过程控制系统的故障检测诊断与容错控制
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摘要
过程系统的生产环境通常处于高温高压或低温真空等极端环境,如操作不当或因控制系统发生故障,可能造成生产中断、爆炸、毒气泄漏等危险。为了提高生产的安全性,对控制系统进行有效地故障检测、诊断与容错补偿措施是十分必要的。且多数过程控制对象都具有慢变化特性,其控制精度的要求比航空航天或运动控制精度要低,这就为故障检测、诊断与容错控制技术在工业过程中的应用提供了可能性。实际的容错控制策略不仅要保证在故障模式下系统的稳定,同时也要尽可能满足一定的性能指标或约束条件,因此进一步探索在多目标或多约束条件下的满意容错控制方法就是非常必要的。本文重点研究过程控制系统的故障检测、诊断与容错控制理论与技术,取得的主要研究成果与创新点如下:
1.建立了符合工业实际的多种传感器故障和执行器故障(阀门故障)的合理描述模型,改进了现有的“二状态故障模型”描述方法,研究了基于神经网络建模与自适应阈值技术的鲁棒故障检测与诊断方法,并进一步设计了一种有效的厂级主动补偿容错控制策略。分别在三水箱实验平台和DAMADICS平台上验证了上述方法的有效性。
2.提出了一种基于特征样本、核主元分析和核函数梯度算法的故障检测与诊断方法。该方法采用了特征样本提取技术解决了过程监控中核矩阵K计算量大的问题,利用核函数梯度算法计算每个监控变量对统计量T~2和SPE贡献度诊断故障信号,并在Tennessee Eastman化工仿真平台的多种不同类型故障模式下,验证了上述策略的有效性。
3.针对复杂工业过程中多回路控制和复杂操作等因素造成的工业故障诊断难度加剧问题,提出了一种基于独立成分分析和支持向量机的集成故障诊断方法。针对中石化丁二烯普通精馏生产装置的实际生产过程,利用连续三年的实际工业故障数据,验证了提出的ICA-SVM集成故障诊断方法的有效性和快速性。
4.针对一类模型未知的多变量非线性系统,提出了一种基于扩展卡尔曼滤波在线学习算法的RBF网络逆模容错控制方法。该方法采用扩展卡尔曼滤波算法在线更新网络权值,学习系统的时变参数或故障动态,并利用自适应RBF模型的迭代逆模算法求解故障动态下最优的控制变量,实现故障容错控制。在三水箱实验平台的多种泄漏故障模式下验证了上述控制策略的有效性。
5.为了满足工业实际中要求容错控制策略不仅保证故障模式下系统的稳定,同时还须满足一定的性能指标或约束条件的要求,本文还进一步对多指标约束下的复杂控制系统满意容错控制方法进行了初步的研究。针对同时具有状态和控制时滞的不确定离散时滞系统,在一般执行器故障模式下,研究了基于状态反馈的H∞满意容错控制和鲁棒保成本控制问题;针对非线性T-S模糊系统,提出了稳定度、输入和输出相容指标约束下的满意容错控制器设计方法,和在极点、状态方差和H_∞相容指标约束下满意容错控制器的设计方法;针对非线性T-S模糊时滞系统,分别设计了含时滞记忆和无时滞记忆的状态反馈H∞满意容错控制器。
最后,在总结全文工作的基础上,给出了本文后续需进一步探讨的一些问题。
The operation of process industry usually takes place in extreme conditions, such as high-temperature & high-pressure or low temperature & vaccum. The maloperation or system faults will cause the hazardous status, for example, production stoppage, equipment explosion or toxic gas leakage. To improve manufacturing safety, it is necessary for control system to effectively detect and diagnose fault. On the other side, many process industries are characteristic with low dynamic performance, and the control precisions are lower than the aerospace control precision. It is more possible for fault detection & diagnosis and fault-tolerant control to successfully apply to process industry. Some new satisfactory tolerant control methods with multi-objects and multi- constraint conditions need to be further explored. The fault detection & diagnosis and fault-tolerant control technique for process control system are investigated in this paper. Some main research findings and innovation are listed as following:
1. Based on the industry practice, rational describing models for sensor faults and valve faults are founded, which can amend the existing two fault description models. Grounded on the above fault models, an effective plant active tolerant control method is proposed by incorporating the intelligent modeling strategy with an adaptive threshold scheme. The simulation results, including three-tank benchmark problem and DAMADICS benchmark problem validate the proposed method.
2. A fault detection & diagnosis method based on feature sample extracting, Kernel PCA and the gradient arithmetic of kernel function is developed. The feature extraction method can solve the calculation problem of the kernel matrix K during monitoring process. The contribution degrees of each variable to Hotelling's T~2 and SPE based on the gradient arithmetic of kernel function are applied to diagnose complex faults. To demonstrate the performance, the proposed method was applied to the Tennessee Eastman (TE) process. The simulation results showed that the proposed method could effectively identify various types of fault sources.
3. A novel fault diagnosis method is proposed by incorporating independent component analysis (ICA) strategy with support vector machines (SVM), which can effectively settle the puzzles of the correlative industry faults which arise from the nonlinearity, multi-loop, complex operation and so on. The proposed monitoring method was applied to fault detection and diagnosis in the butadiene industry distillation column. The simulation results clearly show the power and advantages of ICA-SVM method.
4. An active fault tolerant control scheme based on the inversion model of adaptive RBF neural network is proposed for multi-variable nonlinear systems. The extend Kalman filter (EKF) algorithm is used to on-line update network variables for learning fault dynamics and time-varying parameters. The optimal output value of adaptive controller is worked out by the iterative algorithm of RBF inverse model to maintain the system performances after fault occurrence. The simulation results on the three-tank process with leakage faults validate the proposed method.
5. The tolerant control strategy for process control system should not only guarantee the stability of fault systems, but also satisfy some performance indexs or constraints. The satifisfactory fault-tolerant control methods with multi-indices constraint are investigated. For uncertain discrete time-delay systems against actuator failures, the state-feedback based H∞satifisfactory fault-tolerant control method and guaranted cost control method are investigated. For the fuzzy nonlinear system described by T-S fuzzy models against actuator failures, the satifisfactory tolerant control method with the constraint on decay rate, control input and output is investigated, and the satifisfactory tolerant control method with the constraint on pole, state variance and H∞consistent index is also studied. For nonlinear fuzzy time-delay system against actuator failures, the H∞satifisfactory fault-tolerant controllers with time-delay memory and memory-less are separately designed.
Finally, based on generalizing full text, some problems which need to be further researched are discussed.
1.建立了符合工业实际的多种传感器故障和执行器故障(阀门故障)的合理描述模型,改进了现有的“二状态故障模型”描述方法,研究了基于神经网络建模与自适应阈值技术的鲁棒故障检测与诊断方法,并进一步设计了一种有效的厂级主动补偿容错控制策略。分别在三水箱实验平台和DAMADICS平台上验证了上述方法的有效性。
2.提出了一种基于特征样本、核主元分析和核函数梯度算法的故障检测与诊断方法。该方法采用了特征样本提取技术解决了过程监控中核矩阵K计算量大的问题,利用核函数梯度算法计算每个监控变量对统计量T~2和SPE贡献度诊断故障信号,并在Tennessee Eastman化工仿真平台的多种不同类型故障模式下,验证了上述策略的有效性。
3.针对复杂工业过程中多回路控制和复杂操作等因素造成的工业故障诊断难度加剧问题,提出了一种基于独立成分分析和支持向量机的集成故障诊断方法。针对中石化丁二烯普通精馏生产装置的实际生产过程,利用连续三年的实际工业故障数据,验证了提出的ICA-SVM集成故障诊断方法的有效性和快速性。
4.针对一类模型未知的多变量非线性系统,提出了一种基于扩展卡尔曼滤波在线学习算法的RBF网络逆模容错控制方法。该方法采用扩展卡尔曼滤波算法在线更新网络权值,学习系统的时变参数或故障动态,并利用自适应RBF模型的迭代逆模算法求解故障动态下最优的控制变量,实现故障容错控制。在三水箱实验平台的多种泄漏故障模式下验证了上述控制策略的有效性。
5.为了满足工业实际中要求容错控制策略不仅保证故障模式下系统的稳定,同时还须满足一定的性能指标或约束条件的要求,本文还进一步对多指标约束下的复杂控制系统满意容错控制方法进行了初步的研究。针对同时具有状态和控制时滞的不确定离散时滞系统,在一般执行器故障模式下,研究了基于状态反馈的H∞满意容错控制和鲁棒保成本控制问题;针对非线性T-S模糊系统,提出了稳定度、输入和输出相容指标约束下的满意容错控制器设计方法,和在极点、状态方差和H_∞相容指标约束下满意容错控制器的设计方法;针对非线性T-S模糊时滞系统,分别设计了含时滞记忆和无时滞记忆的状态反馈H∞满意容错控制器。
最后,在总结全文工作的基础上,给出了本文后续需进一步探讨的一些问题。
The operation of process industry usually takes place in extreme conditions, such as high-temperature & high-pressure or low temperature & vaccum. The maloperation or system faults will cause the hazardous status, for example, production stoppage, equipment explosion or toxic gas leakage. To improve manufacturing safety, it is necessary for control system to effectively detect and diagnose fault. On the other side, many process industries are characteristic with low dynamic performance, and the control precisions are lower than the aerospace control precision. It is more possible for fault detection & diagnosis and fault-tolerant control to successfully apply to process industry. Some new satisfactory tolerant control methods with multi-objects and multi- constraint conditions need to be further explored. The fault detection & diagnosis and fault-tolerant control technique for process control system are investigated in this paper. Some main research findings and innovation are listed as following:
1. Based on the industry practice, rational describing models for sensor faults and valve faults are founded, which can amend the existing two fault description models. Grounded on the above fault models, an effective plant active tolerant control method is proposed by incorporating the intelligent modeling strategy with an adaptive threshold scheme. The simulation results, including three-tank benchmark problem and DAMADICS benchmark problem validate the proposed method.
2. A fault detection & diagnosis method based on feature sample extracting, Kernel PCA and the gradient arithmetic of kernel function is developed. The feature extraction method can solve the calculation problem of the kernel matrix K during monitoring process. The contribution degrees of each variable to Hotelling's T~2 and SPE based on the gradient arithmetic of kernel function are applied to diagnose complex faults. To demonstrate the performance, the proposed method was applied to the Tennessee Eastman (TE) process. The simulation results showed that the proposed method could effectively identify various types of fault sources.
3. A novel fault diagnosis method is proposed by incorporating independent component analysis (ICA) strategy with support vector machines (SVM), which can effectively settle the puzzles of the correlative industry faults which arise from the nonlinearity, multi-loop, complex operation and so on. The proposed monitoring method was applied to fault detection and diagnosis in the butadiene industry distillation column. The simulation results clearly show the power and advantages of ICA-SVM method.
4. An active fault tolerant control scheme based on the inversion model of adaptive RBF neural network is proposed for multi-variable nonlinear systems. The extend Kalman filter (EKF) algorithm is used to on-line update network variables for learning fault dynamics and time-varying parameters. The optimal output value of adaptive controller is worked out by the iterative algorithm of RBF inverse model to maintain the system performances after fault occurrence. The simulation results on the three-tank process with leakage faults validate the proposed method.
5. The tolerant control strategy for process control system should not only guarantee the stability of fault systems, but also satisfy some performance indexs or constraints. The satifisfactory fault-tolerant control methods with multi-indices constraint are investigated. For uncertain discrete time-delay systems against actuator failures, the state-feedback based H∞satifisfactory fault-tolerant control method and guaranted cost control method are investigated. For the fuzzy nonlinear system described by T-S fuzzy models against actuator failures, the satifisfactory tolerant control method with the constraint on decay rate, control input and output is investigated, and the satifisfactory tolerant control method with the constraint on pole, state variance and H∞consistent index is also studied. For nonlinear fuzzy time-delay system against actuator failures, the H∞satifisfactory fault-tolerant controllers with time-delay memory and memory-less are separately designed.
Finally, based on generalizing full text, some problems which need to be further researched are discussed.
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