Robust adaptive precision motion control of hydraulic actuators with valve dead-zone compensation

This paper addresses the high performance motion control of hydraulic actuators with parametric uncertainties, unmodeled disturbances and unknown valve dead-zone. By constructing a smooth dead-zone inverse, a robust adaptive controller is proposed via backstepping method, in which adaptive law is synthesized to deal with parametric uncertainties and a continuous nonlinear robust control law to suppress unmodeled disturbances. Since the unknown dead-zone parameters can be estimated by adaptive law and then the effect of dead-zone can be compensated effectively via inverse operation, improved tracking performance can be expected. In addition, the disturbance upper bounds can also be updated online by adaptive laws, which increases the controller operability in practice. The Lyapunov based stability analysis shows that excellent asymptotic output tracking with zero steady-state error can be achieved by the developed controller even in the presence of unmodeled disturbance and unknown valve dead-zone. Finally, the proposed control strategy is experimentally tested on a servovalve controlled hydraulic actuation system subjected to an artificial valve dead-zone. Comparative experimental results are obtained to illustrate the effectiveness of the proposed control scheme.     

含磁滞补偿的电液伺服系统预设性能跟踪控制

针对电液伺服系统普遍存在的参数不确定性、不确定非线性(磁滞、摩擦、外干扰等),提出一种基于自适应鲁棒控制的含磁滞补偿的预设性能跟踪控制策略。以阀控单出杆液压缸位置伺服系统为例,首先建立了含磁滞非线性的系统数学模型,然后通过定义预设性能函数,实现了对跟踪误差收敛速率、最大超调量和稳态精度的预先规划,基于规划后的转换误差设计了自适应鲁棒控制器,并提高了稳态和瞬态跟踪性能。仿真对比结果表明：该控制策略可以减小磁滞对系统跟踪精度的影响,提高跟踪误差的收敛速度,减小最大超调量,最终实现优良的跟踪性能。     

电液马达伺服系统积分鲁棒自适应高精度位置控制

电液马达伺服系统中存在各种类型的扰动,包括参数不确定性和不确定非线性,制约着其高精度位置控制。针对电液马达伺服系统高精度位置跟踪控制,考虑系统的黏性摩擦特性以及外干扰等建模不确定性,提出了一种基于鲁棒自适应的电液马达伺服系统高精度位置控制策略。所提出的全状态控制器通过自适应对模型不确定性进行估计及前馈补偿,提高了系统的低速伺服性能;通过自适应对未建模干扰等不确定性的上界进行估计并前馈补偿,提高了系统对外干扰的鲁棒性。所设计的闭环控制器还能保证系统获得渐近跟踪性能,对比仿真验证了其可行性。     

Direct adaptive robust tracking control for 6 DOF industrial robot with enhanced accuracy

A direct adaptive robust tracking control is proposed for trajectory tracking of 6 DOF industrial robot in the presence of parametric uncertainties, external disturbances and uncertain nonlinearities. The controller is designed based on the dynamic characteristics in the working space of the end-effector of the 6 DOF robot. The controller includes robust control term and model compensation term that is developed directly based on the input reference or desired motion trajectory. A projection-type parametric adaptation law is also designed to compensate for parametric estimation errors for the adaptive robust control. The feasibility and effectiveness of the proposed direct adaptive robust control law and the associated projection-type parametric adaptation law have been comparatively evaluated based on two 6 DOF industrial robots. The test results demonstrate that the proposed control can be employed to better maintain the desired trajectory tracking even in the presence of large parametric uncertainties and external disturbances as compared with PD controller and nonlinear controller. The parametric estimates also eventually converge to the real values along with the convergence of tracking errors, which further validate the effectiveness of the proposed parametric adaption law.     

Parametric adaptive estimation and backstepping control of electro-hydraulic actuator with decayed memory filter

Some unknown parameter estimation of electro-hydraulic system (EHS) should be considered in hydraulic controller design due to many parameter uncertainties in practice. In this study, a parametric adaptive backstepping control method is proposed to improve the dynamic behavior of EHS under parametric uncertainties and unknown disturbance (i.e., hydraulic parameters and external load). The unknown parameters of EHS model are estimated by the parametric adaptive estimation law. Then the recursive backstepping controller is designed by Lyapunov technique to realize the displacement control of EHS. To avoid explosion of virtual control in traditional backstepping, a decayed memory filter is presented to re-estimate the virtual control and the dynamic external load. The effectiveness of the proposed controller has been demonstrated by comparison with the controller without adaptive and filter estimation. The comparative experimental results in critical working conditions indicate the proposed approach can achieve better dynamic performance on the motion control of Two-DOF robotic arm.     

非线性液压伺服系统的自适应控制

针对存在不确定参数的液压伺服系统,提出高性能位置跟踪控制器的设计方法。应用“反演”控制设计策略,给出了基于Lyapunov稳定的设计过程,其中系统负载、液压油缸及液压伺服阀的动力特性都包含于控制系统设计中。同时给出了基于液压系统不确定参数的自适应控制律,数值仿真表明了控制系统设计的正确性。     

Multivariable robust adaptive sliding mode control of an industrial boiler–turbine in the presence of modeling imprecisions and external disturbances: A comparison with type-I servo controller

To guarantee the safety and efficient performance of the power plant, a robust controller for the boiler–turbine unit is needed. In this paper, a robust adaptive sliding mode controller (RASMC) is proposed to control a nonlinear multi-input multi-output (MIMO) model of industrial boiler–turbine unit, in the presence of unknown bounded uncertainties and external disturbances. To overcome the coupled nonlinearities and investigate the zero dynamics, input–output linearization is performed, and then the new decoupled inputs are derived. To tackle the uncertainties and external disturbances, appropriate adaption laws are introduced. For constructing the RASMC, suitable sliding surface is considered. To guarantee the sliding motion occurrence, appropriate control laws are constructed. Then the robustness and stability of the proposed RASMC is proved via Lyapunov stability theory. To compare the performance of the purposed RASMC with traditional control schemes, a type-I servo controller is designed. To evaluate the performance of the proposed control schemes, simulation studies on nonlinear MIMO dynamic system in the presence of high frequency bounded uncertainties and external disturbances are conducted and compared. Comparison of the results reveals the superiority of proposed RASMC over the traditional control schemes. RAMSC acts efficiently in disturbance rejection and keeping the system behavior in desirable tracking objectives, without the existence of unstable quasi-periodic solutions.     

基于Backstepping的电液伺服系统多级自适应滑模控制

针对电液伺服系统的非线性特性、系统参数及外部负载的非匹配不确定性,在电液伺服系统的位置跟踪控制中,提出了基于Backstepping逆向递推技术的多级自适应滑模控制方法,应用Backstepping的逆向递推方法有效地解决了高阶系统的控制问题,并结合了自适应方法和滑模控制方法各自优良的抗干扰特点。仿真结果显示,该控制方法具有较强的鲁棒性及良好的跟踪性能。     

气动肌肉并联关节的位姿轨迹跟踪控制

针对多输入多输出的气动肌肉并联关节,建立包含任务空间负载动态方程、容腔压力动态方程和高速开关阀平均流量方程的多阶动态系统数学模型。为保证气动肌肉并联关节系统良好动态特性的同时具有高精度的位姿轨迹跟踪,采用基于非连续投影算法的自适应鲁棒控制策略。该策略通过自适应参数估计来消除因气动肌肉并联关节系统动态数学模型的参数未知而引起的较大参数不确定,通过鲁棒反馈来消除因气动肌肉的伸缩力模型误差、摩擦力时变和关节系统的不可知干扰等引起的严重非线性不确定,且控制器基于反推设计,对多输入多输出的多阶耦合动态系统具有很好的适用性。试验结果表明：所研究的气动肌肉并联关节阶跃响应的静态误差小于0.09°,连续轨迹跟踪的标准误差小于0.15°,且具有较强的自适应性和鲁棒性。     

输入受限的非完整移动机器人的自适应模糊控制

提出了一种非完整移动机器人饱和自适应模糊轨迹跟踪控制方法,该方法基于反演技术分别设计了系统的运动学控制器和动力学控制器。运动学控制器通过引入分流控制技术解决了初始速度跳变引起的控制量突变问题,动力学控制器利用饱和函数和受限控制参数实现了其有界力矩控制。自适应模糊控制器将模糊逻辑系统与自适应方法相结合,有效消除了常规方法难以解决的系统未知不确定性对系统的影响。通过Lyapunov直接法证明了该系统是收敛且渐进稳定的。仿真结果验证了所设计控制器的良好控制性能和强鲁棒性。     

Nonlinear robust control of hypersonic aircrafts with interactions between flight dynamics and propulsion systems

This paper addresses the nonlinear robust tracking controller design problem for hypersonic vehicles. This problem is challenging due to strong coupling between the aerodynamics and the propulsion system, and the uncertainties involved in the vehicle dynamics including parametric uncertainties, unmodeled model uncertainties, and external disturbances. By utilizing the feedback linearization technique, a linear tracking error system is established with prescribed references. For the linear model, a robust controller is proposed based on the signal compensation theory to guarantee that the tracking error dynamics is robustly stable. Numerical simulation results are given to show the advantages of the proposed nonlinear robust control method, compared to the robust loop-shaping control approach.     

基于自适应的电液负载模拟器积分鲁棒控制

为提高电液负载模拟器的跟踪精度,针对其存在的大量非线性特性和模型不确定性等问题,建立了系统非线性数学模型,基于传统的误差符号积分鲁棒控制方法,融合自适应控制的思想,设计了一种自适应误差符号积分鲁棒控制方法。该方法无需获知模型不确定性的确切界,其积分鲁棒增益的取值可在线调节,更好地克服了模型不确定性对系统的影响,在舵机运动干扰作用下实现了系统的渐近稳定性能。仿真对比结果验证了该控制方法的优良性能。     

Adaptive robust motion trajectory tracking control of pneumatic cylinders with LuGre model-based friction compensation

Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation（RLSE） to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This paper constructs an adaptive robust controller     

Discrete-time direct adaptive control for robotic systems based on model-free and if–then rules operation

An adaptive controller for a class of nonlinear discrete-time systems is proposed for robotic systems under the assumption that the parameters and structure of system dynamics are all unknown. This controller is designed with the concept of model-free adaptive control requiring only the input–output of the unknown plant. The robotic system has been generalized to be a nonaffine discrete-time system under reasonable assumptions. The adaptive scheme called fuzzy rules emulated network (FREN) is implemented as a direct controller. The IF–THEN rules for FREN have been defined by the knowledge according to the relation between input and output of the robotic system without any compensator for the unknown mathematical model or nonlinearities. The underlying physical specifications of robotic system such as the operating range, maximum joint velocity, and so on have been considered to initialize the membership functions and adjustable parameters of FREN. The adaptation scheme is developed according to convergence analysis established for both adjustable parameters and the tracking error. The performance of the proposed controller is validated by the experimental system with a 7-degrees-of-freedom robotic arm operated in velocity-mode control.     

Memoryless disturbance-observer-based adaptive tracking of uncertain pure-feedback nonlinear time-delay systems with unmatched disturbances

This paper presents a delay-independent nonlinear disturbance observer (NDO) design methodology for adaptive tracking of uncertain pure-feedback nonlinear systems in the presence of unknown time delays and unmatched external disturbances. Compared with all existing NDO-based control results for uncertain lower-triangular nonlinear systems where unknown time delays have been not considered, the main contribution of this paper is to develop a delay-independent design strategy to construct an NDO-based adaptive tracking scheme in the presence of unknown time-delayed nonlinearities and non-affine nonlinearities unmatched in the control input. The proposed delay-independent scheme is constructed by employing the appropriate Lyapunov-Krasovskii functionals and the same function approximators for the NDO and the controller. It is shown that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to an adjustable neighborhood of the origin.     

电液伺服力控系统的自适应滑模控制

针对存在不确定性的非线性电液伺服力控系统的跟踪控制问题,基于等价控制的概念,提出了一种自适应滑模控制律综合方法,应用参数自适应的方法,消除不确定性对控制性能的影响,以达到鲁棒跟踪控制的目的。为了证明这种控制器可行性,利用微机实现的该控制器被应用于某疲劳试验机电液伺服系统,实时控制的结果验证了所提方法的有效性。     

Novel prescribed performance neural control of a flexible air-breathing hypersonic vehicle with unknown initial errors

A novel prescribed performance neural controller with unknown initial errors is addressed for the longitudinal dynamic model of a flexible air-breathing hypersonic vehicle (FAHV) subject to parametric uncertainties. Different from traditional prescribed performance control (PPC) requiring that the initial errors have to be known accurately, this paper investigates the tracking control without accurate initial errors via exploiting a new performance function. A combined neural back-stepping and minimal learning parameter (MLP) technology is employed for exploring a prescribed performance controller that provides robust tracking of velocity and altitude reference trajectories. The highlight is that the transient performance of velocity and altitude tracking errors is satisfactory and the computational load of neural approximation is low. Finally, numerical simulation results from a nonlinear FAHV model demonstrate the efficacy of the proposed strategy.     

Development of an adaptive radial basis function neural network estimator-based continuous sliding mode control for uncertain nonlinear systems

In this paper an adaptive neural network (NN)-based nonlinear controller is proposed for trajectory tracking of uncertain nonlinear systems. The adopted control algorithm combines a continuous second-order sliding mode control (CSOSMC), the radial basis function neural network (RBFNN) and the adaptive control methodology. First, a second-order sliding mode control scheme (SOSMC), which is published recently in literature for linear uncertain systems, is extended for nonlinear uncertain systems. Second, an adaptive radial basis function neural network estimator-based continuous second order sliding mode control algorithm (CSOSMC-ANNE) is adopted. In CSOSMC-ANNE control methodology, a radial basis function neural network with adaptive parameters is exploited to approximate the unknown system parameters and improve performance against perturbations. Also, the discontinuous switching control of SOSMC is supplanted with a smooth continuous control action to completely eliminate the chattering phenomenon. The convergence and global stability of the closed-loop system are proved using Lyapunov stability method. Numerical computer simulations, with dynamical model of the nonlinear inverted pendulum system, are presented to demonstrate the effectiveness and advantages of the presented control scheme.     

采用非线性流量特性补偿的直驱式变转速泵控系统轨迹跟踪控制

变转速电机-泵直驱电液系统的发展与伺服技术的提升使得泵控系统在保留高能效特性的同时,具有更高的硬件集成度和更快的响应速度;但是在低转速泵控工况下,此类系统依旧存在泵的流量非线性、流量偏差大等控制难点,使得变转速泵控系统难以完成高精度的执行器运动轨迹跟踪。为实现泵控液压缸系统的精密运动控制,提出了一种新颖的非线性流映射方案,以此得到精确的泵输出流量;同时,利用非线性自适应鲁棒反演控制策略(Adaptive Robust Controller Backstepping,ARCB)实现液压系统在高阶动力学、参数不确定性下的精确控制。试验表明,提出的控制策略可有效解决变转速泵的流量偏差问题,实现理想的控制性能和轨迹跟踪精度。     

Robust control application for a three-axis road simulator

This paper presents the design of a quantitative feedback control system for a three-axis hydraulic road simulator. The road simulator is a multiple input-output (MIMO) system with parameter uncertainties which should be compensated with a robust control method. The objective of the present paper is to reproduce the random input signal or real road vibration signal by three hydraulic cylinders. The replaced m ² MISO equivalent control system is suggested, which satisfies the design specification of the original m×m MIMO control system by decoupling each of the three axes. Quantitative Feedback Theory (QFT) is used to control the simulator. The QFT illustrates a tracking performance of the closed-loop controller with low order transfer function G (s) and pre-filter F (s) having the minimum bandwidth for the uncertain plant with parameter uncertainty. The efficacy of the designed controller is verified through dynamic simulation, which is co-simulated with hydraulic models of Matlab and Adams multi-body. The simulation and the experimental results show that the proposed control technique works well for uncertain hydraulic plant systems.