具有状态约束的电液伺服系统模型参考鲁棒自适应控制

针对电液伺服系统中的模型不确定性和状态约束问题,设计了一种模型参考鲁棒自适应控制(MRRAC)方法。将电液伺服系统的近似模型作为模型预测控制(MPC)的设计对象,在设计过程中考虑状态约束,并生成受约束的状态期望,作为后续伺服控制方法的参考指令。为了克服液压系统中的模型不确定性,基于反步法设计了鲁棒自适应控制器(RAC),实现了兼顾模型不确定性和状态约束的伺服控制。基于Lyapunov稳定性理论证明了所设计控制策略的闭环渐近稳定性,且系统所有信号均有界。仿真结果表明,控制器对于系统模型不确定性具有较强的鲁棒性,且可实现对指定状态的有效约束,充分验证了该控制策略的有效性。     

不可靠WSN时钟同步网络化输出反馈MPC量化分析

在Cyber-Physical环境下,时钟同步双向信息交换过程中,包含时钟信息的数据包丢失将对时钟同步性能产生影响。讨论了现代控制理论状态空间模型的输出反馈Tubes-MPC时钟同步方法。由分离原理,设计了本地化的状态估计器与控制器,实现了输出反馈Tubes-MPC时钟同步的指数稳定。以不完全量测下的观测模型为基础,定量分析了统计意义下的同步误差方差上界与下界,并采用MPC中Set-Theory-in-Control方法,将完全量测下的干扰误差集合运算于由丢包所引入的附加的估计误差集合,建立了集合约束下的模型预测优化模型。已构建的统一框架下的输出反馈Tubes-MPC时钟同步系统化方法,综合考量了控制理论在线计算复杂度与网络控制观点应用的可行性,对无线网络的不可靠性、网络规模、收敛性能具有鲁棒性,进一步容易扩展为网络级绝对时钟状态空间模型。     

Combined feedforward and model-assisted active disturbance rejection control for non-minimum phase system

Control of the non-minimum phase (NMP) system is challenging, especially in the presence of modelling uncertainties and external disturbances. To this end, this paper presents a combined feedforward and model-assisted Active Disturbance Rejection Control (MADRC) strategy. Based on the nominal model, the feedforward controller is used to produce a tracking performance that has minimum settling time subject to a prescribed undershoot constraint. On the other hand, the unknown disturbances and uncertain dynamics beyond the nominal model are compensated by MADRC. Since the conventional Extended State Observer (ESO) is not suitable for the NMP system, a model-assisted ESO (MESO) is proposed based on the nominal observable canonical form. The convergence of MESO is proved in time domain. The stability, steady-state characteristics and robustness of the closed-loop system are analyzed in frequency domain. The proposed strategy has only one tuning parameter, i.e., the bandwidth of MESO, which can be readily determined with a prescribed robustness level. Some comparative examples are given to show the efficacy of the proposed method. This paper depicts a promising prospect of the model-assisted ADRC in dealing with complex systems.     

Performance analysis of active disturbance rejection tracking control for a class of uncertain LTI systems

The paper considers the tracking problem for a class of uncertain linear time invariant (LTI) systems with both uncertain parameters and external disturbances. The active disturbance rejection tracking controller is designed and the resulting closed-loop system׳s characteristics are comprehensively studied. In the time-domain, it is proven that the output of closed-loop system can approach its ideal trajectory in the transient process against different kinds of uncertainties by tuning the bandwidth of extended state observer (ESO). In the frequency-domain, different kinds of parameters׳ influences on the phase margin and the crossover frequency of the resulting control system are illuminated. Finally, the effectiveness and robustness of the controller are verified through the actuator position control system with uncertain parameters and load disturbances in the simulations.     

Tuning of linear active disturbance rejection controller with robustness specification

Active disturbance rejection control (ADRC) treats all the model uncertainties and all the external disturbances as a generalized disturbance. It uses an extended state observer (ESO) to estimate the generalized disturbance in real time, and compensate it using a state-feedback control law, thus can achieve good disturbance rejection performance. For linear ADRC (LADRC), the parameters can be tuned via the bandwidths of the ESO and the feedback control, thus an LADRC can be regarded as a fixed-structured controller with several parameters to tune, just like a PID controller. To help tuning the parameters of LADRC, a tuning rule is proposed in this paper, with the aim to minimize the load disturbance attenuation performance in the integral of time square error sense, under the constraint of a specified robustness measure for the first-order processes with deadtime. The tuning rule is tested for a variety of benchmark systems and the gravity drained tanks case, and the performances are compared with the well-known PID tuning methods.     

A novel auto-tuning PID control mechanism for nonlinear systems

In this paper, a novel Runge–Kutta (RK) discretization-based model-predictive auto-tuning proportional-integral-derivative controller (RK-PID) is introduced for the control of continuous-time nonlinear systems. The parameters of the PID controller are tuned using RK model of the system through prediction error-square minimization where the predicted information of tracking error provides an enhanced tuning of the parameters. Based on the model-predictive control (MPC) approach, the proposed mechanism provides necessary PID parameter adaptations while generating additive correction terms to assist the initially inadequate PID controller. Efficiency of the proposed mechanism has been tested on two experimental real-time systems: an unstable single-input single-output (SISO) nonlinear magnetic-levitation system and a nonlinear multi-input multi-output (MIMO) liquid-level system. RK-PID has been compared to standard PID, standard nonlinear MPC (NMPC), RK-MPC and conventional sliding-mode control (SMC) methods in terms of control performance, robustness, computational complexity and design issue. The proposed mechanism exhibits acceptable tuning and control performance with very small steady-state tracking errors, and provides very short settling time for parameter convergence.     

基于干扰观测器的电液伺服系统反馈线性化滑模控制

为抑制电液伺服系统中各种非线性因素及不确定干扰,提出了基于输入输出反馈线性化的滑模控制与非线性干扰观测器相结合的控制策略以提高其位置控制跟踪精度。以电液振动台为试验对象,建立其非线性控制模型,利用李雅普诺夫稳定性理论保证了位置闭环系统的全局稳定性。利用MATLAB/Simulink对设计的控制器进行了仿真验证,结果验证了提出的控制器的可行性。为了模拟实际环境下存在不确定干扰,在位置电液系统基础上增加了电液加载系统,开展了试验研究。结果表明,该控制器能有效的提高干扰下电液伺服系统的位置跟踪性能。     

基于死区补偿的电液位置伺服系统自抗扰控制

针对电液位置伺服控制系统的比例阀死区、参数不确定及外部未知扰动等问题,设计了由自抗扰控制器与死区逆补偿构成的串联控制器。首先基于实验辨识构造死区逆模型对死区进行预补偿,然后根据系统特性设计了一阶自抗扰控制器,构造改进的扩张状态观测器对“总扰动”进行实时估计,并通过非线性控制律给予主动补偿。联合仿真与试验结果表明,所提出的串联控制器有效地补偿了比例阀死区,提高了系统动态性能和位置跟踪精度。     

高阶非线性液压辊缝系统的Backstepping动态面控制

针对某四辊冷轧机的液压辊缝系统,考虑系统干扰的情况下,建立了高阶非线性系统数学模型,利用Backstepping动态面算法设计了辊缝闭环控制器。该方法由于在逆递推设计过程中结合使用了一阶低通滤波器,无需对模型的非线性部分重复微分,从而避免了因"微分项的膨胀"而引起的算法复杂性。理论分析和仿真结果均表明所设计的控制器能够保证系统的半局稳定性,输出渐近跟踪期望轨迹,使系统对于给定位置跟踪具有良好的动态性能,对外部干扰也有较强的鲁棒性。     

Composite disturbance rejection control based on generalized extended state observer

Traditional extended state observer (ESO) design method does not focus on analysis of system reconstruction strategy. The prior information of the controlled system cannot be used for ESO implementation to improve the control accuracy. In this paper, composite disturbance rejection control strategy is proposed based on generalized ESO. First, the disturbance rejection performance of traditional ESO is analyzed to show the essence of the reconstruction strategy. Then, the system is reconstructed based on the equivalent disturbance model. The generalized ESO is proposed based on the reconstructed model, while convergence of the proposed ESO is analyzed along with the outer loop feedback controller. Simulation results on a second order mechanical system show that the proposed generalized ESO can deal with the external disturbance with known model successfully. Experiment of attitude tracking task on an aircraft is also carried out to show the effectiveness of the proposed method.     

车载液压发电机行车工况发电稳速控制

车载液压发电机在驻车工况下发出电能的质量较高,但在行车发电工况下,行驶负载的扰动使得发电机转速不稳定,发出的电能质量较差。针对行车发电稳速控制展开研究,构建了行车发电工况下变量泵-定量马达闭式调速系统的数学模型,分析了输出转速波动的机理,采用前馈补偿加直接闭环反馈的方法对马达输出转速波动进行抑制。仿真和实验结果表明,补偿控制能够使系统在行车工况下具有较高的控制精度和鲁棒性,输出电力品质满足军用Ⅱ类自发电电站标准。     

混合煤气管道多变量系统自抗扰解耦控制

针对煤气混合蝶阀串联系统具有强耦合、不确定性、干扰因素多、非线性等特点,应用自抗扰控制（ADRC）静态解耦和扩张状态观测器（ESO）动态解耦技术,给出一种适用于煤气混合蝶阀串联系统的ADRC解耦设计方案。为提高系统的响应速度,减少计算量,控制系统去掉跟踪微分器（TD）,并且ESO和NF（非线性反馈）采用线性函数的ADRC。仿真结果表明,该控制方案不仅解耦效果优良,而且具有较好的跟踪性能和抗扰动能力。     

带ESO的ANFTSMC控制PMSM的新型MPTC无传感器控制策略

针对电动汽车中永磁同步电机传统控制策略对电机控制性能差的问题,提出了一种新型的自适应非奇异快速终端滑模模型预测转矩控制策略.设计了新型自适应指数趋近率,用性质更佳的双曲正切函数tanh()替换传统的切换函数sgn(),并构造了带ESO扰动观测的新型ANFTSMC作为系统转速控制器,消弱了抖振,提高了系统鲁棒性.为实现调速系统的无传感器控制,构造了基于tanh(Fal)的ESO转速观测器.与传统基于Fal函数的ESO相比,观测误差较小,观测精度较高.同时,针对预测转矩控制策略,提出了新型的目标函数构造方法,避免了权重系数的设计,并对传统电压矢量选择方法进行了改进与优化,减少了算法的计算量,结合所设计的新型控制器可有效提高系统的快速性,增加算法的实用性.     

An application of sliding horizon control to an electro-hydraulic automotive seat simulator

The paper demonstrates the tracking performance of a sliding horizon feedback/feedforward preview optimal control when applied to a hydraulic motion simulator which has been built to provide a means of replicating the actual ride dynamics of an automobile seat/human system. The design was developed by solving an ordinary differential equation problem instead of a Ricatti equation. Simulation results indicate that the proposed technique has good performance improvement in phase tracking when compared to the classical design methods. It is also found that the controller can be adjusted more easily for robustness due to more turning parameters.     

A novel predictive control algorithm and robust stability criteria for integrating processes

This paper introduces a novel predictive controller for single-input/single-output (SISO) integrating systems, which can be directly applied without pre-stabilizing the process. The control algorithm is designed on the basis of the tested step response model. To produce a bounded system response along the finite predictive horizon, the effect of the integrating mode must be zeroed while unmeasured disturbances exist. Here, a novel predictive feedback error compensation method is proposed to eliminate the permanent offset between the setpoint and the process output while the integrating system is affected by load disturbance. Also, a rotator factor is introduced in the performance index, which is contributed to the improvement robustness of the closed-loop system. Then on the basis of Jury’s dominant coefficient criterion, a robust stability condition of the resulted closed loop system is given. There are only two parameters which need to be tuned for the controller, and each has a clear physical meaning, which is convenient for implementation of the control algorithm. Lastly, simulations are given to illustrate that the proposed algorithm can provide excellent closed loop performance compared with some reported methods.     

Enhanced extended state observer-based control for systems with mismatched uncertainties and disturbances

This paper presents an enhanced Extended State Observer (ESO)-based control strategy to deal with the disturbance attenuation problem for a class of non integral-chain systems subject to non-linear mismatched uncertainties and external disturbances. The proposed control strategy does not assume the integral-chain form and it is formed by a state-feedback plus a dynamic disturbance compensation term, which is designed to reject the disturbance effect in the system output. From a theoretical point of view, the proposed strategy is reduced to the conventional ESO when the integral chain form and the matched condition hold. In this sense, this paper is presented as an extension of the ESO principles to cover a wider class of systems. The theoretical results show that the internal zero-dynamics plays an important role in ESO-based control design. Also, the closed-loop stability is analyzed and some numerical simulations show the effectiveness of the proposal in comparison with previous ESO-based techniques.     

伺服电机驱动的液压动力系统及其神经网络自适应优化控制

针对传统液压系统存在的高能耗、低响应特点,采用节能型液压动力源-永磁伺服电机直接驱动定量泵,以取代原有的异步电机驱动液压动力源,从而形成一种新型的节能、响应快速、易实现闭环控制的液压动力系统。由于实际液压系统随机干扰严重,具有多变量、非线性、强耦合的特征,难以建立较准确的数学模型,常规的PID控制算法很难满足液压系统高精度控制的要求,因此提出基于PSO与BP混合优化前向神经网络 PID自适应控制方法,实现液压系统在典型工况下流量的精确控制。PID控制器的参数采用神经网络进行自适应整定,神经网络的权值采用混合优化算法进行调整,通过神经网络的自学习能力寻找最佳的P、I、D非线性组合控制律,以增强液压系统对工况变化的适应能力。仿真和实验结果表明,该控制方法跟踪速度快、超调小、鲁棒性强,从而为液压系统流量高精度控制提供了一种新方法。     

ROBUST CONTROL OF AN ELECTRO- HYDRAULIC PROPORTIONAL SPEED CONTROL SYSTEM WITH A SINGLE- ROD HYDRAULIC ACTUATOR

A robust control algorithm is proposed to focus on the non-linearity and parameters' uncertainties of an electro-hydraulic proportional speed control system (EHPSCS) with a single-rod hydraulic actuator.The robust controller proposed does not need to design stable compensator in advance,is simple in design and has large scope of uncertainty applications.The feedback gains of the robust controller proposed are small,so it is easily implemented in engineering applications. Experimental research on the speed control under the different conditions is carried out for an EHPSCS.Experimental results show that the robust controller proposed has better robustness subject to parametric uncertainties,and adaptability of parameters' variation of control system itself and plant parameter variation.     

Model-based adaptive sliding mode control of the subcritical boiler-turbine system with uncertainties

As higher requirements are proposed for the load regulation and efficiency enhancement, the control performance of boiler-turbine systems has become much more important. In this paper, a novel robust control approach is proposed to improve the coordinated control performance for subcritical boiler-turbine units. To capture the key features of the boiler-turbine system, a nonlinear control-oriented model is established and validated with the history operation data of a 300 MW unit. To achieve system linearization and decoupling, an adaptive feedback linearization strategy is proposed, which could asymptotically eliminate the linearization error caused by the model uncertainties. Based on the linearized boiler-turbine system, a second-order sliding mode controller is designed with the super-twisting algorithm. Moreover, the closed-loop system is proved robustly stable with respect to uncertainties and disturbances. Simulation results are presented to illustrate the effectiveness of the proposed control scheme, which achieves excellent tracking performance, strong robustness and chattering reduction.     

T–S fuzzy model predictive speed control of electrical vehicles

This paper proposes a novel nonlinear model predictive controller (MPC) in terms of linear matrix inequalities (LMIs). The proposed MPC is based on Takagi–Sugeno (TS) fuzzy model, a non-parallel distributed compensation (non-PDC) fuzzy controller and a non-quadratic Lyapunov function (NQLF). Utilizing the non-PDC controller together with the Lyapunov theorem guarantees the stabilization issue of this MPC. In this approach, at each sampling time a quadratic cost function with an infinite prediction and control horizon is minimized such that constraints on the control input Euclidean norm are satisfied. To show the merits of the proposed approach, a nonlinear electric vehicle (EV) system with parameter uncertainty is considered as a case study. Indeed, the main goal of this study is to force the speed of EV to track a desired value. The experimental data, a new European driving cycle (NEDC), is used in order to examine the performance of the proposed controller. First, the equivalent TS model of the original nonlinear system is derived. After that, in order to evaluate the proficiency of the proposed controller, the achieved results of the proposed approach are compared with those of the conventional MPC controller and the optimal Fuzzy PI controller (OFPI), which are the latest research on the problem in hand.