Hybrid mecihanism is a new type of planar controllable mechanism. Position control acouracy of system determines the output aconracy of the mechanism. In order to achieve the desired high acowacy, nonlinear factors as...Hybrid mecihanism is a new type of planar controllable mechanism. Position control acouracy of system determines the output aconracy of the mechanism. In order to achieve the desired high acowacy, nonlinear factors as friction nmst be accurately compensated in the real-time servo control algoritinn. In this paper, the model of a hybrid five-bar mechanism is introduced. In terms of the characteristics of the hybrid mechanism, a hybrid intelligent control algorithm based on proportional-integral-derivative （PID） control and cerebellar model articulation control techniques was presented and used to perform control of hybrid five-bar mechanism for the lust time. The sinmulation results show that the hybrid control method can improve the control effect remarkably, compared with the traditional PID control strategy.展开更多
The purpose of this paper is to design a neuron adaptive PID controller based on the theory of intelligent control of the extens- ive research on the characteristics of neuronss, neurons and PID controller. Artificial...The purpose of this paper is to design a neuron adaptive PID controller based on the theory of intelligent control of the extens- ive research on the characteristics of neuronss, neurons and PID controller. Artificial neurons have the adaptive, parallel processing, selflearning learning, and mare fault-tolerant characteristics. When the artificial neurons are used to control the process, the syste^n will enabled to en-sure that the accused has strong anti-interference capability and ro. bustness.展开更多
The development of the assistive abilities regarding the decision-making process o fan Intelligent Control System （ICS） like a fuzzy expert system implies the development of its functionality and its ability of spec...The development of the assistive abilities regarding the decision-making process o fan Intelligent Control System （ICS） like a fuzzy expert system implies the development of its functionality and its ability of specification. Fuzzy expert systems can model fuzzy controllers, i.e., the knowledge representation and the abilities of making decisions corresponding to fuzzy expert systems are much more complicated that in the case of standard fuzzy controllers. The expert system acts also as a supervisor, creating meta-level reasoning on a set of fuzzy controllers, in order to choose the best one for the management of the process. Knowledge Management Systems （KMSs） is a new development paradigm of Intelligent Systems which has resulted from a synergy between fuzzy sets, artificial neural networks, evolutionary computation, machine learning, etc., broadening computer science, physics, economics, engineering, mathematics. This paper presents, after a synergic new paradigm of intelligent systems, as a practical case study the fuzzy and temporal properties of knowledge formalism embedded in an ICS. We are not dealing high with level reasoning methods, because we think that real-time problems can only be solved by rather low-level reasoning. Solving the match-time predictability problem would allow us to build much more powerful reasoning techniques.展开更多
文摘Hybrid mecihanism is a new type of planar controllable mechanism. Position control acouracy of system determines the output aconracy of the mechanism. In order to achieve the desired high acowacy, nonlinear factors as friction nmst be accurately compensated in the real-time servo control algoritinn. In this paper, the model of a hybrid five-bar mechanism is introduced. In terms of the characteristics of the hybrid mechanism, a hybrid intelligent control algorithm based on proportional-integral-derivative （PID） control and cerebellar model articulation control techniques was presented and used to perform control of hybrid five-bar mechanism for the lust time. The sinmulation results show that the hybrid control method can improve the control effect remarkably, compared with the traditional PID control strategy.
文摘The purpose of this paper is to design a neuron adaptive PID controller based on the theory of intelligent control of the extens- ive research on the characteristics of neuronss, neurons and PID controller. Artificial neurons have the adaptive, parallel processing, selflearning learning, and mare fault-tolerant characteristics. When the artificial neurons are used to control the process, the syste^n will enabled to en-sure that the accused has strong anti-interference capability and ro. bustness.
文摘The development of the assistive abilities regarding the decision-making process o fan Intelligent Control System （ICS） like a fuzzy expert system implies the development of its functionality and its ability of specification. Fuzzy expert systems can model fuzzy controllers, i.e., the knowledge representation and the abilities of making decisions corresponding to fuzzy expert systems are much more complicated that in the case of standard fuzzy controllers. The expert system acts also as a supervisor, creating meta-level reasoning on a set of fuzzy controllers, in order to choose the best one for the management of the process. Knowledge Management Systems （KMSs） is a new development paradigm of Intelligent Systems which has resulted from a synergy between fuzzy sets, artificial neural networks, evolutionary computation, machine learning, etc., broadening computer science, physics, economics, engineering, mathematics. This paper presents, after a synergic new paradigm of intelligent systems, as a practical case study the fuzzy and temporal properties of knowledge formalism embedded in an ICS. We are not dealing high with level reasoning methods, because we think that real-time problems can only be solved by rather low-level reasoning. Solving the match-time predictability problem would allow us to build much more powerful reasoning techniques.
