PID控制器及智能控制英文文献(3)

Fig. 16.2 The simulation chart

Derivative Control

Derivative control takes into consideration that if you change the output, then it takes time for

that change to be reflected in the input (PV) . For example, let’

s take heating of the oven.

Fig. 16.3 The simulation chart

If we start turning up the gas flow, it will take time for the heat to be produced, the heat to flow around the oven, and for the temperature sensor to detect the increased heat. Derivative control sort of “holds back” the PID controller because some increase in temperature will occur without needing to increase the output further. Setting the derivative constant correctly allows you to become more aggressive with the P & I constants.

Intelligence and intelligent systems can be characterized in a number of ways and along a number of dimensions. There are certain attributes of intelligent systems, common in many definitions, which are of particular interest to the control community.

In the following, several alternative definitions and certain essential characteristics of ntelligent systems are first discussed. A brief working definition of intelligent systems that aptures their common characteristics is then presented. In more detail, we start with a rather eneral definition of intelligent systems, we discuss levels of intelligence, and we explain the role f control in intelligent systems and outline several alternative definitions. [1] We then discuss daptation and learning, autonomy and the necessity for efficient computational structures in ntelligent systems, to deal with complexity. We conclude with a brief working characterization f intelligent (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 n appropriate action is that which increases the probability of success, and success is the chievement of behavioral subgoals that support the system’s ultimate goal. [2]

In order for a man-made intelligent system to act appropriately, it may emulate functions of iving creatures and ultimately human mental faculties. An intelligent system can be haracterized along a number of dimensions. There are degrees or levels of intelligence that can e measured along the various dimensions of intelligence. At a minimum, intelligence requires he ability to sense the environment, to make decisions and to control action. Higher levels of ntelligence may include the ability to recognize objects and events, to represent knowledge in a orld model, and to reason about and plan for the future. In advanced forms, intelligence rovides the capacity to

perceive and understand, to choose wisely, and to act successfully under large variety of circumstances so as to survive and prosper in a complex and often hostile nvironment. [3] Intelligence can be observed to grow and evolve, both through growth in omputational power and through accumulation of knowledge of how to sense, decide and act in complex and changing world.

The above characterization of an intelligent system is rather general. According to this, a reat 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 common, 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 systems 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 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, which 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 subgoals and control actions in an internal or autonomous fashion:

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 system’s attempt to organize or order its “knowledge” of its own dynamical behavior, so to meet a control objective. The organization of 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 system’s designer. This implies that systems which autonomously (self) -organize controllers with respect to an internally realized organizational principle are intelligent control systems. [5]

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