Adaptive output feedback control of uncertain nonlinear systems using single-hidden-layer neural networks

We consider adaptive output feedback control of uncertain nonlinear systems, in which both the dynamics and the dimension of the regulated system may be unknown. However, the relative degree of the regulated output is assumed to be known. Given a smooth reference trajectory, the problem is to design a controller that forces the system measurement to track it with bounded errors. The classical approach requires a state observer. Finding a good observer for an uncertain nonlinear system is not an obvious task. We argue that it is sufficient to build an observer for the output tracking error. Ultimate boundedness of the error signals is shown through Lyapunov's direct method. The theoretical results are illustrated in the design of a controller for a fourth-order nonlinear system of relative degree two and a high-bandwidth attitude command system for a model R-50 helicopter.     

Global approximate output tracking for nonlinear systems

Addresses the global output tracking problem for nonlinear systems with singular points. For nonlinear systems which satisfy a suitable observability condition, the authors identify a class of smooth output trajectories which the system can track using continuous open-loop controls. This class includes all output trajectories generated by smooth state feedback. They then study the problem of approximate output tracking using discontinuous time-varying feedback controllers. Given a smooth output trajectory for which exact tracking is possible, the authors construct a discontinuous feedback controller which achieves robust tracking of the desired output trajectory in the face of perturbations. Finally, it is shown that their results can be applied to the control of a chain system, and some numerical results are presented to illustrate the performance of their controller     

柔性机械臂基于观测的逆动力学轨迹跟踪控制

本文探讨了稳定逆动力学与基于观测的状态误差反馈镇定器集成实现柔性机械臂 末端轨迹跟踪的控制策略．基于观测器可以充分利用由稳定逆动力学生成的理想状态轨迹信 息,实现全状态误差的反馈镇定以消除末端轨迹跟踪的扰动误差．     

轮式移动机器人的位置量测输出反馈轨迹跟踪控制

针对机器人的姿态角难以精确测量的困难,本文研究基于位置测量的轮式移动机器人的轨迹跟踪问题.首先提出一种利用机器人的位置信息估计其姿态角的降维状态观测器,当机器人的线速度严格大于零时,可保证姿态角观测误差的指数收敛.然后给出一种新的状态反馈轨迹跟踪控制律,当参考轨迹满足一定的激励条件时,可以保证机器人的线速度严格大于零且跟踪误差全局渐近收敛.进一步结合姿态角观测器和状态反馈控制律,得到一种输出反馈轨迹跟踪控制算法.理论分析表明,当参考轨迹满足一定的激励条件时,所提出的输出反馈控制算法可以保证跟踪误差的全局渐近收敛.最后对所提出的姿态角观测器、状态反馈和输出反馈轨迹跟踪控制算法进行了仿真验证,证实了算法的有效性,并且当存在位置测量误差时,所提出的输出反馈轨迹跟踪控制算法仍可以保证机器人对参考轨迹的实际跟踪.     

Results on the Robust Observer-based Position Controller for Parallel Kinematic Machines

The problem of state observation and position control by output feedback for a nonlinear three degrees-of-freedom (3-DOF) parallel kinematic machine (PKM) system is considered, based on the limited signal availability (only the moving platform displacement measurements are assumed available). Unknown velocity signals are estimated via a nonlinear robust observer that is designed for the nonlinear system with observable linear dynamics part and bounded nonlinearities and disturbances, and that guarantees global exponential stability of the observation error. A proportional-derivative (PD) controller is designed to solve the position control problem, utilizing the estimated velocity, as well as the gravitation compensation, dynamic friction and external disturbance compensation for the PKM. The closed-loop system is proven to have global asymptotical stability according to the Lyapunov analysis method and LaSalle’s invariance principle. Performance of the resulting observer and controller is illustrated in a simulation study of a 3-DOF PKM. Modifications to the nonlinear observer and control law are discussed, that assure convergence of the position error and state observation error to zero when the upper bounds on the model uncertainties/disturbances are not known a priori.     

Flatness-based linear output feedback control for disturbance rejection and tracking tasks on a Chua's circuit

A linear output feedback controller is developed for trajectory tracking problems defined on a modified version of Chua's circuit. The circuit modification considers the introduction of a flat input, i.e. a suitable external control input channel guided by (a) the induction of the flatness property on a measurable output signal of the circuit and (b) the physical viability of the control input. A linear active disturbance rejection control based on a high-gain linear disturbance observer, is implemented on a laboratory prototype. We show that the state-dependent disturbance can be approximately, but arbitrarily closely, estimated through a linear high-gain observer, called a generalised proportional integral (GPI) observer, which contains a linear combination of a sufficient number of extra iterated integrals of the output estimation error. Experimental results are presented in the output reference trajectory tracking of a signal generated by an unrelated chaotic system of the Lorenz type. Laboratory experiments illustrate the proposed linear methodology for effectively controlling chaos.     

Output Feedback Adaptive Neural Control Without Seeking SPR Condition

For output‐feedback adaptive control of affine nonlinear systems based on feedback linearization and function approximation, the observation error dynamics usually should be augmented by a low‐pass filter to satisfy a strictly positive real (SPR) condition so that output feedback can be realized. Yet, this manipulation results in filtering basis functions of approximators, which makes the order of the controller dynamics very large. This paper presents a novel output‐feedback adaptive neural control (ANC) scheme to avoid seeking the SPR condition. A saturated output‐feedback control law is introduced based on a state‐feedback indirect ANC structure. An adaptive neural network (NN) observer is applied to estimate immeasurable system state variables. The output estimation error rather than the basis functions is filtered and the filter output is employed to update NNs. Under given initial conditions and sufficient control parameter constraints, it is proved that the closed‐loop system is uniformly ultimately bounded stable in the sense that both the state estimation errors and the tracking errors converge to small neighborhoods of zero. An illustrative example is provided to demonstrate the effectiveness of this approach.     

仿人机器人相似性运动轨迹跟踪控制研究

提出一种基于带观测器的条件状态反馈控制的仿人机器人相似性运动轨迹跟踪控制方法.首先,分析了7连杆双足机器人动力学模型,阐述了其运动能量方程与动力学特征方程; 其次,基于带观测器的状态反馈控制器原理,构建起三维倒立摆平衡控制模型; 最后,由线性二次型调节器确定状态反馈增益矩阵,使机器人轨迹跟踪误差最小化,以复现出较高相似度的双足步行运动效果.实验验证了该方法的有效性.     

Application of the dynamic high‐gain scaling methodology to servocompensator design

The error‐feedback servomechanism problem is addressed for a general class of strict‐feedback‐like systems. We provide two error‐feedback control designs based on our recent results on adaptive output‐feedback based on dynamic high‐gain scaling. One control design is of a dual high‐gain observer/controller structure, whereas the other control design utilizes a backstepping‐based controller in conjunction with a dynamic high‐gain scaling‐based observer. Owing to the particular robustness properties offered by a dynamic high‐gain scaling‐based controller and a backstepping‐based controller, the two designs require slightly different sets of assumptions on the system. Both design techniques allow the system to contain both unknown functions and uncertain appended input‐to‐state stable dynamics. Copyright © 2008 John Wiley & Sons, Ltd.     

Robust control with uncertainty estimation for feedback linearizable systems: application to control of distillation columns

The goal of this paper is to describe a linearizing feedback adaptive control structure which leads to a high quality regulation of the output error in the presence of uncertainties and external disturbances. The controller consists of three elements: a nominal input–output linearizing compensator, a state observer and an uncertainty estimator, which provides the adaptive part of the control structure. In this way, the feedback controller, based on the disturbance observer, compensates for external disturbances and plant uncertainties. The effectiveness of the controller is demonstrated on a distillation column via numerical simulations. ©     

Nonlinear adaptive output feedback control of series resonant DC–DC converters

The problem of regulating the output voltage of DC-to-DC series resonant converters (SRC) is addressed. The difficulty is threefold: (i) the converter model involves discontinuous and highly nonlinear terms and is controlled through a modulating frequency signal; (ii) all state variables are not accessible to measurements; (iii) the load is uncertain and may even be varying. An adaptive output feedback controller, involving online state variable estimation, is designed and shown to ensure quite satisfactory tracking performances. The controller development is performed using the adaptive backstepping control approach combined with the high-gain observer design technique.     

Robot control by using only joint position measurements

An observer for reconstructing the joint velocities of rigid-joint robots is proposed. The approach consists of exploiting the structural properties of the robot dynamics. The associated error dynamics are shown to be asymptotically stable. The observer furnishes the state estimate directly in the physical coordinates, so that no transformation is needed. The stability of some state feedback controllers having the proposed observer inserted in the feedback loop is proved. The structure of the observer and its convergence are shown. The stability of the whole system is analyzed when the observer is used in connection with a point-to-point controller and a trajectory controller     

An improved state-space model structure and a corresponding predictive functional control design with improved control performance

Conventional state-space model predictive control requires a state estimator/observer to access the state information for feedback controller design. Its drawbacks are the numerical convergence stability of the observer and closed-loop control performance deterioration with activated plant input/output constraints. The recent direct use of measured input and output variables to formulate a non-minimal state-space (NMSS) model overcomes these problems, but the subsequent controller is too sensitive to model mismatch. In this article, an improved structure of NMSS model that incorporates the output-tracking error is first formulated and then a subsequent predictive functional control design is proposed. The proposed controller is tested on both model match and model mismatch cases for comparison with previous controllers. Results show that control performance is improved. In addition, a linear programming method for constraints dealing and a closed form of transfer function representation of the control system are provided for further insight into the proposed method.     

Fuzzy neural network quadratic stabilization output feedback control for biped robots via H/sub /spl infin// approach

A novel fuzzy neural network (FNN) quadratic stabilization output feedback control scheme is proposed for the trajectory tracking problems of biped robots with an FNN nonlinear observer. First, a robust quadratic stabilization FNN nonlinear observer is presented to estimate the joint velocities of a biped robot, in which an H/sub /spl infin// approach and variable structure control (VSC) are embedded to attenuate the effect of external disturbances and parametric uncertainties. After the construction of the FNN nonlinear observer, a quadratic stabilization FNN controller is developed with a robust hybrid control scheme. As the employment of a quadratic stability approach, not only does it afford the possibility of trading off the design between FNN, H/sub /spl infin// optimal control, and VSC, but conservative estimation of the FNN reconstruction error bound is also avoided by considering the system matrix uncertainty separately. It is shown that all signals in the closed-loop control system are bounded.     

含不匹配扰动非严格反馈系统的输出反馈补偿控制

针对一类非严格反馈非线性系统,系统中包含不确定函数和未知外部扰动,提出一种带不匹配扰动补偿的输出反馈模糊控制器.采用模糊逻辑系统逼近未知的非线性函数,同时构造模糊状态观测器观测系统未知状态.考虑观测器和控制器会受到外部扰动和模糊逼近误差构成的不匹配总扰动信号影响,采用改进的扰动观测器对不匹配扰动进行估计和补偿,使扰动观测误差能够在有限时间内平缓地收敛到任意小的范围,消除不匹配扰动信号对模糊观测器设计的影响.同时在控制器设计中进行扰动的精确补偿,提高系统的抗扰动性.通过Lyapunov函数证明了闭环系统所有信号都是有界的.最后,通过数值仿真进一步验证了所提出方法的有效性.     

Global finite-time stabilization by dynamic output feedback for a class of continuous nonlinear systems

This note studies the problem of global finite-time stabilization by dynamic output feedback for a class of continuous but nonsmooth nonlinear systems. By extending the adding-a-power-integrator technique and a special continuous observer design, a dynamic output feedback controller is explicitly constructed to render the systems globally finite-time stable. The novelty of the note is the development of a recursive design procedure, which takes full advantage of the continuous structure of the systems in constructing the state feedback stabilizer and the continuous observer with rigorously selected gains.     

Adaptive dynamical variable structure feedback regulation for nonlinear uncertain systems

In this article an adaptive discontinuous dynamical feedback strategy is presented for asymptotic output stabilization problems defined on nonlinear controlled systems exhibiting linear parametric uncertainty. A dynamical feedback controller, ideally achieving output stabilization via exact linearization, is obtained by means of output differentiation and sliding mode control ideas. The adaptive version of the dynamical variable structure controller is then obtainable via standard, direct, overparametrized adaptive control techniques available for linearizable systems through static state feedback. An illustrative example from the chemical process control area, including simulations, is provided.     

Observer-based fault tolerant control for a class of nonlinear multi-agent systems with sensor faults

This article focuses on the robust fault tolerant control (FTC) problem for a class of Lipschitz nonlinear multi-agent systems(MASs) subject to sensor faults. Firstly, sensor faults are transformed into actuator faults via introducing a new intermediate auxiliary state variable, and a distributed adaptive fault estimation observer is designed to estimate the state information and the concerned faults by using the relative output estimation error. Then, the sufficient existence conditions for the observer to satisfy the robust performance index are given. Thirdly, based on the results of observer design, a new design method of dynamic output feedback controller is proposed to implement consensus of MASs and ensure the desired disturbance rejection performance. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.     

A new controller design for a flexible one-link manipulator

A novel controller design for noncollocated flexible one-link manipulator arm tip position control based on variable structure sliding mode control is presented. Using the assumed-mode method, the plant model is derived. The discontinuous control law based on the variable structure system theory for the noncollocated manipulator tip position control is then designed. The position state variables are obtained directly from the inversion of the output submatrix multiplied by the sensor measurements. The velocity state variables are estimated through decoupled estimators-a separate first-order observer for each of the system's modes under consideration. Different sampling periods are used for the estimator and the controller. The performance of the controller is evaluated through a series of simulations, followed by an analysis of the designed control system