37results about How to "Convenient online control" patented technology

The invention discloses a bioelectricity synthesis system and a method for synthesizing acetic acid and/or ethyl alcohol through the same. The bioelectricity synthesis system comprises a reactor, an online pH control system, an air supply system and a power source. The reactor is a three-chamber reactor and comprises an air chamber, a negative electrode chamber and a positive electrode chamber, wherein the air chamber is connected with the air supply system; the negative electrode chamber is externally connected with the online pH control system, the negative electrode chamber and the air chamber are partitioned by an air negative electrode, and the negative electrode chamber is further internally provided with a reference electrode; the positive electrode chamber is internally provided with a positive electrode, the positive electrode chamber and the negative electrode chamber are partitioned by a cation exchange membrane, and the positive electrode, the air negative electrode and the reference electrode are externally connected with the power source through wires. Positive electrode electrolyte is added into the positive electrode chamber, a bioelectricity synthetic nutrient solution obtained after sterile and anaerobic treatment is added into the negative electrode chamber, and electrosynthesis bacteria are inoculated into the negative electrode chamber; carbon dioxide is sent into the air chamber through metering of the air supply system, and carbon dioxide penetrates through the air negative electrode and is converted into acetic acid and/or ethyl alcohol in the negative electrode chamber.

The invention relates to a switch reluctance machine (SRM) torque pulse control method and system of a torque-current neutral network model. According to the method, a torque-current conversion relation is obtained by an inductance model of an SRM, each phase control current is obtained by a current allocation function, so that torque pulse is prevented. According to a non-linear characteristic relation between the SRM torque and the current, a function of describing basic change rule of an SRM current is used as an implication layer simulation function, a torque-current neutral network modelof describing the strong non-linear characteristic of the SRM is designed, the total reference current corresponding to torque is calculated by self-learning of the torque-current neutral network model, a reference current corresponding to each phase is obtained by the current allocation function, and the SRM is controlled. A program storage device of a system microprocessor designed by the methodis provided with each program module for executing the method, each sensor signal on the SRM is connected to the microprocessor, and the SRM is connected and controlled by a power converter. By the method, effective control on torque pulse of the SRM is achieved.

The invention relates to a torque control method and system of a current nonlinear compensated switched reluctance motor. According to the method, a basic control current is calculated by an electromagnetic torque mathematical expression of a linear induction model of the switched reluctance motor, a set torque is allocated to allocation torques of a switch-on phase and a switch-off phase by an optimal torque-sharing function, and the basic control current of each phase is acquired through conversion; and a nonlinear current compensation value of each phase is figured out and is superposed to the basic control current of each phase to serve as the control current of each phase, and a current hysteresis loop controller is controlled according to the difference between the control current and actually-measured current. A microprocessor of the system is connected with three current sensors and a rotor position angle and torque sensor on the switched reluctance motor, a program storage is provided with a data acquisition module and each calculation module of the method, a control signal is obtained by calculation according to each actually-measured signal, and a pulse width modulator controls three-phase input current of the switched reluctance motor. By the method and the system, the torque ripple of the switched reluctance motor is effectively suppressed, an embedment system can be constructed, and on-line control is facilitated.

The invention discloses a method for realizing reheat steam temperature multivariable coordinate predictive control through performance indexes. According to the method, the reheat steam temperature system of a thermal power generating unit is regarded as a 2*1 multivariable system, a multivariable predictive controller is designed on the basis of novel performance indexes, and the opening degree of a reheat steam temperature reducing water-spray valve and the opening degree of a smoke baffle are controlled simultaneously. In the performance indexes, on one hand, an algorithm is simplified and rapid control is realized on the basis of requirements on a single-step prediction error and a prediction error change rate, and the control performance of a control system can also be effectively adjusted by adjusting a predictive length and a predictive error change rate weight; on the other hand, dynamic limit on the opening degree of the temperature reducing water-spray valve is added in the indexes, the part of the performance parameters is self-adaptive to changes during a control process, and the amount of temperature reducing water sprayed in reheat steam can be reduced while a reheat steam control quality is improved, thus effectively increasing the cycle efficiency of the unit.

The invention provides a dynamic neural network adaptive inverse SRM torque control method and system. An actual total flux linkage at a previous moment of a system, a current reference torque and a previous-moment reference flux linkage output by an RBF neural network serve as input signals of the RBF neural network, the reference flux linkage is output, and a dynamic RBF neural network, namely,a torque-flux linkage model is formed; and a torque deviation is subjected to PD control to obtain a control quantity, the control quantity is pre-processed to serve as a learning deviation of RBF neural network adaptive inverse control, and the control quantity is subjected to filtering processing to serve as part of a total reference flux linkage, thereby compensating an output of the flux linkage model. The total reference flux linkage and the actual total flux linkage are subjected to subtraction to obtain a flux linkage deviation, and through flux linkage deviation distribution, the fluxlinkage deviation hysteresis control of each phase is accessed, so that the torque pulsation of an SRM is effectively inhibited. The rapid control requirement of the motor is met; a feedback error learning method accelerates the neural network modeling and improves the modeling precision; and the influence of the torque pulsation is reduced.

The invention discloses a polymerization process condition optimization method taking polyolefin microscopic quality as a target, belonging to the field of manufacture of chemical products. The polymerization process condition optimization method is characterized by building a process mathematic model based on reaction mechanism for an olefin polymerization process, and solving an optimal polymerization process condition which meets requirements on quality of specific products by taking average molecular weight or molecular weight distribution as an index of the microscopic quality of the polyolefin. The polymerization process condition optimization method can be used for calculating to obtain the optimal process operation condition under the condition with the given average molecular weight and molecular weight distribution of the polymers; the method can be applied to the design of structures of polymer products and can be used for shortening time for developing a novel type polymer, so that energy conservation and emission reduction are implemented; the economic benefit is increased; the polymerization process condition optimization method is simple and clear in principle and easy to understand and implement; the implementation of computer programming is facilitated; the on-line control of the quality of the polymer products is facilitated.

The invention provides a flexible needle plane puncture controlling device based on a brain emotion learning intelligent control algorithm and a method thereof. The flexible needle motion control is achieved using computer programs and the device. The device includes a feed motor for controlling the feed speed of a flexible needle and a rotary motor for controlling the rotation of a flexible needle tip, a sensor for acquiring the position and heading angle information of the flexible needle, and a computer for flexible needle motion control. The method of the invention is characterized in thata pre-planned path is subjected to discretization to obtain a target point set, and then the current target position of the flexible needle is compared to the next target point to obtain the positionerror, and the voltage of the feed motor is obtained by a designed brain emotion learning intelligent controller; and a rotating electric machine is controlled by the actual heading angle error. Thedevice simplifies a flexible needle model, has fewer control parameters and less calculation amount, realizes online real-time control and precise control, and can finally reach the target accurately.

The invention discloses a torque ripple suppression control system and method for a switched reluctance motor based on flux linkage. The system employs a neural network torque estimation model to estimate the torque, employs a dynamic RBF neural network torque-flux linkage model to achieve the conversion from a phase reference torque to a flux linkage, carries out the real-time feed-forward compensation of the flux linkage based on the estimated torque information, so that accurate flux linkage information is obtained, flux linkage control of the SRM is realized, torque pulsation is suppressed, and the method is small in calculation amount; the constructed neural network torque estimation model has an excitation function capable of reflecting an SRM torque change rule, and preprocessing the input of the neural network to realize estimation of the instantaneous torque; and the system can form an embedded system, instantaneous torque estimation is realized through a neural network torque estimation model, conversion from phase reference torque to flux linkage and flux linkage feed-forward compensation are realized through a dynamic RBF neural network torque-flux linkage model, flux linkage control and torque pulsation suppression of the SRM are realized, and online control of the switched reluctance motor is facilitated.

The invention discloses an online monitoring method for the electrolytic grinding process. The online monitoring method for the electrolytic grinding process comprises the steps that 1, electrolyte is obtained and diluted; 2, particles in the diluted electrolyte are analyzed; 3, particle features obtained through analysis are reasonably selected through a feature fusion technology, so that reasonable feature indexes are obtained for identifying the types of the particles; 4, based on fuzzy C-means and the support vector data description theory, an electrolytic grinding process evaluating model is established, and the electrolytic grinding process is monitored according to the mapping relationship between the types of the particles and the electrolytic grinding process. By the adoption of the online monitoring method for the electrolytic grinding process, the ratio parameter between the mechanical removal amount and the electrochemical removal amount in the electrolytic grinding process can be obtained, the purpose of monitoring the electrolytic grinding process on line can be achieved so that the electrolytic grinding process can be controlled on line, and therefore the online monitoring method for electrolytic grinding precision is effectively improved.

The present invention relates to a trench gate structure and a fabrication method thereof. The trench gate structure includes a substrate, a trench on the surface of the substrate, an insulating liner on the substrate, a gate oxide layer on the inner surface of the trench, and a polysilicon gate on the gate oxide layer; the insulating liner adjoins the trench through the ramp structure of the insulating liner; the polysilicon gate extends along the ramp structure from the trench to the insulating liner; the insulating liner comprises a polysilicon gate lifting region which is recessed relative to the other portions of the liner; and the polysilicon gate extending out from the trench is supported on the polysilicon gate lifting region. According to the trench gate structure of the invention, a portion of the polysilicon gate in the trench is independent from a portion of the polysilicon gate which extends to the insulating liner, and therefore, the depth of the trench and the depth of a contact hole will not limit each other. The photo-etching of the polysilicon gate and polysilicon photo-etching of a device are performed in the same step, and therefore, additional photo-etching masks and photo-etching layers are not needed to be adopted, and cost increase can be avoided.

The invention discloses a helical fiber grating manufacturing device and a manufacturing method thereof and relates to helical fiber gratings. The device comprises a direct current motor, a storage pipe, a metal rod, a heater, a temperature controller, a micro-channel, a power supply, a conductive base, a translation stage controller and an X-Y-axis precision translation stage. The manufacturing method comprises the following steps: adding electrostatic spinning raw materials into the storage pipe, regulating the temperature controller to heat so as to remove the moisture in the raw material, and regulating the temperature to the melting point of the raw materials; inserting the metal rod into a melt polymer, extending out of a discharge hole below the micro-channel, and regulating the rotating speed of the direct current motor until the needle tip is coated by the melt polymer, so that the molten liquid stably flows out; switching on the power switch, regulating the voltage of the conductive base to a preset negative pressure, starting the electrostatic spinning process, collecting electrospun fibers on the conductive base, reducing the temperature for curing in the deposition process, and forming a helical structure; enabling the X-Y-axis precision translation stage to drive the conductive base to move by virtue of the translation stage controller, thereby obtaining the helical fiber grating with the controllable diameter and screw pitch.

The invention discloses an online detection system for single-capped electrodeless fluorescent lamps, which is characterized in that a test area of a light source aging operating device is provided with a positioning device, and when a detected light source moves to a position at which the positioning device is arranged, the positioning device emits positioning signals; the online detection system is provided with an online testing system for responding to the positioning signals emitted by the positioning device, and a data processing system; in the test area of the light source aging operating device, the online testing system carries out signal acquisition on the detected light source so as to obtain an acquisition signal, and the data processing system carries out data conversion and processing on the acquisition signal; and the data processing system provides an online test control signal. According to the invention, an online test is performed in the aging link of a single-capped electrodeless fluorescent lamp so as to obtain the performance parameters and matching effects of products in real time, thereby facilitating the quality management and control on products.