Multisensor switching control strategy with fault tolerance guarantees

In this paper we propose a novel fault tolerant multisensor switching strategy for feedback control. Each sensor of the proposed multisensor scheme has an associated state estimator which, together with a state feedback gain, is able to individually stabilise the closed-loop system. At each instant of time, the switching strategy selects the sensor-estimator pair that provides the best closed-loop performance, as measured by a control-performance criterion. We establish closed-loop stability of the resulting switching scheme under normal (fault-free) operating conditions. More importantly, we show that closed-loop stability is preserved in the presence of faulty sensors if a set of conditions on the system parameters (such as bounds on the sensor noises, maximum and minimum values of the reference signal, etc.) is satisfied. This result enhances and broadens the applicability of the proposed multisensor scheme since it provides guaranteed properties such as fault tolerance and robust closed-loop stability under sensor fault. The results are applied to the problem of automotive longitudinal control.     

感应电动机直接转矩控制的稳定性分析

稳定性问题的研究在感应电动机直接转矩控制(DTC)中具有重要意义。现有文献主要关注恒转速情形,本文研究更接近实际的情况一一变转速下的DTC稳定性,引入状态反馈机制,首先给出定子磁链控制律存在的充分条件;然后在参考转矩大于或小于负载转矩的情形下,分别给出了转矩控制律存在的充分条件,最后以数值仿真验证了所提控制律的有效性,磁链和转矩相对于参考信号的波动确实是限定在一定容差范围内。     

基于DSP交流感应电机直接转矩模糊控制系统

介绍了基于DSP的交流感应电机直接转矩模糊控制系统的硬件：结构和软件设计。电压空间矢量的选择方法和故障诊断原理，并对系统的仿真结果和试验结果进行了分析。本系统具有动态相应快。调速精度宽。可靠性高等特点。     

永磁容错游标轮缘推进电机改进模型预测转矩控制

为提高永磁容错游标轮缘推进电机(FTPMV-RDM)在正常状态和一相开路故障状态下的控制性能, 本文提出了一种基于电压矢量预选的改进模型预测转矩(MPTC)控制方法. 针对六相独立H桥逆变器提供的备选电压矢量数量多导致MPTC系统计算量大的问题, 首先, 采用直接转矩控制中利用转矩、磁链误差及定子磁链位置信息确定预选电压矢量, 减少MPTC系统中电压矢量的枚举次数. 然后, 利用价值函数进行二次筛选得到最优电压矢量. 为了实现开路故障下的容错控制, 提出了一种更换备选电压矢量表的开路故障容错控制策略. 实验结果表明, 基于电压矢量预选的FTPMV-RDM模型, 本文预测转矩控制算法能够在无故障和一相开路故障下抑制电流畸变, 进而有效降低转矩和磁链脉动.     

Sensorless direct torque control of an induction motor by a TLS-based MRAS observer with adaptive integration

This article presents a new speed and flux estimation algorithm for high-performance direct torque control (DTC) induction motor drives based on model reference adaptive systems (MRAS) observers using linear artificial neural networks (ANNs). Two completely new improvements of MRAS speed and flux observers are presented here: the first is a solution to the open-loop integration problem in the reference model, based on the voltage model of the induction machine, by means of a new adaptive neural integrator, the second is the employment of a new adaptation law in the ANN adaptive model, based on the total least-squares (TLS) technique. In particular, the adaptive neural integrator is based on two adaptive noise filters which completely cancel any DC drift present in the voltage or current signals to be integrated. This neural integrator does not need any a priori training of its two only neurons, adapting itself on-line. With regard to the ANN-based adaptive model, since the most suitable least-square technique to be used for training is the TLS technique, here the neuron is trained on-line by means of a TLS EXIN algorithm which is the only neural network able to solve a TLS problem recursively. Also the TLS EXIN algorithm does not require any a priori training, since it adapts itself recursively on-line. Moreover, to improve the dynamical performances of the speed loop of the drive, the adaptive model has been used as predictor, i.e. without any feed-back between its outputs and its inputs. The sensorless algorithm has been verified experimentally both on the classic DTC technique and on the DTC-SVM (space vector modulation), by adopting a proper test set-up. The speed observer has been tested in the most challenging operating conditions. The experimental results show that the dynamical performances of the sensorless drive are comparable or even better than those obtained with the corresponding DTC drives with encoders as for the medium to high-speed ranges. As for low-speed ranges, the presented sensorless DTC algorithm outcomes the performance presented in the literature for MRAS systems, thus permitting to have an accurate estimation equal or better than that obtainable with more complex observers. Finally, experimental results show that the MRAS speed observer is robust to load torque perturbations and permits zero-speed operation at no-load conditions.     

SR电机单神经元PID直接转矩控制系统

针对采用常规PID控制器很难取得很好的控制效果,提出了单神经元PID与常规PID复合控制的开关磁阻电机调速系统的新方法,利用具有自学习和自适应能力的单神经元来构成开关磁阻电机的单神经元自适应控制器,不但结构简单,而且能适应环境变化,具有较强的鲁棒性。以速度误差为系统外环输入,大偏差时采用常规PID控制,小偏差时采用单神经元控制。外环的输出变量为内环的目标转矩,送入60kW三相6/4结构的开关磁阻电机直接转矩调速系统内环。仿真结果表明,这种复合控制方法解决了常规控制方法因电机数学模型难以精确确定而无法确定控制参数的问题,并克服了常规P I D控制器参数固定,控制非线性系统差的缺点,很好的解决了系统上升时间与超调的矛盾。系统具有很好的抗干扰能力与鲁棒性。     

Model-based diagnosis and fault tolerant control for ensuring torque functional safety of pedal-by-wire systems

This paper presents a model based approach for defining automotive functional safety requirements and provides a solution to ensure functional safety through model-based diagnosis and fault tolerant control. This model-based approach is consistent with ISO 26262 – functional safety standard. In particular, this paper presents the necessary steps for defining and implementing functional safety requirements, including item and function definition, Hazard Analysis and Risk Assessment, as well as the design of a model-based diagnostic and fault tolerant control (FTC) system that can lead to a systematic solution to automotive functional safety problems. The methodology proposed in this paper is applied to the problem of torque functional safety of pedal-by-wire systems.     

矿井提升机直接转矩控制系统转矩脉动最优控制

针对矿井提升机直接转矩控制系统低速段运行时存在转矩脉动过大的问题,提出了一种矿井提升机转矩脉动最优控制方法。该方法以预测模型为基础,采用零电压矢量注入方式进行最优电压矢量的占空比调整。整个占空比计算过程以转矩脉动最小为设计指标,采用在线计算的方式实时获得最优占空比。实验结果表明,该方法在低速时可有效减小电动机转矩脉动,获得优异的转矩控制性能。     

Active fault tolerant control using state-space self-tuning control approach

This paper presents a new fault tolerant control scheme for unknown multivariable stochastic systems by modifying the conventional state-space self-tuning control approach. For the detection of faults, a quantitative criterion is developed by comparing the innovation process errors occurring in the Kalman filter estimation algorithm, which, for faulty system recovery, a weighting matrix resetting technique is developed by adjusting and resetting the covariance matrices of the parameter estimate obtained in the Kalman filter estimation algorithm to improve the parameter estimation of the faulty systems. The proposed method can effectively cope with partially abrupt and/or gradual system faults and/or input failures with fault detection. The modified state-space self-tuning control scheme can be applied to the multivariable stochastic faulty system without requiring prior knowledge of system parameters and noise properties.     

Design of a novel adaptive TSK-fuzzy speed controller for use in direct torque control induction motor drives

This study proposes an adaptive Takagi-Sugeno-Kang-fuzzy (TSK-fuzzy) speed controller (ATFSC) for use in direct torque control (DTC) induction motor (IM) drives to improve their dynamic responses. The proposed controller consists of the TSK-fuzzy controller, which is used to approximate an ideal control law, and a compensated controller, which is constructed to compensate for the difference between the TSK-fuzzy controller and the ideal control law. Parameter variations and external load disturbances were considered during the design phase to ensure the robustness of the proposed scheme. The parameters of the TSK-fuzzy controller were adjusted online based on the adaptive rules derived in Lyapunov stability theory. The ATFSC, fuzzy control, and PI control schemes were experimentally investigated, using the root mean square error (RMSE) performance index to evaluate each scheme. The robustness of the proposed ATFSC was verified using simulations and experiments, which involved varying parameters and external load disturbances. The experimental results indicate that the ATFSC scheme outperformed the other control schemes.     

永磁同步电动机直接转矩控制的效率优化

针对永磁同步电动机在轻载、高速运行时效率和功率因数下降的问题,提出了一种永磁同步电动机直接转矩控制效率优化策略。该策略通过分析电动机损耗与转矩、转速和定子磁链之间的关系,建立了考虑铁损的永磁同步电动机数学模型,导出了效率最优时的定子磁链幅值;将最优定子磁链计算模块嵌入直接转矩控制系统,构成了效率最优的永磁同步电动机直接转矩控制调速系统。仿真结果表明,该优化策略能有效降低永磁同步电动机功率损耗,提高电动机的运行效率。     

Passivity-based torque and flux tracking for induction motors with magnetic saturation

An observer-based, globally asymptotically stable torque and rotor flux magnitude tracking controller for induction motors under magnetic saturation is proposed. The controller is synthesized using the passivity-based techniques. The paper considers a magnetically saturated π-model of the motor without any simplifying assumptions. Motor fluxes are reconstructed by a closed-loop observer. Closed-loop stability of the overall scheme including the observer is demonstrated. Simulation results are given to illustrate the proposed scheme.     

基于自适应观测器控制系统的快速故障调节

针对基于自适应观测器故障调节设计中的两个难点,即系统满足严格正实(SPR)条件与故障估计的准确性和快速性,首先引入适当的坐标变换,有效地放松了严格SPR条件,适用于一大类控制系统的故障诊断;其次,针对变换后的系统,提出一种快速故障估计的设计方法,明显改善了故障估计的性能;再次,基于故障估计值修正控制律以补偿故障所带来的影响,使故障调节后的系统稳定;最后通过仿真实验验证了该方法的有效性.     

A performance optimization algorithm for controller reconfiguration in fault tolerant distributed model predictive control

This paper presents a performance optimization algorithm for controller reconfiguration in fault tolerant distributed model predictive control for large-scale systems. After the fault has been detected and diagnosed, several controller reconfigurations are proposed as candidate corrective actions for fault compensation. The solution of a set of constrained optimization problems with different actuator and setpoint reconfigurations is derived by means of an original approach, exploiting the information on the active constraints in the non-faulty subsystems. Thus, the global optimization problem is split into two optimization subproblems, which enable the online computational burden to be greatly reduced. Subsequently, the performances of different candidate controller reconfigurations are compared, and the better performing one is selected and then implemented to compensate the fault effects. Efficacy of the proposed approach has been shown by applying it to the benzene alkylation process, which is a benchmark process in distributed model predictive control.     

Supervisory fault tolerant control for a class of uncertain nonlinear systems

This paper focuses on the design of a unique scheme that simultaneously performs fault isolation and fault tolerant control for a class of uncertain nonlinear systems with faults ranging over a finite cover. The proposed framework relies on a supervisory switching among a family of pre-computed candidate controllers without any additional model or filter. The states are ensured to be bounded during the switching delay, which ends when the correct stabilizing controller has been selected. Simulation results about a flexible joint robotic example illustrate the efficiency of the proposed method.     

Multisensor fusion fault tolerant control

In this paper, a multisensor fusion fault tolerant control system with fault detection and identification via set separation is presented. The fault detection and identification unit verifies that for each sensor–estimator combination, the estimation tracking errors lie inside pre-computed sets and discards faulty sensors when their associated estimation tracking errors leave the sets. An active fault tolerant controller is obtained, where the remaining healthy estimates are combined using a technique based on the optimal fusion criterion in the linear minimum-variance sense. The fused estimates are then used to implement a state feedback tracking controller. We ensure closed-loop stability and performance under the occurrence of abrupt sensor faults. Experimental validation, illustrating the multisensor fusion fault tolerant control strategy is included.     

The use of field programmable gate array （FPGA） in direct torque control of induction motor

In this paper, the feasibility of embedding the direct torque control （DTC） of an induction machine into field programmable gate arrays （FPGA） is investigated. DTC of an induction machine is simulated in a MATLAB/Simulink environment using a Xilinx system generator. The resulting design has a flexible and modular structure where the designer can customize the hardware blocks by changing the number of inputs, outputs, and algorithm when it is compared to the designs implemented using classical microcontrollers and digital signal processors. With its flexibility, other control algorithms can easily be programmed and embedded into the FPGA. The above system has been implemented on Xilinx Spartan 3A DSP FPGA controller. Simulation and experimentation have been performed to prove the validity of the proposed methodology.     

直接转矩控制系统的稳定性问题和鲁棒控制器设计

直接转矩控制(DTC)系统的设计不依赖于感应电机的转子参数,但它的低速性能不好.研究发现,即使定子电阻测量得足够准确,根据定子磁链的电压电流模型设计的经典DTC系统的低速性能仍得不到改善.理论分析说明了这些问题存在的必然性,指出了DTC系统在转矩控制和稳定性之间存在的矛盾,给出了一种鲁棒控制器的设计方案.该方案同时使用了定子电阻和定子磁链的电流模型,当定子电阻和磁链模型出现误差时,表现出了好的鲁棒性.实验结果验证了系统的性能.     

可重构模块机器人分散容错控制

针对可重构模块机器人的执行器故障,提出一种基于自适应模糊系统的分散被动容错控制方法.该方法不需要机器人动力学模型与模块之间的信息交换,模块控制器分别采用间接和直接自适应方法设计,自适应参数的更新律基于Lyapunov稳定性理论设计,保证了系统的稳定性和H∞跟踪性能.数值仿真结果表明了所提出方法的有效性.     

高速动车组多模型切换主动容错预测控制

高速动车组持续高速运行,对控制系统的可靠性和抗干扰能力提出了更高要求.结合高速动车组非线性动力学特点和系统运行数据,应用减法聚类和模式分类算法建立高速动车组多模型集;为适应对象和扰动特性的变化建立高速动车组自适应模型;采用基于累计误差最小的切换策略在线选择最优控制模型,据此设计主动容错预测控制算法来实现高速动车组安全高效运行.最后,仿真实例验证了该方法的有效性.