242 results about "Transfer function model" patented technology

The invention relates to the technical field of PID control, and discloses a fractional order integration PID controller setting and self-setting method. The method specifically comprises the following steps that firstly, the Bode ideal transfer function order beta and the amplitude cross-over frequency omega c are appropriately selected to meet the formula: 1<beta<2 and the formula: 0<omega c<omega max; secondly, when a controlled object mathematical model P(s) is known, the low order derivative of a transfer function model of a controlled object is solved, and then the third step is carried out, and when the controlled object mathematical model P(s) is unknown, the system information is identified according to the step response of the controlled object or the relay closed loop response, and the third step is carried out, wherein the two conditions are not met, the process is ended; thirdly, PID controller parameters with the fractional order integration are fast determined according to the parameter setting formula. According to the technical scheme, automatic control of an ordinary industrial process can be achieved easily.

A wind power penetration limit calculating method that considers frequency constraint and wind power frequency modulation; the method comprises the following steps: using a weight equivalence polymerization method to solve a wind power plant primary frequency modulation response transfer function model and a wind power primary frequency modulation active increment; considering a wind power virtualinertia control strategy, and solving a power system equivalent inertia time constant under different wind power penetration rates; calculating a load damping effect, building a power grid frequencyresponse model that is equivalent to a rotor swing equation, and using the model to describe power system frequency response characteristics; using the power system frequency stable state deviation boundary and frequency rate of change boundary as constraints, and proposing the power grid wind power penetration limit calculating method. The method introduces the real wind power virtual inertia response, the active increment formed by the primary frequency modulation response and the power system frequency constraint into the wind power penetration limit calculation, thus improving the power grid robustness under the wind power grid connection condition, ensuring the power grid to stable and safely operate, and providing important guiding meanings for wind power grid connection planning construction.

The invention provides a method for online monitoring performance of a steam turbine of a coal-firing unit. The method includes the following steps: step 1, according to boiler operation designing procedures, acquiring boiler structure parameters, and reading real-time data of operation condition measuring points of a steam-water system and a heat exchanger system at a given moment from a real-time database of a DCS (distributed control system); step 2, calculating specific enthalpy and density of a working medium on the basis of a working medium physical parameter library; step 3, according to a working medium side energy balance model, respectively calculating heat absorbed by the working medium in the steam-water system and the heat exchanger system to acquire total energy increment of the working medium; step 4, building a transmission function model between the total energy increment of the working medium and output power of the unit, and acquiring efficiency and heat consumption rate of the steam turbine through parameter recognition. The method can be used for online monitoring operation conditions of the steam turbine and providing technical support for coordination and optimization of the unit.

The present invention belongs to the field of multi-variable system application technology. Via one set of simple and practical step response test, the distinction in powerfully coupled multi-variable system is amalyzed into the distinction in several single-in single-out systems so as to obtain precise transfer function model of the multi-variable system. Specially, the process includes four steps of initialization, step response test, synthesis of multi-variable process and parameter distinction in synthesized subprocess. The present invention can realize the real-time on-line distinction of the multi-variable system, and has less impact of step test signal required for system distinction on the normal operation of the control system and no special requirement of distinction algorithm in signal amplitude. The method of the present invention is suitable for industrial process control, robot, aeronautics, astronautics and other multi-variable systems.

The invention provides a real-time identification method for a fired coal lower heating value of a coal-fired power plant. The real-time identification method includes the steps of (1) obtaining boiler structure parameters according to a boiler operation design discipline, and reading an operation condition measurement point real-time value at the given moment from a real-time database of a DSC, (2) calculating the specific enthalpy and the density of working media and the specific heat and the density of smoke based on a working medium physical property parameter base and a smoke physical property parameter base, (3) correcting main steam flow masses based on a relation model of main steam adjustment door opening degrees and the main steam flow masses, (4) respectively calculating corresponding energy output of various parts on the boiler side and total energy output at the given moment according to a boiler-side complete-flow-path mechanism model, (5) building a transfer function model between coal feeding flow masses of a coal feeder and the fired coal flow masses, and (6) building a transfer function model between the fired coal flow masses and the total energy output. The real-time identification method is used for on-line identification on the fired coal lower heating value, and has the application potential of combustion and coal blending optimization.

A method to determine and apply PI gain constants to an HVAC PI controller used to control an HVAC component includes the steps of: recording an opened loop HVAC component dynamic step response; fitting the HVAC component dynamic response to a transfer function model; calculating the PI gain constants from the model; entering the calculated PI gains into a PI control algorithm; and running the PI control algorithm on the HVAC PI controller to control the HVAC component. The inventive method can be used with an HVAC system comprising, an HVAC system component; an HVAC system component controller electrically connected to the HVAC system component to control the operation of the HVAC system component; and a PI algorithm. The PI algorithm uses PI gain constants calculated from the open loop transfer function of the HVAC system component.

The invention discloses an accurate detection method for the voltage travelling wave of a transmission line fault based on waveform inversion. According to the method, special voltage travelling wave sensors are mounted on grounding wires of capacitive equipment, as capacitive voltage transformers (CVT), of transformer stations at the two ends of a power transmission line; the special voltage travelling wave sensors are utilized to detect a primary voltage traveling wave signal after the transmission line fault and output a secondary voltage traveling wave signal; and a high-frequency transfer function model of the special voltage travelling wave sensors is used to establish a high-frequency inversion function model of the special voltage travelling wave sensors, according to the high-frequency inversion function model, a random resonance-deconvolution inversion algorithm is designed for waveform inversion, the primary voltage traveling wave signal is output and inversed, and accurate inversion from the second voltage traveling wave signal to the primary voltage traveling wave signal is realized. According to the invention, the problem of waveform distortion generated when the primary voltage traveling wave signals is transformed by the special voltage travelling wave sensors, and the primary voltage traveling wave signal can be detected accurately and effectively.

The invention relates to a large resection rate milling tremor monitoring method considering rigidity time-varying, and relates to the large resection rate high precision manufacture field with material resection rate above 80%; the monitoring method comprises the following steps: S10, cutter-workpiece coupling system time-varying transfer function modeling: substituting a relation between the transfer function and cutting force and displacement into a built displacement equation so as to obtain a cutter-workpiece coupling system time-varying transfer function model; S20, building a time-verying coupling transfer function online monitoring measuring system so as to monitor the transfer function in real time; S30, building a milling tremor stability kinetic model, substituting the transfer function value measured by the S20 into the kinetic model in the S30, monitoring tremor generation, and obtaining a non-tremor processing parameter scope; S40, providing a tremor optimization processing parameter control guide scheme according to the S30.

The invention relates to a novel modeling and controlling method of a drain pipe network hydraulics system. The conventional computation method is more time-consuming and not beneficial to real-time control. The novel modeling and controlling method disclosed by the invention is a method for rapidly computing the water depth of a pipeline by utilizing a transfer function model. Through the adoption of the method disclosed by the invention, the regional sewage overflow pollution is minimized on the premise of fully utilizing all water storage equipment of a system so that the urban flood-prevention and anti-waterlogging capabilities are improved; in addition, a basis is settled for the conversion from manual operation to automatic operation of a combined sewerage system; meanwhile, the situation that sewage overflow happens while residual water storage systems are idle at a specific region is avoided; and therefore the regional sewage overflow pollution is finally minimized.

A method for controlling self ¿C setting of intelligence and optimization parameter includes obtaining object generalized transmission function model through system identification firsts; then selecting and judging automatic control manner and control mode, carrying out optimization setting for control parameters of each control mode separately based on genetic algorithm; finally setting system running on automatic operation mode.

The invention, which belongs to the motion control field, relates to a parameter setting method of a sliding mode controller of a servo system. The method comprises: step one, a transfer function model of a servo system is established according mechanical and electrical structures of the servo system and needed parameters in the model are obtained; step two, a corresponding system simulink simulation model is established and input and output interfaces needed for a particle swarm optimization algorithm are left; step three, a proper fitness function is selected according to location tracking error and speed tracking error demands; step four, programming is carried out in matlab to optimize a particle swarm; step five, corresponding c,k, and epsilon of location vectors are transferred into the simulink simulation model to obtain a location error response and a speed error response of the system; step six, the speed and location of each particle are updated; step seven, when the k reaches a set maximum iterations number, the iteration process is completed and an optimization result is outputted; otherwise, the operation of the step five is carried out again; and step eight, a global optimal location vector is substituted into a sliding mode controller of the servo system. According to the invention, buffeting amplitude minimization or complete elimination of buffeting can be realized; and the tracking error can be minimized.

A directional hearing aid (100) comprising at least two microphones (201, 202) has means (200) for matching differences in amplitude and phase between the two microphones (201, 202). The microphone matching means (200) compare differences between measured transfer functions of the microphone signal paths at a number of frequencies during use of the hearing aid (100), compares the differences to differences at similar frequencies in a model of the transfer functions of the microphone signal paths, derives a set of parameters based on the comparison, and adjusts the parameters in order to minimize the difference in level differences between the model and the microphones (201, 202). The model is then used to match the microphones (201, 202) mutually by applying appropriate control parameters (103, 104, 105, 106) to an adaptive matching filter (108) carrying one of the microphone signals.

The invention discloses a method for suppressing the rotation speed fluctuation of a PMSM based on iterative learning. The method can suppress the periodic pulsating torque of the PMSM and improve servo precision. The method is a motor control algorithm that compensate for torque ripple by using a PI learning law and attenuates non-periodic agitation error accumulation by introducing a forgettingfactor. The method comprises steps of: firstly establishing a transfer function model of an iterative learning controller to analyze its stability; then determining the convergence condition of the algorithm; and designing two important parameters, namely the learning gain and the forgetting factor, in consideration of the steady-state performance and dynamic response performance of the system. The method is simple and easy to implement, and can track the desired trajectory with high accuracy by learning the periodic deviation signal.

The invention discloses a sampling anti-interference identification modeling method for an industrial time delay response processes. According to the method, pseudorandom binary system pulse sequences convenient to realize industrial processes and persistent excitation signals such as square waves or trapezoidal waves are utilized to excite to-be-distinguished systems. The method comprises the following steps of: firstly estimating a delay time range, a fitting model structure and an order according to dynamic response characteristics of a to-be-distinguished system; design identification experimental scheme, and determining an open-loop or closed-loop operation for of an identification experiment, an amplitude value of an excitation signal, a sampling time and a length of sampling data; and eliminating the influences of non-random load interferences by applying a proposed double-forgetting factor identification algorithm according to the sampling data, so as to realize the unbiased estimation for the parameters of system transfer function models with integer type time delay parameters. According to the method, a convenient and reliable anti-interference identification modeling technology is provided for the industrial time delay response processes.

The invention discloses a secondary channel offline identification method for headphone active noise control. The method comprises the following steps: step S100, establishing an ANC system secondarychannel transfer function model S(z) as shown in description; step S200, determining a parameter of a transfer function model S(z); and step S300, substituting the parameter into an inverse filter ofthe S(z), performing LMS self-adaptive filter to obtain noise elimination sound wave produced by a secondary loudspeaker and opposite to the same phase of a main loudspeaker amplitude. By adopting anapproximate model of the secondary channel is obtained through real measurement, and then a method of approximating the actual secondary channel mode is performed to obtain a parameter of an actual secondary channel transfer function; therefore, an offline modeling method is adopted, the structure is simple, the hardware realization is easy, and the method is simple and feasible. The parameter issubstituted into the inverse filter of the S(z) to perform LMS self-adaptive filtering to obtain the noise elimination sound wave produced by a secondary loudspeaker and opposite to the same phase ofa main loudspeaker amplitude, thereby obtaining good noise reduction effect.

The invention discloses a dynamic model identification method and system based on a recurrent neural network. The system includes a dynamic model identification module, a module for converting a recurrent neural network model into a transfer function model, and a nonlinear module for converting a recurrent neural network into a state space model and the recurrent neural network. The dynamic modelidentification module includes a forward calculation module, an error calculation module, and a back-propagation calculation module. The method includes first establishing the recurrent neural networkmodel; converting the recurrent neural network model into the transfer function model or the state space model as needed; or non-linearizing the recurrent neural network model. The dynamic model identification method and system based on the recurrent neural network are simple to calculate and convenient to implement, the training time is quick, and mutual conversion can be performed with the transfer function model and the state space model. The dynamic model identification method and system can be well popularized to non-linear situations, a good fitting effect can be achieved, and the dynamic model identification method and system can be applied to industrial control model identification very conveniently.

The invention discloses an estimation and compensation method of a TIADC system based on a polynomial model, and belongs to an estimation and compensation algorithm of digital back-end processing based on a channel transfer function model. Any linear error can be contained, comprising, but not limited to, time errors, gain errors, pole-zero errors, etc. Therefore, by adoption of a correction method based on a channel transfer function, an error effect of any linear filter can be transferred into a frequency domain response mismatch error, and by adoption of the estimation and compensation method disclosed by the invention, estimation and compensation of a high-speed time interleaved analog-to-digital conversion is realized, and the estimation and compensation method has the advantages of good validity, universality and practicability.

The invention discloses a unit coordinated control master control system decoupling compensation control method. According to the method, data are acquired by utilizing a unit onsite coal feed rate step test and a steam turbine high pressure regulating valve step test. A boiler master control decoupling compensation transfer function model is established through a genetic identification algorithm. Meanwhile, a boiler master control compensation simplification model is established and coupled in boiler master control by utilizing decoupling compensation model inference so as to overcome the high delay and high inertia properties of a unit boiler master control system. Compared with the conventional cascade control method, main team pressure compensation regulation can be more rapidly performed by the control method without generating fluctuation of a high pressure regulating valve so that safer and more economical and energy-saving operation of the unit can be realized.

The invention discloses a PSO-PID algorithm based intelligent control method of an automatic gas control valve. The automatic gas control valve is taken as a research object, characteristics of a PID control system is taken into full consideration, and a transfer function model of a controlled object is established; meanwhile, an artificial intelligence technology is introduced, PID parameter optimal solutions are searched by an improved particle swarm algorithm with converging factors, and gas flow is automatically controlled. The PSO-PID algorithm based intelligent control method has the advantages that the shortcomings about manual parameter adjustment on a traditional PID gas control valve are overcome, and self-adjusting of PID parameters is realized; the intelligent control method is short in consumed time, high in precision and adaptive capability, good in applicability and the like, and has a promising application prospect and high business value.

The invention discloses an extended state space predictive function control based integral object control method which comprises the following steps: 1) establishing a transfer function model according to the step response data of a controlled integral object; 2) transforming the transfer function model into an extended state space model; and 3) designing a predictive function controller based on the extended state space model. The invention can effectively resist the interference in the integral object through the means of data acquisition, model establishment, model conversion, prediction and error correction; and the expanded state space model also provides more freedom for the design of a controller, therefore, further promoting the application of the extended state space predictive function control.