143 results about "Fuzzy logic control" patented technology

The present invention is a method and system for adaptively detecting a patient trigger threshold. The system and method uses fuzzy-logic control algorithm to detect an appropriate trigger threshold by monitoring the number of patient triggers within a predetermined time frame. The system and method also detects an appropriated trigger threshold by monitoring the complete absence of false triggers over a predetermined time frame, increases in average flow, increases in pressure differential, and pressure drop, in order to lower the trigger threshold. The method and system of the present invention is selectable to the user, and adaptively changes the inspiratory trigger threshold.

A level control algorithm for an HVAC refrigeration system is provided. The control algorithm utilizes a fuzzy logic methodology to automatically adjust a flow of refrigerant in the system to maintain a desired liquid level in the condenser. The fuzzy logic methodology incorporates a plurality of fuzzy logic control algorithms each having different membership functions and other control parameters that can provide different degrees of level control in the condenser. A particular fuzzy logic control algorithm is selected based on the amount a measured liquid level in the condenser deviates from the desired liquid level in the condenser.

Fuzzy logic is utilized to control an RF amplifier and associated tuner for continuous self-optimization and automatic load matching to at least double the battery life of a battery-powered transmitter.

The invention provides a novel control method combining fuzzy logic control with gain auto-tuning sliding mode control. A control error signal e(t) from the detection mechanism and an error change signal ce(t) are combined together as a sliding variable s(t)=ce(t)+λe(t) and used as the fuzzy input control variable. Using the control method, 2D fuzzy control rule is simplified into 1D fuzzy control rule through the sliding variable definition for enhancing the efficiency of computation and saving computation resources. Accordingly, both the quick transient response and steady state precision positioning can be achieved. The present method can overcome the disadvantages of current controller, which can not reach the desired transient and steady state responses simultaneously.

The invention discloses an efficient message authentication method for a vehicular ad hoc network based on edge computing, which comprises the steps of system initialization of participating entitiesof the Internet of vehicles, wherein the step comprises two processes such as parameter generation and vehicle pseudonym and signature generation; and (2) message authentication of an RSU (Roadside Unit) and a vehicle, wherein the step comprises four processes such that the RSU elects an edge computing vehicle (ECV), the ECV executes a task, the RSU checks an authentication result of the ECV and vehicle message authentication is performed. The signing portion of the invention adopts an elliptic curve cryptography based operation, thereby enabling the computation and transmission overhead to below; further the ECV is elected according to a fuzzy logic control theory to achieve local optimal election; the ECV is set to help the RSU to achieve quick and accurate message signature authentication; and the RSU reduces the redundant authentication of the whole system to the maximum extent through broadcasting the authentication result, and the operating efficiency of the whole vehicular ad hoc network is improved.

The invention discloses a system and a method for controlling the membrane-base reflecting mirror surface shape. The system comprises a standard reflecting mirror surface shape designing module, an emulational analyzing module, a reflecting mirror surface shape monitoring module, a fuzzy logic controlling module, a reflecting mirror surface shape controlling actuator and a reflecting mirror surface shape feeding back module. The aperture and the F number of a membrane-base reflecting mirror needed for design are used as the parameters and the Zernike polynomial coefficient form is adopted to determine the standard reflecting mirror surface shape parameter; the real-time membrane-base reflecting mirror surface shape is detected; the errors of the arc rises for the central cross sections of both a membrane-base reflecting mirror and a standard reflecting mirror are used as control variables, and the control variables are processed by a fuzzy logic controller; the voltage needed for forming the membrane-base reflecting mirror is outputted; and the membrane-base reflecting mirror surface shape is changed with the electrostatic method. The invention adopts the emulational reflecting mirror surface shape control analysis based on the finite-element analysis method to predict the reflecting mirror surface shape control effect, optimize the fuzzy control rule base and reduce the difficulty of designing the fuzzy logic controller. The method provides the technological base for the effective membrane-base reflecting mirror surface shape.

In methods and apparatus for controlling multi-layer communications networks, data characterizing activity and state of the network and external demands made on the network by customer requests at at least two Layers is collected. The collected data are processed in accordance with a dynamic policy to determine that a reconfiguration of at least one Layer of the at least two Layers is favourable, and to determine a favoured reconfiguration of the at least one Layer. The collected data are processed in accordance with a dynamic policy to determine a favoured selection of customer demands on the network to be accepted. Implementation of the favoured reconfiguration and favoured admission is initiated. The resulting network behaviour is observed and the dynamic policy is adjusted to increase its ability to find favourable reconfiguration and call admission actions. The Layers may, for example, be a Layer 3 packet data service, such as Internet Protocol service, and layers below Layer 3 including one or more Layer 2 path-oriented service and one or more Layer 1 transport services. The reconfiguration of all Layers depends on information received from all Layers. Rapid reconfiguration of the Layer 2 and Layer 1 equipment and rapid decisions on the acceptance or rejection of customer demands based on data collected from all Layers reduces over-provisioning of the network needed to meet difficult-to-predict traffic patterns and loss of revenue due to inability to serve traffic with the current network configuration. A Fuzzy Logic control algorithm with policy tuning by temporal difference Reinforcement algorithms is described.

Provided is a robot optimal itineration control method satisfying complex requirements. The method comprises six steps of establishing a weighting switching system, establishing a task chart of a Buchi automata, establishing task feasible network topology of a Product automata, searching an optimal path, performing fuzzy logic control, and feeding back pose information. The method comprises: firstly, based on linear temporal logic, combining with robot operation environment information, programming the optimal path satisfying task requirements; and then, by using a fuzzy control strategy, combining with present position coordinate and orientation information of the robot fed back in real time, according to angular deviation [alpha] and distance deviation d between a present mobile robot and a target point, giving controlled quantities of speed vl and vr of a left wheel and a right wheel of the robot, so as to realize optimal path tracking control. The method can plan the optimal path which conforms to robot operation environment and satisfies complex itineration task requirements, and the method can effectively control the robot to realize optimal path tracking, so as to complete appointed tasks.

A level control algorithm for an HVAC refrigeration system is provided. The control algorithm utilizes a fuzzy logic methodology to automatically adjust a flow of refrigerant in the system to maintain a desired liquid level in the condenser. The fuzzy logic methodology incorporates a plurality of fuzzy logic control algorithms each having different membership functions and other control parameters that can provide different degrees of level control in the condenser. A particular fuzzy logic control algorithm is selected based on the amount a measured liquid level in the condenser deviates from the desired liquid level in the condenser.

An adaptive front-lighting system is provided for a vehicle, such as a passenger car, truck, or tractor trailer. A plurality of LED light sources on the vehicle have a projection pattern for exterior illumination to supplement a main beam from a main light source. A power supply drives the LED light sources according to a driving signal having a magnitude between a minimum driving signal and a maximum driving signal, wherein the LED light sources sequentially illuminate in response to the magnitude of the driving signal. A speed sensor characterizes an instantaneous vehicle speed. A turn sensor characterizes an instantaneous turning radius. A fuzzy controller generates the driving signal in response to the instantaneous vehicle speed and the instantaneous turning radius based on a fuzzy model. The fuzzy model is characterized by a plurality of empirically-derived fuzzy rules that define discontinuous values and by a plurality of modified consequents that produce a substantially continuous output.

The invention provides a novel control method combining fuzzy logic control with gain auto-tuning sliding mode control. A control error signal e(t) from the detection mechanism and an error change signal ce(t) are combined together as a sliding variable s(t)=ce(t)+λe(t) and used as the fuzzy input control variable. Using the control method, 2D fuzzy control rule is simplified into 1D fuzzy control rule through the sliding variable definition for enhancing the efficiency of computation and saving computation resources. Accordingly, both the quick transient response and steady state precision positioning can be achieved. The present method can overcome the disadvantages of current controller, which can not reach the desired transient and steady state responses simultaneously.