磨矿过程的多变量模糊监督控制

针对磨矿过程的关键工艺指标-磨矿粒度难以用现有控制方法进行有效控制的难题,提出一种由模糊监督器、磨矿控制回路预设定模型和磨矿粒度预报器组成的磨矿过程多变量模糊监督控制(MFSC)方法.MFSC方法用于对磨矿过程进行监督,根据工况变化对回路控制器设定值进行调整.通过控制回路跟踪调整后的设定值,可将磨矿粒度控制在期望目标范围内.工业试验表明了所提出方法的有效性.     

Intelligent distributed and supervised flow control methodology for production systems

This paper deals with the development of an intelligent distributed and supervised control approach for high-volume production systems, in which the flow of parts can be approximated by a continuous (fluid) model. The proposed approach is based on the decomposition of the production system into elementary modules in order to reduce the control design computational complexity. In this context, a two levels control structure is proposed. At the local level, a surplus-based principle is adopted to regulate the production flow for each module according to the distributed structure. The proposed control methodology decides how to adjust the production rate in order to avoid system overloading and eliminate machine starvation or blocking. In this context, the local control law is synthesized by using the Takagi–Sugeno fuzzy systems. At the high level, a supervisory controller is designed to improve the overall system performances. A supervisor provides an additive component for each local controller when the overall system performances deviate from their acceptable domains (degraded mode). This is done by combining both local and global information into a unified formalism by using aggregation operators and according to fuzzy interval representation of the desired objectives. Finally, the feasibility of the proposed methodology is validated with simulation examples.     

The challenge of modelling supervisory systems using fuzzy cognitive maps

This paper examines fuzzy cognitive map (FCM) theory and its use in supervisory control systems. An FCM is a graph used to depict cause and effect between concepts that stand for the states and variables of the system. An FCM represents the whole system in a symbolic manner, just as humans have stored the operation of the system in their brains, thus it is possible to help man's intention for more intelligent and autonomous systems. FCM representation, construction and a mathematical model are examined; a generic system is proposed and the implementation of FCM in a process control problem is illustrated and a model for supervisors of manufacturing systems is discussed. Although an FCM seems to be a simple model of system behaviour, it appears to be a powerful and effective tool describing the behaviour of a system and representing the accumulated knowledge of a system.     

Robust supervisory control of a class of timed discrete event systems under partial observation

This paper studies robust supervisory control of timed discrete event systems proposed by Brandin and Wonham. Given a set of possible models which includes the exact model of the plant, the objective is to synthesize a robust supervisor such that it achieves legal behavior for all possible models. We show that controllability for each possible model and observability for a suitably defined aggregate model are necessary and sufficient conditions for the existence of a solution to the robust supervisory control problem. Moreover, when there does not exist a solution, a maximally permissive robust supervisor is synthesized under the assumption that all controllable events are observable.     

A fuzzy logic based supervisory hierarchical control scheme for real time pressure control

This paper describes a supervisory hierarchical fuzzy controller （SHFC） for regulating pressure in a real-time pilot pressure control system. The input scaling factor tuning of a direct expert controller is made using the error and process input parameters in a closed loop system in order to obtain better controller performance for set-point change and load disturbances. This on-line tuning method reduces operator involvement and enhances the controller performance to a wide operating range. The hierarchical control scheme consists of an intelligent upper level supervisory fuzzy controller and a lower level direct fuzzy controller. The upper level controller provides a mechanism to the main goal of the system and the lower level controller delivers the solutions to a particular situation. The control algorithm for the proposed scheme has been developed and tested using an ARM7 microcontroller-based embedded target board for a nonlinear pressure process having dead time. To demonstrate the effectiveness, the results of the proposed hierarchical controller, fuzzy controller and conventional proportional-integral （PI） controller are analyzed. The results prove that the SHFC performance is better in terms of stability and robustness than the conventional control methods.     

Hybrid supervisory control using recurrent fuzzy neural network fortracking periodic inputs

A hybrid supervisory control system using a recurrent fuzzy neural network (RFNN) is proposed to control the mover of a permanent magnet linear synchronous motor (PMLSM) servo drive for the tracking of periodic reference inputs. First, the field-oriented mechanism is applied to formulate the dynamic equation of the PMLSM. Then, a hybrid supervisory control system, which combines a supervisory control system and an intelligent control system, is proposed to control the mover of the PMLSM for periodic motion. The supervisory control law is designed based on the uncertainty bounds of the controlled system to stabilize the system states around a predefined bound region. Since the supervisory control law will induce excessive and chattering control effort, the intelligent control system is introduced to smooth and reduce the control effort when the system states are inside the predefined bound region. In the intelligent control system, the RFNN control is the main tracking controller which is used to mimic a idea control law and a compensated control is proposed to compensate the difference between the idea control law and the RFNN control. The RFNN has the merits of fuzzy inference, dynamic mapping and fast convergence speed, In addition, an online parameter training methodology, which is derived using the Lyapunov stability theorem and the gradient descent method, is proposed to increase the learning capability of the RFNN. The proposed hybrid supervisory control system using RFNN can track various periodic reference inputs effectively with robust control performance.     

Active control of earthquake excited structures using fuzzy supervisory technique

A fuzzy supervisory technique for the active control of earthquake-excited building structures is studied in this paper. The method has a hierarchical structure, which consists of a supervisor at the higher level and several sub-controllers at the lower level. Each sub-controller is designed to reduce the story-drift of each floor by using an optimal control theory and a fuzzy logic is adopted to obtain a desirable supervisor. A fuzzy supervisor appropriately tunes the predesigned control gains at every moment by estimating the state of a structure through the fuzzy inference mechanism. The improved seismic control performance can be achieved by converting a simply designed static gain into a real-time variable dynamic gain through a fuzzy tuning process. Example designs and numerical simulations of an earthquake-excited three-story building are performed to prove the validity of the proposed control strategy.     

Supervisory multiple regime control

The objective of this work is to identify a control algorithm that is capable of handling nonlinear behaviour (operating point dependent) witnessed in most industrial processes. To this end, the proposed solution is that of a supervisory multiple model control scheme, SMMC. This work demonstrates that the multiple model methodology can be recast into a Supervisory approach, whereby the supervisor is employed as a selector. This selector (supervisor) identifies the appropriate local-controller from a fixed family set. Unlike other supervisory techniques a multiple model observer (MMO) is proposed for the selection mechanism. Switching between local-controllers is accomplished bumplessly through a multiple model bumpless transfer scheme. Consequently, producing a continuous control signal as the process transverses between different operating regimes. The key issue in this application is the unique interaction between the local-controllers and the supervisor. This interaction is necessary to ensure global stability is maintained at all times, especially during switching. In short, the SMMC scheme enables the implementation of linear control theory, which is well accepted in industry, to standard nonlinear processes. The SMMC approach warrants the control design to extend beyond normal operating conditions that breakdown when standard linear control techniques are applied. The above notion is applied to a pilot-scale binary distillation column. In this example the column's distinct operating points describe the nonlinear behaviour. The results illustrate that as the distillation column shifted between different operating points the SMMC self-regulates accordingly. This self-regulation ensures that global stability and performance are maintained at an optimum. The entire SMMC design was implemented within a PC Windows-NT environment that was interfaced to an industrial DCS system.     

Supervisory control of nondeterministic discrete-event systems with driven events via masked prioritized synchronization

Studies the supervisory control problem of nondeterministic discrete event systems with driven events in the setting of masked prioritized synchronous composition (MPSC). MPSC was extended from prioritized synchronous composition (PSC) by Kumar and Heymann (2000) in order to permit systems interaction with their environment via interface masks. They also studied the supervisory control problem under the assumption that the set of driven events was empty. In this paper, the aforementioned assumption is relaxed. We first derive relations among behaviors at different levels of the system. Next, we solve the supervisor synthesis problem for controlling the plant behavior as observed at the interface level. Finally, we give a necessary and sufficient condition for the existence of the supervisor for controlling the plant behavior as observed at the plant level. We establish a link between MPSC and PSC by showing that a supervisory control problem in the setting of MPSC can be transferred to a supervisory control problem in the setting of PSC under certain conditions.     

基于模糊控制规则的建筑物结构主动控制的研究

针对地震中建筑物结构主动控制的问题,引入模糊控制规则。该方法采用分层结构,其中包括一个高层的控制器和多个为了降低层间位移的底层子控制器。模糊控制规则能够恰当地调节预先控制在每一时刻所估计的结构状态。改进的地震控制性能通过模糊调节过程将一个简单设计的静态增益转换为实时动态增益。本文在控制器的设计部分充分考虑作动器饱和的状态,并以三层剪切型建筑物结构模型来举例说明。最后模糊规则的运用和Matlab仿真证明这种控制策略的正确性和有效性。     

Online tuning of a supervisory fuzzy controller for low-energy building system using reinforcement learning

This paper proposes a model-free method using reinforcement learning scheme to tune a supervisory controller for a low-energy building system online. The training time and computational demands are reduced by basing the supervisor on sets of fuzzy rules generated by off-line optimisation and by learning the optimal values of only one parameter, which selects the most appropriate set of rules. By carefully choosing the tuning targets, discretizing the state space, parameterizing the fuzzy rule base, using fuzzy trace-back, the proposed method can complete the training process in one season.     

Observability and decentralized control of fuzzy discrete-event systems

Fuzzy discrete-event systems as a generalization of (crisp) discrete-event systems have been introduced in order that it is possible to effectively represent uncertainty, imprecision, and vagueness arising from the dynamic of systems. A fuzzy discrete-event system has been modeled by a fuzzy automaton; its behavior is described in terms of the fuzzy language generated by the automaton. In this paper, we are concerned with the supervisory control problem for fuzzy discrete-event systems with partial observation. Observability, normality, and co-observability of crisp languages are extended to fuzzy languages. It is shown that the observability, together with controllability, of the desired fuzzy language is a necessary and sufficient condition for the existence of a partially observable fuzzy supervisor. When a decentralized solution is desired, it is proved that there exist local fuzzy supervisors if and only if the fuzzy language to be synthesized is controllable and co-observable. Moreover, the infimal controllable and observable fuzzy superlanguage, and the supremal controllable and normal fuzzy sublanguage are also discussed. Simple examples are provided to illustrate the theoretical development.     

Qualitative Event-Based Expert Supervision for Transient Condition Monitoring

This paper addresses the following supervisory problem: a continuous plant (P) is to be supervised via symbolic (or quantised) actions. These symbolic actions suggest the set points for the lower level control loops. The system dynamic is analysed on the supervisory level (K) by a qualitative approach. The relationships between variables and the steady-state references are known. These problems are especially common in chemical process control. The supervisor handles start-up and shut-down procedures and takes appropriate action to solve the sequential or parallel tasks of a basic procedure. The object of this paper is to introduce an approach to solving the problem of how to derive a set of rules from a physical process.The solutions for supervising start-up and shut-down operations in close loop are suitable for large industrial systems, as are as the batch and semi-continuous processes used in order to maintain operations in a dynamic mode. This paper considers the qualitative event-based expert supervision approach to distillation column problems. The development of a general supervision in this work is based on an events generator and a corrective actions generator. The qualitative symbols are based on fuzzy sets. In particular, there are mechanisms for processing the changes in the system variables from qualitative symbols.     

Masked prioritized synchronization for interaction and control of discrete event systems

Extends the formalism of prioritized synchronous composition (PSC), proposed by Heymann for modeling interaction (and control) of discrete event systems, to permit system interaction with their environment via interface masks. This leads to the notion of masked prioritized synchronous composition (MPSC), which we formally define, MPSC can be used to model interaction of systems at single as well as multiple interfaces. We show that MPSC can alternatively be computed by "unmasking" the PSC of "masked" systems, thereby establishing a link between MPSC and PSC. We next prove that MPSC is associative and thus suitable for modeling and analysis of supervisory control of discrete event systems. Finally, we use MPSC of a discrete event plant and a supervisor for controlling the plant behavior and show (constructively) that under the absence of "driven" events, controllability together with normality of the given specification serve as conditions for the existence of a supervisor. This extends the results on supervisory control, which permits control and observation masks to be associated with the plant only.     

智能办公环境中多Agent模糊Q学习研究

目前有关智能办公环境的研究忽视了对建筑环境的考虑,为了给工作人员提供一个节能、舒适、便捷的办公环境,研究了智能办公环境无线网络系统的学习方法,即为系统建立了多智能体（Agent）模型,基于该模型提出了改进的模糊Q学习算法,用于学习用户的行为,以自动控制环境中执行器的动作。通过对环境温度学习的实验,比较了该算法和普通Q学习的MSE（Mean Square Error）值,实验结果表明提出的算法较优。     

Process objects/masked composition: an object-oriented approach formodeling and control of discrete-event systems

An object oriented framework for modeling and supervisory control of discrete-event systems is described. Control and observation masks are encapsulated with process logic to form process objects, and a single type of interconnection operator called masked composition is used to build complex process objects out of simpler component process objects. The approach applies to both deterministic and nondeterministic plant models and supervisory design. In addition to the usual benefits of object-oriented design, such as software reusability, it yields conditions under which the existence of a nondeterministic supervisor implies existence of a deterministic supervisor     

Distributed Computation Multi-agent System

This article addresses a formal model of a distributed computation multi-agent system. This model has evolved from the experimental research on using multi-agent systems as a ground for developing fuzzy cognitive maps. The main paper contribution is a distributed computation multi-agent system definition and mathematical formalization based on automata theory. This mathematical formalization is tested by developing distributed computation multi-agent systems for fuzzy cognitive maps and artificial neural networks – two typical distributed computation systems. Fuzzy cognitive maps are distributed computation systems used for qualitative modeling and behavior simulation, while artificial neural networks are used for modeling and simulating complex systems by creating a non-linear statistical data model. An artificial neural network encapsulates in its structure data patterns that are hidden in the data used to create the network. Both of these systems are well suited for formal model testing. We have used evolutionary incremental development as an agent design method which has shown to be a good approach to develop multi-agent systems according to the formal model of a distributed computation multi-agent system.     

Supervisory control of discrete event systems with state-dependent controllability

This article studies the supervisory control problem of discrete event systems (DES) with state-dependent controllability. The new problem is given with the background of operating systems where the processes and the interrupt service routines (ISR) are supervised and coordinated. The new model is novel because the controllability of an event is changeable in the lifetime of system evolution, and dependent on the system state. Two fundamental problems are concerned with the new model: supervisor existence problem and supervisor synthesis problem. We derive a necessary and sufficient condition for the existence of the supervisor, and introduce an algorithm to synthesise the supremal supervisor in a given specification. With the background of process and ISR management in operating systems, some examples are given to show how the new model can be applied to practical computing.