design the FMRlC so that it will learn and remember different fuzzy controllers for all the different plant operating conditions and reference inputs; hence, the fuzzy controller needs information about these Often, however, we cannot measure the operating condition of the plant, so the FmrlC does not know exactly what operating condition it is learning the controller for. Moreover, it then does not know exactly when it has returned to an operating condition. Clearly, then, if the fuzzy controller has better information about the plant's operating conditions the Fmrlc will be able to learn and apply better control actions. If it does not have good information, it will continually adapt, but it will not properly remember For instance, for some plants e(kn) and c(kn) may only grossly characterize the operating conditions of the plant. In this situation the FmrLC is not able to learn different controllers for different operating conditions; it will use its limited information about the operating condition and continually adapt to search for the best controller. It degrades from a learning system to an adaptive system that will not properly remember the control actions(this is not to imply, however that there will automatically be a corresponding degradation in performance) Generally, we think of the inputs to the fuzzy controller as specifying what conditions we need to learn different controllers for. This should be one guideline used for the choice of the fuzzy controller inputs for practical applications A competing objective is, however, to keep the number of fuzzy controller inputs low due to concerns about computational complexity. In fact, to help with computational complexity, we will sometimes use multiple fuzzy controllers with fewer inputs to each of them rather than one fuzzy controller with many inputs; then we may, for instance, sum the outputs of the individual controllers 3.2.2 The Reference model Next, you must decide what to choose for the reference model that quantifies the desired performance. Basically, you want to specify a desirable performance, but also a reasonable one. If you ask for too much, the controller will not be able to deliver it; certain characteristics of real- world plants place practical constraints on what performance can be achieved. It is not always easy to pick a good reference model since it is sometimes hard to know what level of performance we can expect, or because we have no idea how to characterize the performance for some of the plant output variables(see the flexible robot application in Section 3.3 where it is difficult to know a priori how the acceleration profiles of the links should behave) In general, the reference model may be discrete or continuous time, linear or nonlinear, time-invariant or time-varying, and so on. For example, suppose that we would like to have the response track the continuous time model G(s)= 1+s Suppose that for your discrete-time implementation you use T=0. 1 sec. Using a bilinear(Tustin) transformation PDF文件使用" pdffactory Pro"试用版本创建ww. fineprint,com,cndesign the FMRLC so that it will learn and remember different fuzzy controllers for all the different plant operating conditions and reference inputs; hence, the fuzzy controller needs information about these. Often, however, we cannot measure the operating condition of the plant, so the FMRLC does not know exactly what operating condition it is learning the controller for. Moreover, it then does not know exactly when it has returned to an operating condition. Clearly, then, if the fuzzy controller has better information about the plant's operating conditions, the FMRLC will be able to learn and apply better control actions. If it does not have good information, it will continually adapt, but it will not properly remember. For instance, for some plants e(kT) and c(kT) may only grossly characterize the operating conditions of the plant. In this situation the FMRLC is not able to learn different controllers for different operating conditions; it will use its limited information about the operating condition and continually adapt to search for the best controller. It degrades from a learning system to an adaptive system that will not properly remember the control actions (this is not to imply, however, that there will automatically be a corresponding degradation in performance). Generally, we think of the inputs to the fuzzy controller as specifying what conditions we need to learn different controllers for. This should be one guideline used for the choice of the fuzzy controller inputs for practical applications. A competing objective is, however, to keep the number of fuzzy controller inputs low due to concerns about computational complexity. In fact, to help with computational complexity, we will sometimes use multiple fuzzy controllers with fewer inputs to each of them rather than one fuzzy controller with many inputs; then we may, for instance, sum the outputs of the individual controllers. 3.2.2 The Reference Model Next, you must decide what to choose for the reference model that quantifies the desired performance. Basically, you want to specify a desirable performance, but also a reasonable one. If you ask for too much, the controller will not be able to deliver it; certain characteristics of real- world plants place practical constraints on what performance can be achieved. It is not always easy to pick a good reference model since it is sometimes hard to know what level of performance we can expect, or because we have no idea how to characterize the performance for some of the plant output variables (see the flexible robot application in Section 3.3 where it is difficult to know a priori how the acceleration profiles of the links should behave). In general, the reference model may be discrete or continuous time, linear or nonlinear, time-invariant or time-varying, and so on. For example, suppose that we would like to have the response track the continuous time model ( ) 1 1 G s s = + . Suppose that for your discrete-time implementation you use T = 0. 1 sec. Using a bilinear (Tustin) transformation PDF 文件使用 "pdfFactory Pro" 试用版本创建 www.fineprint.com.cn