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1、智能控制系统智能控制系统可以从多个方面来描述，主要包含智能系统的特征和功能，这些也是控制领域所关心的特征。首先讨论智能系统的几种定义和一些基本特性，接着陈述一下具有共同特性的智能系统的简洁定义。更详细的，我们从智能系统的一般定义开始，讨论智能程度，解释控制在智能系统中的作用，并概括出几种定义。然后讨论智能系统中的自适应和自学习，自主性和必要的高效计算结构，来处理智能系统的复杂性。最后归结出智能（控制）系统的基本特征。我们从智能系统的一般特征开始：一个智能系统应具备在不可测的环境下适当工作的能力，在这环境中一个适当的反应能够增加成功的可能性，从而达到系统最终的目的。为了能让人造智能系统适当的工作
2、，它应能模拟生物的功能和基本的人的智能。一个智能系统能从多个方面来描述。智能程度能从智能的各个方面测得。智能至少要具有感受环境，进而作出决定来进行控制的能力。智能化程度比较高的智能系统具有识别目标和事件，描述世界模型中的知识，思考并计划未来的能力。在智能化程度更高级的形式中，智能具有感知和理解，理智的做出选择，在各种各样的环境下成功的运行以便能在复杂的，不利的环境下生存和发展的能力。通过计算能力的发展和在复杂多变的环境中怎样感知，决定并做出响应的知识的积累，我们可以观察到智能也在更新和发展。智能系统的以上特征是非常普遍的。据上所述，很多系统都可以被认为是智能的。事实上，根据这种定义，恒温器尽管
3、只是低水平的智能，但是也是可以被认为是智能系统。然而，习惯上当一个系统具有更高水平的智能时，我们才称它为智能系统。智能系统存在许多相关的定义，下面我们提到了几种。它们提供可选择但相关的智能系统的特性，这种智能系统着重强调系统的高程度智能。下面的定义强调这样的事实，处理信息的系统集中在人造系统和智能机器上：A机器智能是分析，组织和转换数据成知识的过程，在这里，知识被定义为结构化的信息，这种信息被用来消除无知或相对于智能机器来说某些特殊任务的不确定性。这种定义导致了增加精度而相对减少智能的原则，这种原则表示：应用机器智能到数据库能生成一系列的知识，通过分析形式进行过程建模。其次，智能系统具有自动分
4、配任务和内在自主的执行机构的特性：B许多自适应或自学习控制系统被认为是作为一种控制法则来满足明确的控制目标。这种行为代表着系统试图组织或排列自己动态行为的知识，来满足控制目标。这里知识的组织是组成智能的一个重要特征。如果系统能够自主实现这种组织，那么智能就成为系统的一种性能，而非系统设计者的。这就意味着能内部实现自组织原则的自组织控制器是智能控制系统。下面给出智能系统的过程特性：C智能是系统的一种特性，当集中注意，联合搜索和概括等过程被应用在输入信息，从而产生输出时，这种特性就会出现。你可以很容易的推断出：一旦以上过程被定义，具有智能结构的结果规则生成并作为新的结果。只有一种标准结构将导致在恒
5、温器中固有的一个不成熟的智能或导致成为一个可变结构的变化模型的控制器。下面，介绍一下智能（控制）系统的另外一些特性。根据观察，一个控制系统包括数据结构或对象和处理单元或方法。D由于组件，控制目标，加工模型和控制法则并没有完全被定义，没被定义的原因或是因为在设计时不了解，或是因为它们在不可预测的变化着。所以设计一个智能控制系统以便能自动获得高标准目标。在具有不同智能化程度的系统中呈现出几种基本特性。你可以认为它们是智能系统的特征，或是衡量智能程度的方面。下面我们讨论在智能控制系统中三种非常基本的特性。自适应与自学习，在智能系统中适应变化多端的条件的能力是必需的。尽管自适应不一定要具备自学习能力，
6、但一个系统要适应不可预测的各种变化，学习是最必要的。因此学习能力是高智能系统系统的一种重要特性。自主性和智能，在设置和获取目标过程中自主性是智能控制系统的一个重要特性。当一个系统在一个没有外界干预的不确定的环境中能正常运行时，它就被认为是一个高自主性系统。结构和层次，为了应对复杂情况，一个智能系统必需具备一个合适的功能结构来进行有效的分析和控制决策的估计。这种结构是稀少的并且它应该提供一种机制来建立提取标准或者提供某种形式的部分规则来减少复杂性。一种研究智能机器的熵方法能加强这种有效的计算结构。能够适应的层次（或许是大致的，局部的或是组合的层次），可以作为一种主要的工具来处理复杂性。这里的“层
7、次”术语是指功能性层次，或者是指时空的范围和决议，而且它并不意味着是一种层次硬件。这里面的某些结构可能是硬件的。为了应付多变的环境，自学习能力是必要的，因此这种结构应能适应重要的，不可预料的变化。鉴于以上所述，具有其他任何系统都存在的基本特性的智能系统的一个工作特征是：一个智能系统必需对重要的，不可预料的变化具有很高的适应性，而且自学习也是必要的。在应对变化因素时它必需呈现出高度自主性。它必需能够处理非常复杂的问题，而且这将导致某些稀少的，例如层次这样的功能机构。 The System of Intelligent ControlIntelligence and intelligent sys
8、tems can be characterized in a number of ways and along a number of dimensions. There are certain attributes of intelligence systems, common in many definitions, which are of particular interest to the control community.In the following, several alternative definitions and certain essential characte
9、ristics of intelligent systems are first discussed. A brief working definition of intelligent systems that captures their common characteristics is then presented. In more detail, we start with a rather general definition of intelligent systems, we discuss levels of intelligence, and we explain the
10、role of control in intelligent systems and outline several alternative definitions. We then discuss adaptation and learning, autonomy and the necessity for efficient computational structures in intelligent systems, to deal with complexity. We conclude with a brief working characterization of intelli
11、gent control systems.We start with a general characterization of intelligent systems:An intelligent system has the ability to act appropriately in an uncertain environment, where an appropriate action is that which increases the probability of success, and success is the achievement of behavioral su
12、b goals that support the systems ultimate goal.In order for a man-made intelligent system to act appropriately, it may emulate functions of living creatures and ultimately human mental faculties. An intelligent system can be characterized along a number of dimensions .There are degrees or levels of
13、intelligence that can be measured along the various dimensions of intelligence. At a minimum, intelligence requires the ability to sense the environment, to make decisions and to control action. Higher levels of intelligence may include the ability to recognize objects and events, to represent knowl
14、edge in a world model. and to reason about and plan for the future. In advanced forms, intelligence provides the capacity to perceive and understand, to choose wisely, and to act successfully under a large variety of circumstances so as to survive and prosper in a complex and often hostile environme
15、nt. The above characterization of an intelligent system is rather general. According to this a great number of systems can be considered intelligent. In fact, according to this definition, even a thermostat may be considered to be an intelligent system, although of low level of intelligence. It is c
16、ommon, however, to call a system intelligent when in fact it has a rather high level of intelligence. There exist a number of alternative but related definitions of intelligent systems and in the following we mention several. They provide alternative, but related characterizations of intelligent sys
17、tems with emphasis on systems with high degrees of intelligence The following definition emphasizes the fact that the system in question processes information, and it focuses on man-made systems and intelligent machines: A. Machine intelligence is the process of analyzing, organizing and converting
18、data into knowledge; where machine knowledge is defined to be the structured information acquired and applied to remove ignorance or uncertainty about a specific task pertaining to the intelligent machine. This definition leads to the principle of increasing precision with decreasing intelligence, w
19、hich claims that: applying machine intelligence to a database generates a flow of knowledge, lending an analytic form to facilitate modeling of the process. Next, an intelligent system is characterized by its ability to dynamically assign sub goals and control actions in an internal or autonomous fa
20、shion. B. Many adaptive or learning control systems can be thought of as designing a control law to meet well-defined control objectives. This activity represents the systems attempt to organize or order its knowledge of its own dynamical behavior, so to meet a control objective. The organization of
21、 knowledge can be seen as one important attribute of intelligence. If this organization is done autonomously by the system, then intelligence becomes a property of the system, rather than of the systems designer. This implies that systems which autonomous organize controllers with respect to an inte
22、rnally realized organizational principle are intelligent control systems. The procedural characterization of intelligent systems is given next: C. Intelligence is a property of the system that emerges when the procedures of focusing attention, combinatorial search, and generalization are applied to
23、the input information in order to produce the output. One can easily deduce that once a string of the above procedures is defined, the other levels of resolution of the structure of intelligence are growing as a result of the recursion. Having only one level structure leads to rudimentary intelligen
24、ce that is implicit in the thermostat, or to a variable-structure sliding mode controller. Below, one more alternative characterization of intelligent control systems is included According to this view; a control system consists of data structures or objects (the plant models and the control goals)
25、and processing units or methods (the control laws): D. An intelligent control system is designed so that it can autonomously achieve a high level goal, while its components, control goals, plant models and control laws are not completely defined, either because they were not known at the design time
26、 or because they changed unexpectedly. There are several essential properties present in different degrees in intelligent systems. One can perceive them as intelligent system characteristics or dimensions along which different degrees or levels of intelligence can be measured. Below we discuss three
27、 such characteristics that appear to be rather fundamental in intelligent control systems.Adaptation and Learning. The ability to changing conditions is necessary in an intelligent system. Although adaptation does not necessarily require the ability to learn, for systems to be able to adapt to a wid
28、e variety of unexpected changes learning is essential. So the ability to learn is an important characteristic of intelligent systems.Autonomy and Intelligence. Autonomy in setting and achieving goals is an important characteristic of intelligent control systems. When a system has the ability to act
29、appropriately in an uncertain environment for extended periods of time without external intervention, it is considered to be highly autonomous. There are degrees of autonomy; an adaptive control system can be considered as a system of higher autonomy than a control system with fixed controllers, as
30、it can cope with greater uncertainty than a fixed feedback controller. Although for low autonomy no intelligence (or low intelligence) is necessary, for high degrees of autonomy, intelligence in the system (or high degrees of intelligence) is essential. Structures and Hierarchies. In order to cope w
31、ith complexity, an intelligent system must have an appropriate functional architecture or structure for efficient analysis and evaluation of control strategies. This structure should be sparse and it should provide a mechanism to build levels of abstraction or at least some form of partial ordering
32、so to reduce complexity. An approach to study intelligent machines involving entropy emphasizes such efficient computational structures. Hierarchies that are able to adapt, may serve as primary vehicles for such structures to cope with complexity. The term hierarchies refers to functional hierarchie
33、s, or hierarchies of range and resolution along spatial or temporal dimensions, and it does not necessarily imply hierarchical hardware. Some of these structures may be hardwired in part. To cope with changing circumstances, the ability to learn is essential, so these structures can adapt to signifi
34、cant, unanticipated changes. In view of the above, a working characterization of intelligent systems that captures the essential characteristics present in any such system is: An intelligent system must be highly adaptable to significant unanticipated changes, and so learning is essential. It must exhibit high degree of autonomy in dealing with changes. It must be able to deal with significant complexity, and this leads to certain sparse types of functional architectures such as hierarchies.
