Robust adaptive control for mobile manipulators

This paper addresses the trajectory tracking control of a nonholonomic wheeled mobile manipulator with parameter uncertainties and disturbances. The proposed algorithm adopts a robust adaptive control strategy where parametric uncertainties are compensated by adaptive update techniques and the disturbances are suppressed. A kinematic controller is first designed to make the robot follow a desired end-effector and platform trajectories in task space coordinates simultaneously. Then, an adaptive control scheme is proposed, which ensures that the trajectories are accurately tracked even in the presence of external disturbances and uncertainties. The system stability and the convergence of tracking errors to zero are rigorously proven using Lyapunov theory. Simulations results are given to illustrate the effectiveness of the proposed robust adaptive control law in comparison with a sliding mode controller.     

非完整移动机器人的神经网络鲁棒自适应控制

在非完整移动机器人轨迹跟踪问题中,针对机器人运动学与动力学模型的参数和非参数不确定性,提出了一种混合神经网络鲁棒自适应轨迹跟踪控制器,该控制器由运动学控制器和动力学控制器两部分组成;其中,采用了参数自适应的径向基神经网络对运动学模型的未知部分进行了建模,并采用权值在线调整的单层神经网络和自适应鲁棒控制项构成了动力学控制器;基于Lyapunov方法的设计过程保证了系统的稳定性和收敛性,仿真结果证明了算法的有效性。     

Robust adaptive tracking control of robotic systems with uncertainties

To deal with the uncertainty factors of robotic systems, a robust adaptive tracking controller is proposed. The knowledge of the uncertainty factors is assumed to be unidentified; the proposed controller can guarantee robustness to parametric and dynamics uncertainties and can also reject any bounded, immeasurable disturbances entering the system. The stability of the proposed controller is proven by the Lyapunov method. The proposed controller can easily be implemented and the stability of the closed system can be ensured; the tracking error and adaptation parameter error are uniformly ultimately bounded （UUB）. Finally, some simulation examples are utilized to illustrate the control performance.     

Observer‐based adaptive robust control of a class of nonlinear systems with dynamic uncertainties

In this paper, a discontinuous projection‐based adaptive robust control (ARC) scheme is constructed for a class of nonlinear systems in an extended semi‐strict feedback form by incorporating a nonlinear observer and a dynamic normalization signal. The form allows for parametric uncertainties, uncertain nonlinearities, and dynamic uncertainties. The unmeasured states associated with the dynamic uncertainties are assumed to enter the system equations in an affine fashion. A novel nonlinear observer is first constructed to estimate the unmeasured states for a less conservative design. Estimation errors of dynamic uncertainties, as well as other model uncertainties, are dealt with effectively via certain robust feedback control terms for a guaranteed robust performance. In contrast with existing conservative robust adaptive control schemes, the proposed ARC method makes full use of the available structural information on the unmeasured state dynamics and the prior knowledge on the bounds of parameter variations for high performance. The resulting ARC controller achieves a prescribed output tracking transient performance and final tracking accuracy in the sense that the upper bound on the absolute value of the output tracking error over entire time‐history is given and related to certain controller design parameters in a known form. Furthermore, in the absence of uncertain nonlinearities, asymptotic output tracking is also achieved. Copyright © 2001 John Wiley & Sons, Ltd.     

Nonlinear asymptotic attitude tracking control of an underactuated 3-degree-of-freedom helicopter using neural network feedforward term

This paper proposes a new asymptotic attitude tracking controller for an underactuated 3-degree-of-freedom (DOF) laboratory helicopter system by using a nonlinear robust feedback and a neural network (NN) feedforward term. The nonlinear robust control law is developed through a modified inner-outer loop approach. The application of the NN-based feedforward is to compensate for the system uncertainties. The proposed control design strategy requires very limited knowledge of the system dynamic model, and achieves good robustness with respect to system parametric uncertainties. A Lyapunov-based stability analysis shows that the proposed algorithms can ensure asymptotic tracking of the helicopter’s elevation and travel motion, while keeping the stability of the closed-loop system. Real-time experiment results demonstrate that the controller has achieved good tracking performance.     

Model reference tracking control of an aircraft: a robust adaptive approach

This work presents the design and the corresponding analysis of a nonlinear robust adaptive controller for model reference tracking of an aircraft that has parametric uncertainties in its system matrices and additive state- and/or time-dependent nonlinear disturbance-like terms in its dynamics. Specifically, robust integral of the sign of the error feedback term and an adaptive term is fused with a proportional integral controller. Lyapunov-based stability analysis techniques are utilised to prove global asymptotic convergence of the output tracking error. Extensive numerical simulations are presented to illustrate the performance of the proposed robust adaptive controller.     

未知不确定非线性系统的直接自校正滑模控制

针对一类具有未知不确定性的非线性系统,提出一种参数直接自校正滑模控制方法.将系统的非线性、参数变化和外部干扰都视作系统不确定性,控制器的设计无需不确定项的上下界等信息:为改善跟踪性能与减小输入抖振,控制器设计中引入可调边界层厚度的双极性sigmoid函数与可变滑模切换增益,推导出控制增益和边界层厚度的直接自校正律,并基于Lyapunov判据给出了闭环系统稳定性证明.仿真实例证明了该方法的有效性和正确性.     

A robust constrained control approach for flexible air‐breathing hypersonic vehicles

This article investigates the robust adaptive control system design for the longitudinal dynamics of a flexible air‐breathing hypersonic vehicle (FAHV) subject to parametric uncertainties and control input constraints. A combination of back‐stepping and nonlinear disturbance observer (NDO) is utilized for exploiting an adaptive output‐feedback controller to provide robust tracking of velocity and altitude reference trajectories in the presence of flexible effects and system uncertainties. The dynamic surface control is introduced to solve the problem of “explosion of terms.” A new NDO is developed to guarantee the proposed controller's disturbance attenuation ability and to performance robustness against uncertain aerodynamic coefficients. To deal with the problem of actuator saturation, a novel auxiliary system is exploited to compensate the desired control laws. The stability of the presented NDO and controller is analyzed. Simulation results are given to demonstrate the effectiveness of the presented control strategy.     

基于期望轨迹补偿的机器人鲁棒自适应控制

针对机器人存在的参数不确定性和外扰的问题,提出了一种基于期望轨迹补偿和自适应控制的方法,在传统自适应控制方法的基础上,结合变结构控制方法,设计了一种新的控制策略.该方法采用期望轨迹补偿,离线计算回归矩阵,可以有效节约控制系统在线计算的时间,实时性好,并利用变结构思想补偿非线性摩擦和外界干扰,利用lyapunov直接法分...     

Dynamical adaptive integral backstepping variable structure controller design for uncertain systems and experimental application

In this study, a dynamical adaptive integral backstepping variable structure control (DAIBVSC) system based on the Lyapunov stability theorem is proposed for the trajectory tracking control of a nonlinear uncertain mechatronic system with disturbances. In this control scheme, no prior knowledge is required on the uncertain parameters and disturbances because it is estimated by two types of dynamical adaptive laws. These adaptive laws are integrated into the dynamical adaptive integral backstepping control and variable structure control (VSC) parts of the DAIBVSC. The dynamical adaptive law in the dynamical adaptive integral backstepping control part updates parametric uncertainties, while the other in the VSC part adapts upper bounds of non‐parametric uncertainties and disturbances. In order to achieve a more robust output tracking and better parameter adaptation, the control system is extended by one integrator and sliding surface is augmented by an integral action. Experimental evaluation of the DAIBVSC is conducted with respect to performance and robustness to parametric uncertainties. Experimental results of the DAIBVSC are compared with those of a traditional VSC. The proposed DAIBVSC exhibits satisfactory output tracking performance, good estimation of the uncertain parameters and can reject disturbances with a chattering free control law. Copyright © 2017 John Wiley & Sons, Ltd.     

Adaptive Backstepping Tracking Control of a 6-DOF Unmanned Helicopter

This paper presents an adaptive backstepping control design for a class of unmanned helicopters with parametric uncertainties. The control objective is to let the helicopter track some pre-defined position and yaw trajectories. In order to facilitate the control design, we divide the helicopter's dynamic model into three subsystems. The proposed controller combines the backstepping method with online parameter update laws to achieve the control objective. The global asymptotical stability (GAS) of the closed-loop system is proved by a Lyapunov based stability analysis. Numerical simulations demonstrate that the controller can achieve good tracking performance in the presence of parametric uncertainties.      

On the Robust Nonlinear Motion Position and Force Control of Flexible Joints Robot Manipulators

The design of a robust nonlinear position and force controller for a flexible joints robot manipulator interacting with a rigid environment is presented. The controller is designed using the concept of feedback linearization, sliding mode techniques, and LQE estimation methodologies. It is shown that the nonlinear robot manipulator model is feedback linearizable. A robust performance of the proposed control approach is achieved by accounting for the system parameters uncertainties in the derivation of the nonlinear control law. An upper bound of the error introduced by parametric uncertainties in the system is computed. Then, the feedback linearizing control law is modified by adding a switching action to compensate the errors and to guarantee the achievement of the desired tracking performance. The relationship between the minimum achievable boundary layer thickness and the parametric uncertainties is derived. The proposed controller is tested using an experimental flexible joints robot manipulator, and the results demonstrate its potential benefits in reducing the number of sensors required and the complexity of the design. This is achieved by eliminating the need for nonlinear observers. A robust performance is obtained with minimum control effort by taking into account the effect of system parameter uncertainties and measurement noise.     

Robust output tracking control of a laboratory helicopter for automatic landing

In this paper, robust output tracking control problem of a laboratory helicopter for automatic landing in high seas is investigated. The motion of the helicopter is required to synchronise with that of an oscillating platform, e.g. the deck of a vessel subject to wave-induced motions. A robust linear time-invariant output feedback controller consisting of a nominal controller and a robust compensator is designed. The robust compensator is introduced to restrain the influences of parametric uncertainties, nonlinearities and external disturbances. It is shown that robust stability and robust tracking property can be achieved simultaneously. Experimental results on the laboratory helicopter for automatic landing demonstrate the effectiveness of the designed control approach.     

Nonlinear robust adaptive Cartesian impedance control of UAVs equipped with a robot manipulator

In this paper, a new nonlinear robust adaptive impedance controller is addressed for Unmanned Aerial Vehicles (UAVs) equipped with a robot manipulator that physically interacts with environment. A UAV equipped with a robot manipulator is a novel system that can perform different tasks instead of human being in dangerous and/or inaccessible environments. The objective of the proposed robust adaptive controller is control of the UAV and its robotic manipulator’s end-effector impedance in Cartesian space in order to have a stable physical interaction with environment. The proposed controller is robust against parametric uncertainties in the nonlinear dynamics model of the UAV and the robot manipulator. Moreover, the controller has robustness against the bounded force sensor inaccuracies and bounded unstructured modeling (nonparametric) uncertainties and/or disturbances in the system. Tracking performance and stability of the system are proved via Lyapunov stability theorem. Using simulations on a quadrotor UAV equipped with a three-DOF robot manipulator, the effectiveness of the proposed robust adaptive impedance controller is investigated in the presence of the force sensor error, and parametric and non-parametric uncertainties.     

基于一类饱和函数的机器人混合鲁棒/自适应控制

提出一类不需要线性PD反馈的混合鲁棒/自适应控制策略,用于不确定性机器人的轨迹 跟踪.其控制结构由一个补偿参数不确定性的自适应控制器和补偿非参数不确定性的鲁棒控 制器构成. 其主要特点是基于一类饱和型函数,提出了一类新颖的鲁棒控制器和非线性滑动 变量的设计方法.基于Lyapunov方法的理论分析和计算机仿真,均保证设计的控制策略能够消 除系统所有的不确定性影响,并达到全局的渐近稳定.     

Neural network-based asymptotic tracking control of unknown nonlinear systems with continuous control command

ABSTRACT

This paper proposes a robust tracking controller for a class of nonlinear second-order systems with time-varying uncertainties. The controller is mainly based on the robust integral of the sign of the error (RISE) control approach to achieve an asymptotic stability result with a continuous control command in the presence of additive uncertainties. An adaptive feedforward neural network control term is blended with a new RISE controller to improve the system's transient performance. The proposed RISE controller is a modified version of the existing saturated RISE controller such that only sign of the derivative of the output is needed. The stability of the closed-loop system is well studied, where a local asymptotic stability is proven. The controller performance is validated through simulations on a two-degree-of-freedom lower limb robotic exoskeleton.     

Robust parametric CMAC with self-generating design for uncertain nonlinear systems

In this paper, a robust parametric cerebellar model articulation controller (RP-CMAC) with self-generating design, called RPCSGD, is proposed for uncertain nonlinear systems. The proposed controller consists of two parts: one is the parametric CMAC with self-generating design (PCSGD), which is utilized to approximate the ideal controller and the other is the robust controller, which is designed to achieve a specified H^∞ robust tracking performance of the system. The corresponding memory size of the proposed controller can be suitably constructed via the self-generating design. Thus, the useless or untrained memories will not take possession of the space. Besides, the concept of sliding-mode control (SMC) is adopted so that the proposed controller has more robustness against the approximated error and uncertainties. The stability of the system can be guaranteed surely due to the derivations of the adaptive laws of the proposed RPCSGD based on the Lyapunov function. Finally, the proposed controller is applied to the second-order chaotic system and the one-link rigid robotic manipulator. The tracking performance and effectiveness of the proposed controller are verified by simulations of the computer.     

Adaptive feedback linearizing control of nonholonomic wheeled mobile robots in presence of parametric and nonparametric uncertainties

In this paper, the integrated kinematic and dynamic trajectory tracking control problem of wheeled mobile robots (WMRs) is addressed. An adaptive robust tracking controller for WMRs is proposed to cope with both parametric and nonparametric uncertainties in the robot model. At first, an adaptive nonlinear control law is designed based on input–output feedback linearization technique to get asymptotically exact cancellation of the parametric uncertainty in the WMR parameters. The designed adaptive feedback linearizing controller is modified by two methods to increase the robustness of the controller: (1) a leakage modification is applied to modify the integral action of the adaptation law and (2) the second modification is an adaptive robust controller, which is included to the linear control law in the outer loop of the adaptive feedback linearizing controller. The adaptive robust controller is designed such that it estimates the unknown constants of an upper bounding function of the uncertainty due to friction, disturbances and unmodeled dynamics. Finally, the proposed controller is developed for a type (2, 0) WMR and simulations are carried out to illustrate the robustness and tracking performance of the controller.     

Robust adaptive control using a universal approximator for SISOnonlinear systems

This paper deals with the robust adaptive control of a class of nonlinear systems in the presence of parametric uncertainties and dominant uncertain nonlinearities. The proposed controller utilizes the robust adaptive control to guarantee uniform boundedness and convergence of tracking errors. In addition, an adaptive fuzzy logic system is used as a universal approximator to reduce the model uncertainties coming from uncertain nonlinearities and to improve tracking performance. The approach does not require the matching condition imposed on control systems by using the backstepping design procedure, and provides boundedness of tracking errors under poor parameter adaptation. The method can be applied to a class of single-input single-output (SISO) nonlinear systems, transformable to a parametric-strict-feedback form     

Robust output tracking control of SISO plants with multiple operating points and with parametric and unstructured uncertainties

The robust output tracking control problem is considered for single-input single-output plants with multiple operating points and with both parametric and unstructured uncertainties (i.e. interval parameter uncertainties and norm-bounded unmodelled dynamics). The parametric uncertainties can involve parameter perturbations as well as degree variations. The plant with uncertainties is assumed to be of minimum phase, but is not required to have a fixed number of unstable poles. A new method is presented by which a linear time-invariant robust controller is designed in two steps: first, a nominal controller is designed to get exact output tracking for the nominal plant; then, a robust compensator is added to achieve robust properties. It is shown that robust stability, robust static state property, robust transient property and robust tracking property can be achieved simultaneously. A computationally tractable design procedure is presented. A salient feature of our results, shown in the present paper, is that we can tell the users how to tune on-line the parameters of the controller with the proposed structure.