(which represent random events that can affect the problem domain and hence the measured variable yk), and goals gk (what we would like to achieve in the problem domain). There are closed-loop specifications that quantify performance specifications and stability requirements Plan generation Planner Control Set of pla plan outputs 目 e Istep Play decisions execution domain F Fir Figure 4.8 Closed-loop planning system It is the task of the planner in Figure 4.8 to monitor the measured outputs and goals and generate control actions that will counteract the effects of the disturbances and result in the goals and the closed-loop specifications being achieved To do this, the planner performs"plan generation, "where it projects into the future(usually a finite number of steps, and often using a model of the problem domain) and tries to determine a set of candidate plans. Next, this set of plans ed to one plan that is the best one to apply at the current time(where "best"can be determined based on, e.g consumption of resources). The plan is then executed, and during execution the performance resulting from the plan is monitored and evaluated. Often, due to disturbances, plans will fail, and hence the planner must generate a new set of candidate plans, select one, then execute that one While not pictured in Figure 4.8, some planning systems use"situation assessment" to try to estimate the state of the problem domain(this can be useful in execution monitoring and plan generation); others perform"world modeling, where a model of the problem domain is developed in an on-line fashion(similarly to on-line system identification), and planner design"uses information from the world modeler to tune the planner(so that it makes the right plans for the current problem domain). The reader will, perhaps, think of such a planning system as a general adaptive controller The role of planning systems in fuzzy control could be any one of the following: (1)the use of a fuzzy planner as a controller, (2) the use of fuzzy "situation assessment"in determining control actions, (3)the use of fuzzy "world modeling"to generate a model of the plant that is useful in making control decisions, (4)the use of a fuzzy adaptive planning system(e.g, a fuzzified version of the adaptive planner in[ 162), or(5) the use of a planning system in a supervisory control role 4.6 Intelligent and Autonomous control Autonomous systems have the capability to independently perform complex tasks with a high degree of success Consumer and governmental demands for such systems are frequently forcing engineers to push many functions performed by humans into machines. For instance, in the emerging area of intelligent vehicle and highway systems(IVHS), engineers are designing vehicles and highways that can fully automate vehicle route selection, steering braking, and throttle control to reduce congestion and improve safety. In avionic systems a"pilot's associate"computer program has been designed to emulate the functions of mission and tactical planning that in the past may have been performed by the copilot. In manufacturing systems, efficiency optimization and flow control are being automated, and robots are replacing humans in performing relatively complex tasks PDF文件使用" pdffactory Pro"试用版本创建ww. fineprint,com,cn(which represent random events that can affect the problem domain and hence the measured variable yk), and goals gk (what we would like to achieve in the problem domain). There are closed-loop specifications that quantify performance specifications and stability requirements. k d k y k u k g Figure 4.8 Closed-loop planning system It is the task of the planner in Figure 4.8 to monitor the measured outputs and goals and generate control actions that will counteract the effects of the disturbances and result in the goals and the closed-loop specifications being achieved. To do this, the planner performs "plan generation," where it projects into the future (usually a finite number of steps, and often using a model of the problem domain) and tries to determine a set of candidate plans. Next, this set of plans is pruned to one plan that is the best one to apply at the current time (where "best" can be determined based on, e.g., consumption of resources). The plan is then executed, and during execution the performance resulting from the plan is monitored and evaluated. Often, due to disturbances, plans will fail, and hence the planner must generate a new set of candidate plans, select one, then execute that one. While not pictured in Figure 4.8, some planning systems use "situation assessment" to try to estimate the state of the problem domain (this can be useful in execution monitoring and plan generation); others perform "world modeling," where a model of the problem domain is developed in an on-line fashion (similarly to on-line system identification), and "planner design" uses information from the world modeler to tune the planner (so that it makes the right plans for the current problem domain). The reader will, perhaps, think of such a planning system as a general adaptive controller. The role of planning systems in fuzzy control could be any one of the following: (1) the use of a fuzzy planner as a controller, (2) the use of fuzzy "situation assessment" in determining control actions, (3) the use of fuzzy "world modeling" to generate a model of the plant that is useful in making control decisions, (4) the use of a fuzzy adaptive planning system (e.g., a fuzzified version of the adaptive planner in [ 162]), or (5) the use of a planning system in a supervisory control role. 4.6 Intelligent and Autonomous Control Autonomous systems have the capability to independently perform complex tasks with a high degree of success. Consumer and governmental demands for such systems are frequently forcing engineers to push many functions normally performed by humans into machines. For instance, in the emerging area of intelligent vehicle and highway systems (IVHS), engineers are designing vehicles and highways that can fully automate vehicle route selection, steering, braking, and throttle control to reduce congestion and improve safety. In avionic systems a "pilot's associate" computer program has been designed to emulate the functions of mission and tactical planning that in the past may have been performed by the copilot. In manufacturing systems, efficiency optimization and flow control are being automated, and robots are replacing humans in performing relatively complex tasks. PDF 文件使用 "pdfFactory Pro" 试用版本创建 www.fineprint.com.cn