An intelligent shearer height adjusting system is a key technology for mining at a man-less working face. A control strategy for a shearer height adjusting system based on a mathematical model of the height adjusting ...An intelligent shearer height adjusting system is a key technology for mining at a man-less working face. A control strategy for a shearer height adjusting system based on a mathematical model of the height adjusting mechanism is proposed. It considers the non-linearity and time variations in the control process and uses Dynamic Fuzzy Neural Networks （D-FNN）. The inverse characteristics of the system are studied. An adaptive on-line learning and error compensation mechanism guarantees sys- tem real-time performance and reliability. Parameters from a German Eickhoff SL500 shearer were used with Maflab/Simulink to simulate a height adjusting control system. Simulation shows that the trace error of a D-FNN controller is smaller than that of a PID controller. Also, the D-FNN control scheme has good generalization and tracking performance, which allow it to satisfy the needs of a shearer height adjusting system.展开更多
This paper deals with fuzzy intelligent position control of electro-hydraulic activated robotic excavator for the control of boom, arm and bucket axes. Intelligent control systems are required to overcome unde- sirabl...This paper deals with fuzzy intelligent position control of electro-hydraulic activated robotic excavator for the control of boom, arm and bucket axes. Intelligent control systems are required to overcome unde- sirable stick-slip motion, limit cycles and oscillations. Models of electro-hydraulic servo controlled front end loader excavators are highly nonlinear. The nonlinear model accounts for fluid flow rate of valve, pump hydraulics, and friction forces. The friction forces are modelled by Coulomb, viscous and Stribeck function. Interval Type-2 Fuzzy Logic Controller （IT2FLC） is used to study the time-domain position responses of axes in the presence of external applied load. It has the ability to control the position of each of the three axes with minimum actuator position errors. Models presented are accurate and study the dynamics of the actuator and load. To improve the transient behaviour of the robotic excavator, we elim- inated iitter of the bucket movement in the presence of nonlinearities.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
The indirect vector controlled IM （induction motor） drive involves decoupling of the stator current into torque and flux producing components. This paper proposes the implementation of a fuzzy logic control scheme a...The indirect vector controlled IM （induction motor） drive involves decoupling of the stator current into torque and flux producing components. This paper proposes the implementation of a fuzzy logic control scheme applied to a two d-q current components model of an induction motor. An intelligent based on fuzzy logic controller is developed with the help of knowledge rule base for efficient control. The performance of fuzzy logic controller is compared with that of the proportional integral controller in terms of the settling time and dynamic response to sudden load changes. The harmonic pattern of the output current is evaluated for both fixed gain proportional integral controller and the fuzzy logic based controller. The performance of the IM drive has been analyzed under steady state and transient conditions. Simulation results of both the controllers are presented for comparison.展开更多
Large space truss structure is widely used in spacecrafts.The vibration of this kind of structure will cause some serious problems.For instance,it will disturb the work of the payloads which are supported on the truss...Large space truss structure is widely used in spacecrafts.The vibration of this kind of structure will cause some serious problems.For instance,it will disturb the work of the payloads which are supported on the truss,even worse,it will deactivate the spacecrafts.Therefore,it is highly in need of executing vibration control for large space truss structure.Large space intelligent truss system(LSITS) is not a normal truss structure but a complex truss system consisting of common rods and active rods,and there are at least one actuator and one sensor in each active rod.One of the key points in the vibration control for LSITS is the location assignment of actuators and sensors.The positions of actuators and sensors will directly determine the properties of the control system,such as stability,controllability,observability,etc.In this paper,placement optimization of actuators and sensors(POAS) and decentralized adaptive fuzzy control methods are presented to solve the vibration control problem.The electro-mechanical coupled equations of the active rod are established,and the optimization criterion which does not depend upon control methods is proposed.The optimal positions of actuators and sensors in LSITS are obtained by using genetic algorithm(GA).Furthermore,the decentralized adaptive fuzzy vibration controller is designed to control LSITS.The LSITS dynamic equations with considering those remaining modes are derived.The adaptive fuzzy control scheme is improved via sliding control method.One T-typed truss structure is taken as an example and a demonstration experiment is carried out.The experimental results show that the GA is reliable and valid for placement optimization of actuators and sensors,and the adaptive fuzzy controller can effectively suppress the vibration of LSITS without control spillovers and observation spillovers.展开更多
基金support for this work, provided by the National High Technology Research and Development Program of China (No2008AA062202)China University of Mining & Technology Scaling Program
文摘An intelligent shearer height adjusting system is a key technology for mining at a man-less working face. A control strategy for a shearer height adjusting system based on a mathematical model of the height adjusting mechanism is proposed. It considers the non-linearity and time variations in the control process and uses Dynamic Fuzzy Neural Networks （D-FNN）. The inverse characteristics of the system are studied. An adaptive on-line learning and error compensation mechanism guarantees sys- tem real-time performance and reliability. Parameters from a German Eickhoff SL500 shearer were used with Maflab/Simulink to simulate a height adjusting control system. Simulation shows that the trace error of a D-FNN controller is smaller than that of a PID controller. Also, the D-FNN control scheme has good generalization and tracking performance, which allow it to satisfy the needs of a shearer height adjusting system.
文摘This paper deals with fuzzy intelligent position control of electro-hydraulic activated robotic excavator for the control of boom, arm and bucket axes. Intelligent control systems are required to overcome unde- sirable stick-slip motion, limit cycles and oscillations. Models of electro-hydraulic servo controlled front end loader excavators are highly nonlinear. The nonlinear model accounts for fluid flow rate of valve, pump hydraulics, and friction forces. The friction forces are modelled by Coulomb, viscous and Stribeck function. Interval Type-2 Fuzzy Logic Controller （IT2FLC） is used to study the time-domain position responses of axes in the presence of external applied load. It has the ability to control the position of each of the three axes with minimum actuator position errors. Models presented are accurate and study the dynamics of the actuator and load. To improve the transient behaviour of the robotic excavator, we elim- inated iitter of the bucket movement in the presence of nonlinearities.
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.
文摘The indirect vector controlled IM （induction motor） drive involves decoupling of the stator current into torque and flux producing components. This paper proposes the implementation of a fuzzy logic control scheme applied to a two d-q current components model of an induction motor. An intelligent based on fuzzy logic controller is developed with the help of knowledge rule base for efficient control. The performance of fuzzy logic controller is compared with that of the proportional integral controller in terms of the settling time and dynamic response to sudden load changes. The harmonic pattern of the output current is evaluated for both fixed gain proportional integral controller and the fuzzy logic based controller. The performance of the IM drive has been analyzed under steady state and transient conditions. Simulation results of both the controllers are presented for comparison.
基金supported by the National Natural Science Foundation of China (Grant No. 10472006)
文摘Large space truss structure is widely used in spacecrafts.The vibration of this kind of structure will cause some serious problems.For instance,it will disturb the work of the payloads which are supported on the truss,even worse,it will deactivate the spacecrafts.Therefore,it is highly in need of executing vibration control for large space truss structure.Large space intelligent truss system(LSITS) is not a normal truss structure but a complex truss system consisting of common rods and active rods,and there are at least one actuator and one sensor in each active rod.One of the key points in the vibration control for LSITS is the location assignment of actuators and sensors.The positions of actuators and sensors will directly determine the properties of the control system,such as stability,controllability,observability,etc.In this paper,placement optimization of actuators and sensors(POAS) and decentralized adaptive fuzzy control methods are presented to solve the vibration control problem.The electro-mechanical coupled equations of the active rod are established,and the optimization criterion which does not depend upon control methods is proposed.The optimal positions of actuators and sensors in LSITS are obtained by using genetic algorithm(GA).Furthermore,the decentralized adaptive fuzzy vibration controller is designed to control LSITS.The LSITS dynamic equations with considering those remaining modes are derived.The adaptive fuzzy control scheme is improved via sliding control method.One T-typed truss structure is taken as an example and a demonstration experiment is carried out.The experimental results show that the GA is reliable and valid for placement optimization of actuators and sensors,and the adaptive fuzzy controller can effectively suppress the vibration of LSITS without control spillovers and observation spillovers.
