电液力伺服系统自适应抗扰控制研究

考虑到电液伺服系统中存有各种非线性因素、不确定干扰以及参数时变,为了提高干扰下电液力伺服系统的控制精度,以电液伺服振动实验台作为控制对象,构建其非线性模型,同时使用参数自适应率对不定参数进行补偿,并在反演控制器中引入滑模控制以降低系统的干扰敏感性,利用Lyapunov理论保证闭环系统的全局稳定。对设计的控制器进行实验,模拟在有未知外部位置干扰下的力控制,提升系统的稳定性。实验结果证明,此控制方法能够有效地提升电液力伺服系统的抗干扰跟踪性能。     

On the performance enhancement of self-tuning adaptive control for time-varying machining processes

This paper investigates efficient approaches to improve the performance of a self-tuning adaptive control system for time-varying machining processes. The milling process is a typical time-varying system because of variations of the cutting conditions, e.g., the change of cutting depths and variation of the cutting materials. On the other hand, the milling processes are considered as typically non-minimum phases since one or more zeros of discrete-time models of milling processes may be located outside the unit circle. In this paper, an efficient method, using the pole assignment method, is presented to design a self-tuning adaptive controller for time-varying and non-minimum phase milling processes, and an effective method to select appropriate design parameters in order to improve its performance has been proposed. Its effectiveness has been verified in experiments on controlling milling processes with varying cutting depth. The experimental results illustrate that improved control performances can be obtained using the appropriate design parameters selected according to the principles and criteria presented here.     

车辆四轮转向控制平台研究

针对机-电-液复合结构的四轮转向平台具有非线性、快时变的特点，提出了模糊自适应PID控制策略。将模糊自适应补偿器与PID控制器并联，提高系统的鲁棒性和抗干扰能力。使用PID控制器稳定系统的线性标称部分，应用模糊自适应补偿器调节PID参数来补偿系统参数摄动、非线性和外界扰动对系统控制性能的影响。仿真和外加扰动实验结果验证了提出的控制策略对四轮转向平台的控制具有快速性、准确性、稳定性和鲁棒性。     

High accuracy motion control of linear motor drive wire-EDM machines

This paper aims to develop and investigate a permanent magnet linear-motor-driven table system for a wire-EDM machine. A dynamic model and system identification of `the linear motor system have been derived and analyzed. The linear motor drive system has nonlinear and time-varying behaviors because of the effect of irregular friction of the sliding surface and cogging force. Therefore, a conventional digital controller may not suffice to provide a high contouring accuracy as well as adequate disturbance rejection and parameter variation robustness. An indirect adaptive controller (IAC), combined with a neural network-based feedforward controller (NNBFC) is proposed to improve the contouring performance of the linear motor system. Experimental results not only indicate that the proposed control scheme can achieve a high contouring accuracy of ± 0.3 μm, they also demonstrate that the developed linear motor drive wire-EDM machine can meet the requirement for micro machining. The maximum contour error of circular trajectory at a feed-rate of 0.1 mm/min was significantly reduced from 8 μm to 0.5 μm in comparison with proportional-integral-derivative (PID) controller.     

In-situ neural network process controller for copper chemical mechanical polishing

Process control is one of the key methods to improve manufacturing quality. This research proposes a neural network based run-to-run process control scheme that is adaptive to the time-varying environment. Two multilayer feedforward neural networks are implemented to conduct the process control and system identification duties. The controller neural network equips the control system with more capability in handling complicated nonlinear processes. With the system information provided by this neural network, batch polishing time (T) an additional control variable, can be implemented along with the commonly used down force (p) and relative speed between the plashing pad and the plashed wafer (v). Computer simulations and experiments on copper chemical mechanical polishing processes illustrate that in drafting suppression and environmental changing adaptation that the proposed neural network based run-to-run controller (NNRTRC) performs better than the double exponentially weighted moving average (d-EWMA) approach. It is also suggested that the proposed approach can be further implemented as both an end-point detector and a pad-conditioning sensor.     

Nonlinear robust dual-loop control for electro-hydraulic load simulator

This paper investigates on the high performance torque control of electro-hydraulic load simulator (EHLS). In order to suppress actuator׳s motion disturbance, a nonlinear robust dual-loop control scheme is developed, which consists of a open-loop nonlinear velocity feed-forward compensator and a closed-loop nonlinear deterministic robust torque controller. The main function of the open-loop compensator is to decouple actuator׳s active motion disturbance, whereas the torque loop controller aims at guaranteeing the dynamics performance of tracking torque reference. Besides actuator׳s motion disturbance, both the nonlinearity characteristics and friction problem of the EHLS system are taken into consideration in this paper. The effectiveness of the developed method are verified through comparative co-simulations and experiments.     

A new self-tuned PID-type fuzzy controller as a combination of two-term controllers

The present paper is a venture into the domain of proportional-integral-derivative (PID) -type adaptive fuzzy logic controllers (FLC's) and proposes a new algorithm which is realized by a self-tuned PI-type FLC (in velocity form) in parallel with a self-tuned PD-type FLC (in position form). Each of these PI/PD controllers implements a supervisory static FLC for adaptive online modification of the output scaling factor (SF) of a static PI/PD FLC. The proposed scheme is developed with a view to having a PID-type FLC with an architecture, simple enough for practical implementation, which at the same time has substantially satisfactory performance for a wide class of processes. Simulation studies on a range of processes reveal that the proposed controller has better performance compared to many of its existing counterparts.     

基于PID参数自整定的双容系统抗扰控制

针对双容液面调节系统的非线性、参数时变的特点,基于现代控制理论设计了带扰动观测器的模糊自整定控制器.把这种控制器应用在双容液面调节系统中,既实现了PID控制器参数的在线自整定,又增强了系统的抗扰能力.仿真试验表明,这种方案极大地提高了被控对象的静态和动态性能,对参数时变的适应能力强,鲁棒性好.该方案同样可以用于其他非线性、时变系统.     

A FUZZY UNCERTAINTY COMPENSATOR FOR MANIPULATOR TRAJECTORY TRACKING

A novel fuzzy logic compensating (FLC) scheme is proposed to enhance the conventional computed-torque control (CTC) structure of manipulators The control scheme is based on the combination of a classical CTC and FLC, and the resulting control scheme has a simple structure with improved robustness. Further improvement of the performance of the FLC scheme is achieved through automatic tuning of a weight parameter a leading to a self-tuning fuzzy logic compensator, so the system uncertainty can be compensated very well. By taking into account the full nonlinear nature of the robotic dynamics, the overall closed-loop system is shown to be asymptotically stable. Experimental results demonstrate the effectiveness of the computed torque and fuzzy compensation scheme to control a manipulator during a trajectory tracking task.     

Adaptive output feedback tracking of nonlinear systems with uncertain nonsymmetric dead-zone input

In this paper, the problem of adaptive practical tracking is investigated by output feedback for a class of uncertain nonlinear systems subject to nonsymmetric dead-zone input nonlinearity with parameters of dead-zone being unknown. Instead of constructing the inverse of dead-zone nonlinearity, an adaptive robust control scheme is developed by designing an output compensator including two dynamic gains based respectively on identification and non-identification mechanism. With the aid of dynamic high-gain scaling approach and Backstepping method, stability analysis of the closed-loop system is proceeded using non-separation principle, which shows that the proposed controller guarantees that all closed-loop signal is bounded while the output of system tracks a broad class of bounded reference trajectories by arbitrarily small error prescribed previously. Finally, two examples are given to illustrate our controller effective.     

具有滞后非线性的汽车悬架系统中的混沌及控制

由于带有滞后非线性的汽车悬架系统中具有明显的非线性,这直接导致了系统存在分岔与混沌的可能性.为此分析了其在路面拟周期激励作用下发生受迫振动时的运动情况,揭示了该系统存在混沌现象,并利用比例微分控制器对其混沌行为进行了控制,数值模拟表明了该控制方法的有效性与可行性,可为汽车悬架系统的分析研究和优化设计提供理论依据.     

Real-time tracking control of electro-hydraulic force servo systems using offline feedback control and adaptive control

This paper focuses on an application of an electro-hydraulic force tracking controller combined with an offline designed feedback controller (ODFC) and an online adaptive compensator in order to improve force tracking performance of an electro-hydraulic force servo system (EHFS). A proportional-integral controller has been employed and a parameter-based force closed-loop transfer function of the EHFS is identified by a continuous system identification algorithm. By taking the identified system model as a nominal plant model, an H_∞ offline design method is employed to establish an optimized feedback controller with consideration of the performance, control efforts, and robustness of the EHFS. In order to overcome the disadvantage of the offline designed controller and cope with the varying dynamics of the EHFS, an online adaptive compensator with a normalized least-mean-square algorithm is cascaded to the force closed-loop system of the EHFS compensated by the ODFC. Some comparative experiments are carried out on a real-time EHFS using an xPC rapid prototype technology, and the proposed controller yields a better force tracking performance improvement.     

无模型控制器在气缸压力控制系统中的应用研究

气动伺服系统存在纯时延、非线性、时变等特点,传统的控制策略(如PID控制)在解决非线性系统时效果不理想,因此提出一种无模型控制算法。此方法在被控对象结构复杂、参数时变时控制效果较好。首先对气动伺服系统进行建模,建模过程包括阀口流量、比例流量阀及缸内压力建立一个二阶模型;其次设计无模型自适应控制器(Model-Free Adaptive Controller,MFAC)用于气动伺服系统压力控制;最后利用LabWindows/CVI平台进行试验验证。结果表明,针对气动伺服系统设计的无模型控制器是有效的,相比于传统PID控制有更快的响应速度和更高的控制精度。     

非最小相位加工过程的极点配置自校正控制

针对加工过程模型的时变性与非最小相位的特点，研究了变切削深度铣削加工过程的极点配置自校正控制，提出了适应于非最小相位过程的自适应控制算法，试验结果表明了该算法的有效性。并指出了获得理想控制结果的控制器设计参数，包括观测器参数与期望的极点分布。     

非对称泵缸系统模型跟踪控制研究

用神经网络逼近非对称泵缸系统的非线性逆模型，通过神经网络模型参考控制实现电液斜盘位置和流量的控制，使系统的不确定性和非线性等得到补偿。仿真和实验表明，所开发的神经网络控制器能够较好地实现模型跟踪控制，有较好的自适应性和鲁棒性，跟踪性能有较大改善。     

超磁致伸缩致动器的复合反馈控制及其在变椭圆销孔精密加工中的应用

针对非对称性销孔的镗削加工,研究了用于高负荷孔精密镗削装置的超磁致伸缩致动器(GMA)的相关控制。考虑GMA的迟滞非线性,分析了准静态改进型Prandtl-Ishlinskii(P-I)模型的数学机理;为提高其动态适用频域和控制精度,提出了结合相角前馈补偿的动态改进型P-I模型,获得了满意的控制效果。结合PID反馈控制搭建的闭环控制实验结果显示,GMA的迟滞非线性由补偿前的14.5%~67.2%减小到1.5%~4.3%,有效降低了迟滞系统的非线性误差。在此基础上进行了椭圆销孔试镗削实验,结果显示其椭圆度均符合图纸要求,验证了补偿方法的正确性。本文的研究为实现高负荷异形孔的精密加工提供了新方法。     

Indirect predictive type-2 fuzzy neural network controller for a class of nonlinear input - delay systems

In this paper a new indirect type-2 fuzzy neural network predictive (T2FNNP) controller has been proposed for a class of nonlinear systems with input-delay in presence of unknown disturbance and uncertainties. In this method, the predictor has been utilized to estimate the future state variables of the controlled system to compensate for the time-varying delay. The T2FNN is used to estimate some unknown nonlinear functions to construct the controller. By introducing a new adaptive compensator for the predictor and controller, the effects of the external disturbance, estimation errors of the unknown nonlinear functions, and future sate estimation errors have been eliminated. In the proposed method, using an appropriate Lyapunov function, the stability analysis as well as the adaptation laws is carried out for the T2FNN parameters in a way that all the signals in the closed-loop system remain bounded and the tracking error converges to zero asymptotically. Moreover, compared to the related existence predictive controllers, as the number of T2FNN estimators are reduced, the computation time in the online applications decreases. In the proposed method, T2FNN is used due to its ability to effectively model uncertainties, which may exist in the rules and data measured by the sensors. The proposed T2FNNP controller is applied to a nonlinear inverted pendulum and single link robot manipulator systems with input time-varying delay and compared with a type-1 fuzzy sliding predictive (T1FSP) controller. Simulation results indicate the efficiency of the proposed T2FNNP controller.     

Study on self-tuning pole assignment speed control of an ultrasonic motor

Ultrasonic motors have a heavy nonlinearity, which varies with driving conditions. The nonlinearity is a problem as an accurate motion actuator for industrial applications and it is important to eliminate the nonlinearity in order to improve the control performance. In general, complicated control strategies are used to deal with the nonlinearity of ultrasonic motors. This paper proposes a new speed control scheme for ultrasonic motors to overcome the nonlinearity employing a simplified self-tuning control. The speed control model which can reflect the main nonlinear characteristics is obtained using a system identification method based on the step response. Then, a pole assignment speed controller is designed. To avoid the influence of the motor’s nonlinearity on the speed control performance, a control parameters’ on-line self-tuning strategy utilizing the gain of the model is designed. The proposed control strategy is realized using a DSP circuit, and experiments prove the validity of the proposed speed control scheme.     

Neural adaptive pointing control of a moving tank gun with lumped uncertainties based on dynamic simulation

This study focuses on the pointing control problem of a moving tank gun. Model uncertainty and foundation vibration, which may be nonlinear, coupled, or time-varying but bounded, are considered. First, the electrohydraulic servo system of a vertical stabilizer is constructed as a nonlinear dynamic system with lumped uncertainties. Second, a neural adaptive controller is proposed to improve the control performance of the vertical stabilizer. A back-propagation neural network is introduced to compensate for the uncertainties, and its weight and threshold values are self-tuned online. Third, a co-simulation model of the moving tank is established. Dynamic simulation verifies that the proposed controller exhibits better performance than typical controllers. Finally, the influence of hull foundation vibration on the proposed controller is analyzed. The pointing accuracy of a moving tank gun is verified to be controlled effectively by the proposed controller under different driving conditions. This work combines control theory with multi-body dynamics to provide a feasible solution for the pointing control problem of a moving tank with model uncertainty and foundation vibration.

     

Control system design of a linear motor feed drive system using virtual friction

This paper proposes a friction compensator and a design method for control systems to improve the response characteristics of linear motor feed drive systems. The proposed friction compensator cancels the real nonlinear friction of feed drive systems by using the nonlinear friction model proposed in this study and introduces virtual linear friction to facilitate the control system design. The proposed design method enables the determination of servo gains and friction compensator parameters that lead to desirable tracking performance and disturbance rejection without many trial-and-error tuning processes. In addition, the proposed method facilitates the design of the velocity feedforward compensator by using the inverse transfer function of the velocity control loop to correct the position tracking errors for various position commands. The effectiveness of the proposed method with the friction compensator and the velocity feedforward compensator was verified in simulations and experiments using a one-axis feed drive system consisting of a rod-type linear motor and linear roller guides. The results confirmed that the proposed method enables desirable overshoot-free responses and corrects motion trajectory errors due to nonlinear friction characteristics, and the proposed velocity feedforward compensator can correct tracking errors in both constant velocity motion and circular motion.