38results about How to "Optimal Control Parameters" patented technology

The invention discloses a method for self-adjusting control parameters of a speed ring of a permanent magnet synchronous motor based on fractional orders. An integer-order proportional integral (PI) controller in an alternating current servo system of the permanent magnet synchronous motor is replaced by a fractional-order PI controller, parameters of the fractional-order PI controller are automatically adjusted, and the alternating current servo system of the permanent magnet synchronous motor can be controlled. The method specifically comprises the following steps of: firstly, acquiring current and speed signals of the alternating current servo system; secondly, identifying a speed ring controlled object model of a permanent magnet synchronous motor servo system according to the acquired signals, and identifying the parameters of the model; and finally, optimally adjusting the control parameters, and thus obtaining optimal control parameters. According to the method, the original integer-order PI controller is replaced by the fractional-order PI controller, and the parameters of the controller are automatically adjusted; the parameters of the controller are optimized by using a pattern search algorithm; and the adjusted parameters of the controller are high in robust, high in anti-disturbance capacity and high in control accuracy.

The invention discloses a PDFF-based AC servo driver control parameter self-tuning method. Firstly, current and speed signals required for identifying an AC servo system model are acquired; secondly, according to the acquired signals, a speed loop controlled object model of a permanent magnet synchronous motor AC servo driving system is identified and parameters of the model are identified; and finally, according to the parameters and performance indexes of the model, searching optimization tuning is performed on control parameters of a servo driver so that the optimal control parameter is acquired. According to the self-tuning method, a PDFF controller is utilized to substitute a conventional PI controller on a speed loop of the servo driver and the parameters of the controller are automatically tuned. The model of the controlled object is identified by the self-tuning method by utilizing a recursion least square method. Then according to the feasible performance indexes, searching optimization is performed on the parameters of the controller by utilizing a mode searching algorithm, and the optimal control parameter is obtained so that the servo driving system can be great in anti-disturbance capability, control precision and robustness.

The invention relates to an intelligent adjusting system of in-vehicle air quality and an application method thereof. The system comprises an air quality detecting unit, an air quality adjusting unit and a data processing control unit. The air quality detecting unit comprises a concentration detector of pollutants inside and outside a vehicle; the air quality adjusting unit comprises a vehicle-mounted air conditioner and a vehicle-mounted air purifier; the data processing control unit comprises a processor and a wireless control terminal; and the processor and the wireless control terminal are connected through an internet of things technology. Controllers input travel parameters through the wireless control terminal; the parameters are transmitted into the processor through networking; the processor calculates optimal operation parameters of the air quality adjusting unit through a pre-built calculation model and data input by the air quality detecting unit and the air quality adjusting unit, and returns and performs an instruction to realize intelligent adjustment of the in-vehicle air quality. The system can detect the pollution level of the pollutants inside and outside the vehicle in real time, optimally adjusts the operation parameters of the vehicle-mounted air conditioner and a vehicle-mounted air filter, and improves the in-vehicle air quality. The adjusting system has such characteristics as advanced and reasonable settings, realization of automatic control, complete functions and simple and fast operation.

The invention discloses a fast self-learning improved ADRC control method for a non-linear system, which comprises the following steps: S1, creating an active disturbance rejection controller (ADRC) which includes a tracking differentiator (TD) part, an extended state observer (ESO) part, a non-linear state error feedback (NLSEF) part and a disturbance compensation part, wherein S1 includes S11, establishing a tracking differentiator (TD) control model, S12, establishing an extended state observer (ESO) control model, S13, establishing a non-linear state error feedback (NLSEF) control model, and S14, establishing a disturbance compensation control model; S2, creating a self-learning active disturbance rejection controller (SADRC): applying a self-learning method to the non-linear state error feedback (NLSEF) control model to establish a self-learning non-linear active disturbance rejection control system model; and S3, creating a fast self-learning active disturbance rejection controller (FSADRC): designing a learning rate oriented adaptive mechanism by using an additional momentum term method and establishing a fast self-learning model based on dynamic adaptive learning rate.

The invention relates to self-control laser surgical equipment, which consists of a main controller, a display, a charge-coupled device (CCD) camera, a laser, light source equipment, a main bracket, a cantilever arm, a suspension surgical treatment head, a microscopic observation system and a microscopic surgical adapter. The main controller recognizes and processes images and light spectrums of focal tissues and normal tissues acquired by the CCD camera and correspondingly send a command to control the operation of the laser so as to prevent faulty operation of a laser surgery from damaging the normal tissues and making a surgery mistake; the main controller sends a command to control the startup and shutdown of the laser and modify laser output; an optical lens group forms a light path; and the microscopic observation system, a microscopic observation mirror, the CCD camera and the microscopic surgical adapter are integrated with one another through the optical lens group. The equipment has the advantages of simple structure, reasonable design, simple and easily-grasped operation, capability of eliminating the focal tissues without damaging the normal tissues in a surgery process, various control modes, adjustable parameter, wide application and capability of accurately controlling the number of surgeries and improving treating effect.

The invention discloses a special efficient data-driven internal-model polynomial controller for industrial processes. The special efficient data-driven internal-model polynomial controller is characterized in that an integral control structure with polynomial and internal-model functions is designed, an error series [e(k)] is inputted into a polynomial controller, a series [u(k)] is outputted by the polynomial controller, the structure is shown as an equation, and a<0>-a<n> and b<1>-b<n> are coefficients to be determined; parameters of a internal-model polynomial controller are optimized by means of data-driven stochastic approximation. The special efficient data-driven internal-model polynomial controller has the advantages that the essence of simplicity and practicality of a PID (proportion, integration and differentiation) controller is inherited, shortcomings of single structure and low error utilization efficiency of the PID controller are overcome, the PID controller is developed into the structure-variable internal-model polynomial controller, dependency on a mathematical model of a controlled object is omitted, and an internal-model driving function is directly added into the internal-model polynomial controller on the basis of data by the aid of a stochastic approximation principle; an internal-model compensation function can be automatically started specifically for a process with obvious large lag, stochastic approximation is synchronously performed on parameters of the internal-model controller and the parameters of the polynomial controllers, and the optimal control parameters can be obtained.

The invention discloses a self-detection method for voice coil motor parameters. The method comprises steps: a control chip is connected with the voice coil motor through a control interface, and through controlling the current inside the voice coil motor, the control chip pushes the motor to different positions; the coil in the voice coil motor performs magnetic line cutting movement on the magnetic field inside the voice coil motor, an induced electromotive force is generated at two ends of the coil, and induced voltage is obtained; the control chip automatically detects the induced electromotive force; and the control chip measures and calculates the parameters of the voice coil motor according to the detected induced electromotive force. The motor parameters are detected by the chip, the motor parameters do not need to be tested by a client, each chip is corresponding to one motor, and each motor is ensured to have the optimal control parameters; and the chip can detect the motor parameters in real time, and the phenomenon that parameter change is caused by the time lapse when the motor is used and the stability effects are caused to be weak can be avoided.

The invention is glaucoma filter automatic controlled laser operator for curing glaucoma. The system is made up of software and hardware; the hardware is made up of laser, guiding light laser, image picking device, mechanism frame and computer, the guiding laser is assembled in the box of primary laser, the laser knife of the primary laser is connected with the image picking device through mechanical frame, and it is connected to the computer through interface card or interface circuit; the work of each hardware is connected by software. It uses image picking device to acquire the image information of the focus part, and monitors the operation process in real-time; the system combines the active control and the feedback control, monitors the operation process in real-time and shuts off the laser automatically after the operation has been completed, it can acquires the best working parameter, and reduces the damage to the lowest effectively.

The invention relates to a vibration damping control method and device for a hybrid electric vehicle. The method includes the steps of collecting vibration signals in three directions when the vehicleis at a standstill state, and calculating a combined phasor amplitude of the vibration signals in the three directions; determining whether the combined phasor amplitude is less than the set amplitude threshold or not, and if the combined phasor amplitude is not less than the set amplitude threshold, determining whether the engine rotating speed is related to the vehicle speed or not; if the engine rotating speed is not related to the vehicle speed, selecting at least one power adjustment strategy for power adjusting, and finding out corresponding overall vehicle control parameters enabling the combined phasor amplitude of the vehicle in the three directions to be minimum in the power adjusting process; and using the corresponding overall vehicle control parameters enabling the combined phasor amplitude of the vehicle in the three directions to be minimum to control a vehicle power system. By means of the vibration damping control method and device, closed loop control of signal detection and control optimization is formed by organically combining vibration detection and optimization control, the optimization cycle is better shortened, and the optimization effect is improved.

The invention discloses a ventilation system for nursing and disinfection. Air enters a main pipeline through a compressor at a ventilation inlet; a filter, a jet flow atomizer and a buffer chamber are sequentially arranged on the upstream of the main pipeline; a humidifier, an ion generator, an air ion meter, an impactor, a vacuum pump, an air ion meter and an anemometer are sequentially arranged on the downstream of the main pipeline; the air is discharged into a ward through an air supply grille; and a heater, a controller and a centrifugal fan are arranged in the buffer chamber. By using the ventilation system disclosed by the invention, optimal control parameters are obtained according to effect evaluation indexes of the steady state simulation and the transient simulation, and the controller transmits the optimal control parameters to each control component for layered ventilation, so that the exposure risk of medical staff in a hospital ward can be greatly reduced.

The invention relates to an operational optimization method for nitration and nitrosation processes, and belongs to the technical field of wastewater biotreatment. The method comprises the following steps of: construction of a dynamic control system: according to parameters involved in a two-step nitration process of NH4+/-N->NO2--N and NO2--N->NO3--N, establishing kinetic models of the nitrosation and nitration processes; according to characteristics of substance change, a reactor flow state and a reactor unit involved in the nitration process, establishing a material balance equation set of the whole nitration process; in combination with the kinetic models and the material balance equation set, constructing the dynamic simulation control system for the simulated nitration process; and simulation operation: obtaining the parameters involved in the nitration process in the kinetic models of the nitrosation and nitration processes, substituting the parameters into the dynamic simulation control system, and performing operation to obtain nitrosation and nitration reaction results. The method quantitatively describes the nitration process of ammonia nitrogen in a wastewater treatment process and accurately simulates the two-step nitration process.

The present invention discloses an electric cylinder pressure high-accuracy and fast loading control method. The method includes the four parts of a startup automatic origin point search and reset control method, a fast and accurate pressure loading control method, a self-learning-based control parameter generation method, an accurate origin point return and no-load pressure zeroing method; the fast and accurate pressure loading control method includes a position preloading control method, a pressure preloading control method, a pressure rough loading control method and a pressure fine loading control method. With the electric cylinder pressure high-accuracy and fast loading control method of the invention adopted, control on high-accuracy and fast loading of the pressure of an electric cylinder can be realized; the origin point position of the electric cylinder can be adjustable and can be fast reset; the loading of the pressure is fast, accurate and stable; optimal control parameters can be automatically generated through self leaning for different applications; and the electric cylinder pressure high-accuracy and fast loading control method is environmentally friendly and has a broad application prospect.

The invention relates to a preparation method of low-molecular-weight halogen flame-retardant polycarbonate, which is characterized by comprising the following steps: a. adding polyhalo bisphenol A into a sodium hydroxide solution-haloalkane mixed system, completely dissolving by stirring at normal temperature, and meanwhile, adding a catalyst; b. introducing phosgene, meanwhile, dropwisely adding a sodium hydroxide solution to keep the pH value of the system at 7-14, and carrying out prepolymerization reaction at 0-20 DEG C for 0.2-1.5 hours; c. increasing the reaction temperature to 10-40 DEG C, adding a blocking agent, and meanwhile, dropwisely adding a sodium hydroxide solution to keep the pH value of the system at 7-14; d. after the reaction finishes, standing to stratify to obtain an organic phase, adding fatty alcohol, washing to obtain a white solid, filtering, and drying to obtain the product. By strictly controlling the prepolymerization and polycondensation reaction temperatures and the pH value of the reaction system, the synthesized product has small fluctuation of the molecular weight, and the molecular weight can be fixed within a certain range. The synthesis technique has the advantages of short period, simple operating technique and high efficiency.

The invention relates to an optimizing, energy saving and carbon reducing method of a DCS (Distributed Control System) for papermaking. A DCS is adopted. Firstly, according to the types of raw materials, the performance characteristics of a product, the speed of a paper machine and the like, the pulping concentration, the pulping current, the optimal pulping concentration of starting of a disc mill, the ratio of a core layer and the ratio of a surface layer to a bottom layer are reasonably controlled, and then the DCS is used for controlling different pulping power distribution and disc mill series connection modes; a pulping result is comprehensively analyzed to obtain related data; the data is fed back to the DCS control for comprehensive processing to obtain optimized data; and finally, the DCS makes adjustment according to the optimized data to control different pulping power distribution and disc mill series connection modes, and optimization, energy conservation and carbon reduction of the DCS for papermaking are achieved. Compared with the prior art, the DCS control system is comprehensively applied and optimized according to relevant characteristic parameters and consumption data of raw materials of the paper machine, so that the optimal strength performance of paper under the condition of lowest energy consumption is achieved, and optimization, energy conservation and carbon reduction of the papermaking system are achieved.

The invention discloses a structural vibration active control method based on non-probability interval confidence reliability, and designs an active vibration control system capable of being automatically adjusted, and the system is improved on the basis of an original open-loop control system according to the uncertainty of structural parameters; according to the double-reliability-index calculation method based on reliability and confidence, vibration suppression algorithm research is conducted on the premise that structural parameters are uncertain on the original basis, and the confidenceindex is introduced, so that the designed active vibration control system capable of being automatically adjusted can improve the reliability of the structure. The feasibility of the active vibrationcontrol system capable of being automatically adjusted is verified through a continuous model and a discrete model, and the control method can be used for designing the active control system of an uncertain structure in the future.