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577 results about "Model control" patented technology

Adaptive nonsingular terminal sliding model control method for permanent magnet synchronous motors on basis of disturbance observers

The invention relates to an adaptive nonsingular terminal sliding model control method for permanent magnet synchronous motors on the basis of disturbance observers. An adaptive nonsingular terminal sliding model controller is introduced into speed loops of vector control systems for the permanent magnet synchronous motors. The adaptive nonsingular terminal sliding model control method is characterized in that an adaptive variable-speed exponential approach law is proposed, first-order norms of state variables are introduced into the approach law, index approach speeds and constant approach speeds are adaptively adjusted according to the distances from the state variables to balance points, accordingly, the approach time can be shortened, and system buffeting can be weakened; the disturbance observers are designed for solving the problems of external disturbance of existing systems and load perturbation, and observation values are fed into designs of the sliding mode controllers. Rotational speeds can be quickly tracked when the systems are disturbed or load fluctuates, accordingly, overshoot and steady-state static difference of the systems can be reduced, and the robustness of the systems can be greatly enhanced.
Owner:JIANGSU UNIV

Upper limb rehabilitation system and method based on myoelectric signal and virtual reality interaction technology

The invention provides an upper limb rehabilitation system and method based on a myoelectric signal and a virtual reality interaction technology. The system comprises a myoelectric signal acquiring and processing part, a virtual reality man-machine interaction part and a muscle function evaluation part, wherein the myoelectric signal acquiring and processing part is composed of a data acquiring module, a signal processing module and a model control module; the virtual reality man-machine interaction part is composed of an upper computer virtual environment module and a force feedback device module; the muscle function evaluation part is composed of a muscular tension quantitative evaluation module and a muscle cooperativeness quantitative evaluation module. According to the rehabilitation method, myoelectric control is used so that a patient subjective intention can be reflected better; a patient keeps initiative in a rehabilitation process by using a virtual reality technology, and the portability, the safety and the effectiveness of rehabilitation trainings are improved. According to the upper limb rehabilitation system and method, an existing clinical rehabilitation evaluation manner can be combined and a muscle function state of the patient is objectively evaluated, so that rehabilitation training standards are provided for the patient and evidences for formulating a therapeutic scheme are provided for rehabilitation doctors.
Owner:YANSHAN UNIV

Hybrid cascade model-based predictive control system

A hybrid cascade Model-Based Predictive control (MBPC) and conventional control system for thermal processing equipment of semiconductor substrates, and more in particular for vertical thermal reactors is described. In one embodiment, the conventional control system is based on a PID controller. In one embodiment, the MBPC algorithm is based on both multiple linear dynamic mathematical models and non-linear static mathematical models, which are derived from the closed-loop modeling control data by using the closed-loop identification method. In order to achieve effective dynamic linear models, the desired temperature control range is divided into several temperature sub-ranges. For each temperature sub-range, and for each heating zone, a corresponding dynamic model is identified. During temperature ramp up/down, the control system is provided with a fuzzy control logic and inference engine that switches the dynamic models automatically according to the actual temperature. When a thermocouple (TC) temperature measurement is in failure, a software soft sensor based on dynamic model computing is used to replace the real TC sampling in its place as a control system input. Consequently, when a TC failure occurs during a process, the process can be completed without the loss of the semiconductor substrate(s) being processed.
Owner:ASM INTERNATIONAL

Combination automatic control method with single-joint manipulator under mixed suspension microgravity environments

The invention provides a combination automatic control method with a single-joint manipulator under mixed suspension microgravity environments. The combination automatic control method comprises the following steps of 1, enabling a combination to be equivalent to an underwater robot, and establishing a kinematics equation and a dynamics equation; 2, approximating the dynamics equation of the combination by a radial basis function neural network, so as to obtain control force and control torque corresponding to the radial basis function neural network; 3, using a sliding mode control method, so as to obtain control force and control torque corresponding to sliding model control; 4, synthesizing the control force and control torque corresponding to the neural network and the control force and control torque obtained by the sliding model control method, and distributing thrust, so as to obtain a general vector which consists of thrust and joint torque of each propeller; approximating the thrust deviation of the corresponding thruster through the radial basis function neural network, so as to obtain the estimation value of the thrust deviation; 5, combining the results obtained in step 2, step 3 and step 4, obtaining the general vector consisting of the thrust and the joint torque of the corresponding propeller, and further obtaining the thrust and the joint torque of the corresponding propeller, so as to realize the automatic control.
Owner:NORTHWESTERN POLYTECHNICAL UNIV

Electricity economizer centralized management method and system of central air-conditioning

The invention relates to a method and a system for centralized management of an electric saver of a central air-conditioner; a water flow pressure difference sensor between a water supply main pipe and a return water main pipe of a central air-conditioner freezing water system, a flow meter for a two-way freezing water return pipe, a water temperature sensor for a back-way freezing water return pipe of a freezing water pump, the water temperature sensor for a freezing water outlet pipe of an air conditioning mainframe, the water temperature sensor for a cooling water outlet pipe of the air conditioning mainframe and the water temperature sensor for a cooling water inlet main pipe of the air conditioning mainframe respectively collect pressure difference, flow speed and water temperature of the corresponding position; collection values are transferred into a fuzzy controller, the fuzzy controller gains dynamic flow and speed parameters through the control of a fuzzy prediction model and an optimal algorithm model, the dynamic flow and speed parameters are transferred into each electric saver, and the speed and the flow of corresponding fans and water pumps are controlled through the frequency change of the electric saver. The invention has the advantages of the high temperature-adjusting precision, the good dynamic performance, the small mechanical loss, the fully-automatic remote monitoring, the closed-loop control of temperature, the soft starting and stopping of a motor and the optimum system electricity-saving rate.
Owner:SUZHOU IRON TECH

Dissolved oxygen model prediction control method based on self-organization radial basis function neural network

ActiveCN103064290AImprove real-time performanceSolve the problem of difficult real-time closed-loop precise controlAdaptive controlNerve networkOxygen
The invention discloses a dissolved oxygen model prediction control method based on a self-organization radial basis function neural network, not only belongs to the field of control, but also belongs to the field of water treatment. Aiming to the characteristics of high nonlinearity, strong coupling, time varying, large lag, serious uncertainty and the like in a sewage disposal process, the control method improves the disposal capability of the neural network by automatically adjusting a neural network structure, builds a prediction model of the sewage disposal process, carries out control through a prediction model control method, and therefore improves a control effect, and enables dissolved oxygen to achieve expected requirements fast and accurately. The method solves the problem that current methods based on a switch control and a proportion integration differentiation (PID) control are poor in adaptive ability. Experimental results show that the method can control dissolved oxygen concentration fast and accurately, has strong adaptive ability, improves the quality and the efficiency of sewage disposal process, reduces sewage disposal cost, and promotes a sewage treatment plant to run efficiently and stably.
Owner:BEIJING UNIV OF TECH
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