基于滚动时域优化策略的网络化系统状态估计与控制器设计
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摘要
传统点对点控制模式是将控制对象的现场数据通过电缆线集中到中央控制室，由中央处理器计算得到的控制量再通过电缆线下放到现场。随着通信、计算机和控制技术的飞速发展，这种控制模式已经不能满足不断提高的控制系统性能要求，并使得控制模式发生了根本性变化。控制系统是由传感器、控制器和执行器等多个环节组成，每个环节通过共享网络实现与其它环节的信息交换，从而形成网络化控制系统。近年来，网络化控制系统已经成为控制理论研究的热点方向。虽然已取得了不少研究成果，但仍有许多问题尚未解决并对现有的控制方法提出了新的挑战。考虑到滚动时域的优化策略在状态估计与控制器设计上不同于反馈的策略，这样带有丢包、数据量化以及通信约束的网络化系统的估计与控制问题可以基于滚动时域窗口的性能指标进行优化求解，进而取得优越的系统性能。因此，本文针对丢包、数据量化和通信约束，研究了基于滚动时域优化策略的状态估计与控制器设计，建立了丢包、量化和通信约束特征参数与系统参数和性能之间的关系。本文主要内容有：
1）针对随机丢包过程满足独立同分布伯努利序列的网络控制系统，基于滚动时域优化策略，提出了一种能够充分利用滚动窗口内系统输入输出信息的滚动时域状态估计方法，以克服数据包随机丢失带给系统的影响。这种估计方法能够充分利用那些以不等式约束形式出现的关于状态和输入输出的额外信息，提高了状态估计的准确性和合理性。与现有的其它估计方法相比，该方法的一个显著特点在于：如果当前数据包发生丢失，滚动窗口内的一段最新数据而非仅前一个时刻数据或当前数据直接置为零，能够用于估计器设计，这样提高了估计的精度。此外，通过分析估计器的估计性能，以不等式的形式给出了保证估计性能收敛的充分条件。最后，通过仿真示例验证了所提出的滚动时域估计方法的有效性。
2）针对连续丢包数在有界范围内任意变化的网络控制系统，提出了一种基于滚动时域优化策略的网络预测控制方法。首先，考虑到数据在网络中是以包的形式进行传输的这一特性，建立了具有有界丢包过程的网络控制系统模型。随后，基于这个模型，设计出保证系统渐近稳定且具有一定控制性能的网络预测控制器。不同于其它控制方法，这种预测控制策略能够根据系统未来的动态行为，预测出系统未来的控制动作，在数据传输中实现了整个预测控制序列打成一个数据包进行传输而非仅当前控制量的传输，这样当控制量丢失时能够利用预测控制量替代当前丢失的控制量，作用于被控对象，从而克服数据包丢失带给系统的影响。最后，通过一个倒立摆系统的仿真示例验证了所提控制方法的优越性。
3）针对控制量经由通信网络从控制器传输至执行器的过程中而发生数据量化的网络控制系统，提出了一种基于滚动时域优化策略的鲁棒预测控制器设计方法。首先，考虑到控制器-执行器间的通信信道存在数据量化，采用对数形式的量化器来表征这种量化作用并利用扇形有界分析方法，建立了具有控制输入量化的网络控制系统模型。其次，基于所建模型，研究了网络控制系统的量化稳定性问题并将其转化为线性不确定系统的鲁棒控制问题，设计出保证系统渐近稳定的鲁棒预测控制器，并以线性矩阵不等式形式给出了系统可镇定的充分条件。随后，在保证网络控制系统稳定性和具有一定控制性能的基础上，给出了一种求解最粗糙量化密度的锥补线性化方法。最后，通过仿真示例验证了所提算法的有效性。
4）考虑到网络带宽受限使得每个采样时刻只有有限数目的传感器能够通过通信网络将部分测量输出数据传输至远程估计器的这种通信情况，提出了一种基于滚动时域优化策略的动态调度方法，使得估计器在网络资源受限的情况下仍具有良好的估计性能。首先，通过定义一种通信序列，将通信约束转化为一个含有逻辑变量0与1的等式约束，从而将一个具有通信约束的线性时不变系统描述为一个带有等式约束的线性时变系统，并根据此模型提出了一种基于二次型调度指标的滚动时域调度方法，其中该二次型调度指标包括通信成本与估计误差。这种动态调度方法通过在线求解一个混合整数二次规划的优化问题，实时得到通信状态。其次，考虑到具有状态约束的被控对象，提出了一种能够处理这种状态约束的滚动时域状态估计方法，并给出了估计误差范数平方有界的充分条件。最后，通过一个双容液位系统的物理实验验证了所提调度策略的优越性。
The traditional point-to-point control strategy is the one, where the field real-timedata from the controlled plant can be centrally transmitted through the cable to the centralcontrol room and then the control variable computed by the central processing unit can besent to the field. With the rapid development of communication, computer and controltechnology, the traditional point-to-point control structure can not meet the performancerequirements of control systems. Meanwhile, a fundamental change of the traditionalpoint-to-point control structure has taken place. Specifically, control systems are made upof sensors, controllers, actuators and other components each of which can communicatewith others by the shared network, and then Networked Control Systems (NCSs)generated. NCSs have now been one of the hot topics in the control theory research.Though there have been lots of useful results on this issue, lots of problems remain to beunsolved and bring forward new challenges and opportunities to the existing controlmethods. Considering the difference between the moving horizon optimization and thefeedback strategy on the state estimation and the controller design, the estimation andcontrol problem of NCSs with packet dropouts, data quantization and communicationconstraints can be solved based on the performance index of the moving horizon window,which can obtain a good performance. Therefore, based on the moving horizonoptimization strategy, the state estimation and controller design problem of NCSs arerespectively investigated in this thesis. Furthermore, the relations among systemparameters and performances, and parameters characterizing the packet dropouts, dataquantization and communication constraints are established respectively. The maincontents are as follows.
1) Based on the moving horizon optimization strategy, a moving horizon estimation(MHE) method fully utilizing the available input and output information of the system dynamics in sliding window is proposed for NCSs to overcome the influence of the datapacket dropouts which can be modeled by a stochastic variable satisfying the Bernoullibinary distribution. This estimation method can make good use of the additionalinformation about state, control input and output variables shown in the form of inequalityconstraints to enhance the accuracy and rationality of the state estimation. Compared withthe existing other state estimation methods, a distinct character of the proposed estimatoris that when the current measurement is lost during transmission, a batch of the mostrecent measurements instead of the previous value or the current value directly set to zerowill be used to the design of the proposed estimator, which can improve the estimationprecision. Moreover, a sufficient condition in the form of the inequality is presented toguarantee the convergence of the estimation performance. Finally, the efficiency of theproposed MHE can be illustrated by some simulation examples.
2) Based on the moving horizon optimization strategy, a new networked predictivecontrol method is proposed for networked control systems under the network environmentwhere the number of the consecutive data packet dropouts is bounded arbitrarily.Considering the fact that the data in network can be packed into one packet and then canbe transmitted at each instant, the model of the NCSs with bounded packet dropouts isbuilt. Based on the proposed model, the networked predictive controller can be designedto stabilize the system, and a good control performance can also be obtained. Differentfrom other control methods, the proposed method has the unique merits which can predictthe future control action of the system according to the future dynamics of the controlledsystem and can accomplish the network transmission of the data packet including apredictive control sequence, but not only a current predictive control action. When thecontrol packet is lost, the corresponding predictive control can be picked up from thepredictive control sequence conserved in the buffer, and then acts on the controlled system,which can overcome the effect of the packet dropouts on the controlled system. Finally, aninverted pendulum system can be used to verify the superiority of the proposed method.
3) Based on the moving horizon optimization strategy, a new robust model predictivecontrol method is proposed to deal with the control problem of NCSs with dataquantization through the communication network between controller and actuator. Firstly,considering the effect of the data quantization in the controller-actuator channel and applying the logarithmic quantizers to describe this kind of quantization, the model of theNCSs with control input quantization is established based on the sector bound approach.Secondly, relying on the proposed model, the stability of the networked control systemswith quantization is studied which can be converted into the robust control problem of thelinear uncertain systems, and then the robust predictive controller to asymptoticallystabilize the system is designed. Furthermore, the stability conditions of NCSs shown interms of linear matrix inequalities (LMIs) are obtained. On the basis of guaranteeing thestability of NCSs and obtaining a certain control performance, the coarsest quantizationdensity can be also derived by using a cone complementary linearization method. Finally,two simulation examples are given to show the validity of the proposed method.
4) Based on the moving horizon optimization strategy, a novel dynamical schedulingapproach has been firstly proposed to handle the communication scheduling problem ofNCSs with communication constraints which means that because of the limited networkbandwidth only some sensors can be allowed to transmit the partial measured outputs tothe remote estimator through the communication network at each sample instant. By thisway, the state estimator can still have a good estimation performance in the case of thelimited network resources. Firstly, defining the communication sequence to explain thecommunication constraints, the communication constraints can be changed into anequality constraint with a logical variable taking the value of zero and one, and then alinear time-invariant system with communication constraints can be converted into a lineartime-varying system with an equality constraint, and then the moving horizon schedulingmethod is proposed based on a new quadratic performance criterion includingcommunication cost and estimation performance penalties. Consequently, by onlinesolving the optimization problem of the mixed integer quadratic programming, thecommunication scheduling sequence can be derived. Secondly, a moving horizon stateestimation method has been also suggested to estimate the unavailable states of NCSsincorporating state inequality constraints. It is further analyzed that sufficient conditionsare presented for the boundness on the square norm of the estimation error. Finally, apractical experiment on a two-tank liquid-level system is given to demonstrate theadvantages of the proposed scheduling method.
1）针对随机丢包过程满足独立同分布伯努利序列的网络控制系统，基于滚动时域优化策略，提出了一种能够充分利用滚动窗口内系统输入输出信息的滚动时域状态估计方法，以克服数据包随机丢失带给系统的影响。这种估计方法能够充分利用那些以不等式约束形式出现的关于状态和输入输出的额外信息，提高了状态估计的准确性和合理性。与现有的其它估计方法相比，该方法的一个显著特点在于：如果当前数据包发生丢失，滚动窗口内的一段最新数据而非仅前一个时刻数据或当前数据直接置为零，能够用于估计器设计，这样提高了估计的精度。此外，通过分析估计器的估计性能，以不等式的形式给出了保证估计性能收敛的充分条件。最后，通过仿真示例验证了所提出的滚动时域估计方法的有效性。
2）针对连续丢包数在有界范围内任意变化的网络控制系统，提出了一种基于滚动时域优化策略的网络预测控制方法。首先，考虑到数据在网络中是以包的形式进行传输的这一特性，建立了具有有界丢包过程的网络控制系统模型。随后，基于这个模型，设计出保证系统渐近稳定且具有一定控制性能的网络预测控制器。不同于其它控制方法，这种预测控制策略能够根据系统未来的动态行为，预测出系统未来的控制动作，在数据传输中实现了整个预测控制序列打成一个数据包进行传输而非仅当前控制量的传输，这样当控制量丢失时能够利用预测控制量替代当前丢失的控制量，作用于被控对象，从而克服数据包丢失带给系统的影响。最后，通过一个倒立摆系统的仿真示例验证了所提控制方法的优越性。
3）针对控制量经由通信网络从控制器传输至执行器的过程中而发生数据量化的网络控制系统，提出了一种基于滚动时域优化策略的鲁棒预测控制器设计方法。首先，考虑到控制器-执行器间的通信信道存在数据量化，采用对数形式的量化器来表征这种量化作用并利用扇形有界分析方法，建立了具有控制输入量化的网络控制系统模型。其次，基于所建模型，研究了网络控制系统的量化稳定性问题并将其转化为线性不确定系统的鲁棒控制问题，设计出保证系统渐近稳定的鲁棒预测控制器，并以线性矩阵不等式形式给出了系统可镇定的充分条件。随后，在保证网络控制系统稳定性和具有一定控制性能的基础上，给出了一种求解最粗糙量化密度的锥补线性化方法。最后，通过仿真示例验证了所提算法的有效性。
4）考虑到网络带宽受限使得每个采样时刻只有有限数目的传感器能够通过通信网络将部分测量输出数据传输至远程估计器的这种通信情况，提出了一种基于滚动时域优化策略的动态调度方法，使得估计器在网络资源受限的情况下仍具有良好的估计性能。首先，通过定义一种通信序列，将通信约束转化为一个含有逻辑变量0与1的等式约束，从而将一个具有通信约束的线性时不变系统描述为一个带有等式约束的线性时变系统，并根据此模型提出了一种基于二次型调度指标的滚动时域调度方法，其中该二次型调度指标包括通信成本与估计误差。这种动态调度方法通过在线求解一个混合整数二次规划的优化问题，实时得到通信状态。其次，考虑到具有状态约束的被控对象，提出了一种能够处理这种状态约束的滚动时域状态估计方法，并给出了估计误差范数平方有界的充分条件。最后，通过一个双容液位系统的物理实验验证了所提调度策略的优越性。
The traditional point-to-point control strategy is the one, where the field real-timedata from the controlled plant can be centrally transmitted through the cable to the centralcontrol room and then the control variable computed by the central processing unit can besent to the field. With the rapid development of communication, computer and controltechnology, the traditional point-to-point control structure can not meet the performancerequirements of control systems. Meanwhile, a fundamental change of the traditionalpoint-to-point control structure has taken place. Specifically, control systems are made upof sensors, controllers, actuators and other components each of which can communicatewith others by the shared network, and then Networked Control Systems (NCSs)generated. NCSs have now been one of the hot topics in the control theory research.Though there have been lots of useful results on this issue, lots of problems remain to beunsolved and bring forward new challenges and opportunities to the existing controlmethods. Considering the difference between the moving horizon optimization and thefeedback strategy on the state estimation and the controller design, the estimation andcontrol problem of NCSs with packet dropouts, data quantization and communicationconstraints can be solved based on the performance index of the moving horizon window,which can obtain a good performance. Therefore, based on the moving horizonoptimization strategy, the state estimation and controller design problem of NCSs arerespectively investigated in this thesis. Furthermore, the relations among systemparameters and performances, and parameters characterizing the packet dropouts, dataquantization and communication constraints are established respectively. The maincontents are as follows.
1) Based on the moving horizon optimization strategy, a moving horizon estimation(MHE) method fully utilizing the available input and output information of the system dynamics in sliding window is proposed for NCSs to overcome the influence of the datapacket dropouts which can be modeled by a stochastic variable satisfying the Bernoullibinary distribution. This estimation method can make good use of the additionalinformation about state, control input and output variables shown in the form of inequalityconstraints to enhance the accuracy and rationality of the state estimation. Compared withthe existing other state estimation methods, a distinct character of the proposed estimatoris that when the current measurement is lost during transmission, a batch of the mostrecent measurements instead of the previous value or the current value directly set to zerowill be used to the design of the proposed estimator, which can improve the estimationprecision. Moreover, a sufficient condition in the form of the inequality is presented toguarantee the convergence of the estimation performance. Finally, the efficiency of theproposed MHE can be illustrated by some simulation examples.
2) Based on the moving horizon optimization strategy, a new networked predictivecontrol method is proposed for networked control systems under the network environmentwhere the number of the consecutive data packet dropouts is bounded arbitrarily.Considering the fact that the data in network can be packed into one packet and then canbe transmitted at each instant, the model of the NCSs with bounded packet dropouts isbuilt. Based on the proposed model, the networked predictive controller can be designedto stabilize the system, and a good control performance can also be obtained. Differentfrom other control methods, the proposed method has the unique merits which can predictthe future control action of the system according to the future dynamics of the controlledsystem and can accomplish the network transmission of the data packet including apredictive control sequence, but not only a current predictive control action. When thecontrol packet is lost, the corresponding predictive control can be picked up from thepredictive control sequence conserved in the buffer, and then acts on the controlled system,which can overcome the effect of the packet dropouts on the controlled system. Finally, aninverted pendulum system can be used to verify the superiority of the proposed method.
3) Based on the moving horizon optimization strategy, a new robust model predictivecontrol method is proposed to deal with the control problem of NCSs with dataquantization through the communication network between controller and actuator. Firstly,considering the effect of the data quantization in the controller-actuator channel and applying the logarithmic quantizers to describe this kind of quantization, the model of theNCSs with control input quantization is established based on the sector bound approach.Secondly, relying on the proposed model, the stability of the networked control systemswith quantization is studied which can be converted into the robust control problem of thelinear uncertain systems, and then the robust predictive controller to asymptoticallystabilize the system is designed. Furthermore, the stability conditions of NCSs shown interms of linear matrix inequalities (LMIs) are obtained. On the basis of guaranteeing thestability of NCSs and obtaining a certain control performance, the coarsest quantizationdensity can be also derived by using a cone complementary linearization method. Finally,two simulation examples are given to show the validity of the proposed method.
4) Based on the moving horizon optimization strategy, a novel dynamical schedulingapproach has been firstly proposed to handle the communication scheduling problem ofNCSs with communication constraints which means that because of the limited networkbandwidth only some sensors can be allowed to transmit the partial measured outputs tothe remote estimator through the communication network at each sample instant. By thisway, the state estimator can still have a good estimation performance in the case of thelimited network resources. Firstly, defining the communication sequence to explain thecommunication constraints, the communication constraints can be changed into anequality constraint with a logical variable taking the value of zero and one, and then alinear time-invariant system with communication constraints can be converted into a lineartime-varying system with an equality constraint, and then the moving horizon schedulingmethod is proposed based on a new quadratic performance criterion includingcommunication cost and estimation performance penalties. Consequently, by onlinesolving the optimization problem of the mixed integer quadratic programming, thecommunication scheduling sequence can be derived. Secondly, a moving horizon stateestimation method has been also suggested to estimate the unavailable states of NCSsincorporating state inequality constraints. It is further analyzed that sufficient conditionsare presented for the boundness on the square norm of the estimation error. Finally, apractical experiment on a two-tank liquid-level system is given to demonstrate theadvantages of the proposed scheduling method.
引文
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