFE estimates the exerted force, and then, the force control law in the outer loop modifies the desired trajectory of the manipulator for the adaptive tracking loop. Besides, an updating law updates the estimated compliance to provide an accurate tracking force control. Some experimental results of a PHANToM Premium robot are provided to validate the proposed scheme. In addition, some simulations are presented that verify the performance of the controller for different situations in interaction.