球磨机多模型控制系统

提出了一种用于多变量模型不确定性控制的方法 ,克服了常规解耦设计没有考虑模型的不确定性 ,当对象模型摄动时解耦效果可能退化的缺陷。其要点是把整个工作范围按工作特性划分为若干个子区间 ,并以确定性模型表示。运用该概念 ,从对角优势化的定义出发 ,提出一种基于多模型的多变量控制系统逆奈奎斯特阵列设计方法 ,并应用于火电厂球磨机控制系统设计。从各模型对应的 Gershgorin带及以单位阶跃作为输入的仿真结果可看出 ,所设计的多变量解耦控制系统具有较强的鲁棒性和满意的调节品质 ;且在不增加设备投资的情况下 。

石灰炉炉况诊断及多模型集成智能控制系统的开发与应用

研制了石灰炉计算机仿真与优化模型 ,开发了石灰炉炉况诊断及多模型智能控制系统 (LDMICS)。该系统能进行热工实时计算、炉况实时诊断与操作运行的智能模糊控制 ,且具有自学习和自适应功能。系统投运后 ,能显著提高炉子产能 ,降低焦比 ,提高CO2 浓度 。

Multivariable Fuzzy Predictive Control Based on the Modified CPN Model

Through modifying the CPN model, a kind of multivariable fuzzy model is put forward, and the matching fuzzy multistep predictive control algorithm is deduced based on the model. The modified model works in a competitive output manner which results in its local representation property. While studying on line, only a few parameters need to be regulated. So the model has the merits of fast learning and on line self organizing modeling. The control algorithm is simple, adaptive and useful in multivariable and time delay systems. Applying the algorithm in a paper making system, simulation shows its good effect.

Multimodel Approach for Intelligent Control and Applications

The use of the multimodel approach in the modelling, analysis and control of non-linear complex and/or ill-defined systems was advocated by many researchers. This approach supposes the definition of a set of local models valid in a given region or domain. Different strategies exist in the literature and are generally based on a partitioning of the non-linear system’s full range of operation into multiple smaller operating regimes each of which is associated with a locally valid model or controller. However, most of these strategies, which suppose the determination of these local models as well as their validity domain, remain arbitrary and are generally fixed thanks to a certain a priori knowledge of the system whatever its order. Recently, we have proposed a new approach to derive a multimodel basis which allows us to limit the number of models in the basis to almost four models. Meanwhile, the transition problem between the different models, which may use either a simple commutation or a fusion technique, remains still arise. In this plenary talk, a fuzzy fusion technique is presented and has the following main advantages: （1） use of a fuzzy partitioning in order to determine the validity of each model which enhances the robustness of the solution; 2 introduction, besides the four extreme models, of another model, called average model, determined as an average of the boundary models.

STOCHASTIC ADAPTIVE SWITCHING CONTROL BASED ON MULTIPLE MODELS

It is well known that the transient behaviors of the traditional adaptive control may be very poor in general, and that the adaptive control designed based on switching between multiple models is an intuitively appealing and practically feasible approach to improve the transient performances. In this paper, we shall prove that for a typical class of linear systems disturbed by random noises, the multiple model based least-squares(LS) adaptive switching control is stable and convergent, and has the same convergence rate as that established for the standard least-squares-based self-tunning regulators. Moreover, the mixed case combining adaptive models with fixed models is also considered.

SOFT CONTROL ON COLLECTIVE BEHAVIOR OF A GROUP OF AUTONOMOUS AGENTS BY A SHILL AGENT

This paper asks a new question： how can we control the collective behavior of self-organized multi-agent systems？ We try to answer the question by proposing a new notion called ＇Soft Control＇ which keeps the local rule of the existing agents in the system. We show the feasibility of soft control by a case study. Consider the simple but typical distributed multi-agent model proposed by Vicsek et al. for flocking of birds： each agent moves with the same speed but with different headings which are updated using a local rule based on the average of its own heading and the headings of its neighbors. Most studies of this model are about the self-organized collective behavior, such as synchronization of headings. We want to intervene in the collective behavior （headings） of the group by soft control. A specified method is to add a special agent, called a ＇Shill＇, which can be controlled by us but is treated as an ordinary agent by other agents. We construct a control law for the shill so that it can synchronize the whole group to an objective heading. This control law is proved to be effective analytically and numerieally. Note that soft control is different from the approach of distributed control. It is a natural way to intervene in the distributed systems. It may bring out many interesting issues and challenges on the control of complex systems.

PERFORMANCE EVALUATION FOR DAMPING CONTROLLERS OF POWER SYSTEMS BASED ON MULTI-AGENT MODELS

This paper proposes a multi-layer multi-agent model for the performance evaluation of powersystems,which is different from the existing multi-agent ones.To describe the impact of the structureof the networked power system,the proposed model consists of three kinds of agents that form threelayers:control agents such as the generators and associated controllers,information agents to exchangethe information based on the wide area measurement system (WAMS) or transmit control signals tothe power system stabilizers (PSSs),and network-node agents such as the generation nodes and loadnodes connected with transmission lines.An optimal index is presented to evaluate the performance ofdamping controllers to the system's inter-area oscillation with respect to the information-layer topology.Then,the authors show that the inter-area information exchange is more powerful than the exchangewithin a given area to control the inter-area low frequency oscillation based on simulation analysis.