242 results about "Transfer function model" patented technology

A MIDI-compatible gesture synthesizer is provided for use with a conventional music synthesizer to create musically realistic<DEL-S DATE="20020416" ID="DEL-S-00001" / >ally<DEL-E ID="DEL-S-00001" / > sounding gestures. The gesture synthesizer is responsive to one or more user controllable input signals, and includes several transfer function models that may be user-selected. One transfer function models properties of muscles using Hill's force-velocity equation to describe the non-linearity of muscle activation. A second transfer function models the cyclic oscillation produced by opposing effects of two force sources representing the cyclic oppositional action of muscle systems. A third transfer function emulates the response of muscles to internal electrical impulses. A fourth transfer function provides a model representing and altering virtual trajectory of gestures. A fifth transfer function models visco-elastic properties of muscle response to simulated loads. The gesture synthesizer outputs <DEL-S DATE="20020416" ID="DEL-S-00002" / >MIDI-compatible<DEL-E ID="DEL-S-00002" / > continuous pitch data, tone volume and tone timbre information. The continuous pitch data is combined with discrete pitch data provided by the discrete pitch generator within the conventional synthesizer, and the combined signal is input to a tone generator, along with the tone volume and tone timbre information. The tone generator outputs tones that are user-controllable in real time during performance of a musical gesture.

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 invention discloses a double-feed blower fan subsynchronous oscillation inhibition method based on virtual impedance control, and the method comprises the steps: enabling a dq-axis component of a rotor current of a double-feed blower fan to serve as an input signal, and filtering a low-frequency component and a fundamental frequency component through a band-pass filter, and then obtaining a subsynchronous current component. The current component brings virtual impedance to a rotor loop through a proportional amplifier and a differentiation link, thereby achieving the effects of increasing the subsynchronous oscillation damping and inhibiting the subsynchronous oscillation. According to the invention, the method starts from the structure of a rotor controller, achieves the research of the relation between the rotor current and the output voltage of the rotor controller, and obtains the equivalent resistance of a rotor side controller, i.e., the virtual resistance value. Afterwards, a double-feed blower fan rotor current transfer function model is used for solving and obtaining a virtual inductance value needed by the virtual impedance control. The method is advantageous in that the method is simple in parameter configuration, is clear in physical concepts, improves a virtual resistance control strategy, is better in adaptability, is low in control cost, and can effectively inhibit the subsynchronous oscillation to a certain degree.

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.

The invention provides a simulation turntable self-correction control method based on model parameter accurate identification, relates to the simulation turntable self-correction control method based on model parameter accurate identification, and is to solve the defects that an existing open-loop frequency sweep measurement method needs to consume a lot of time, a fixed parameter control method is poor in load change adaptability, and it is likely to have the problem that several sets of control method parameters cannot ensure optimum performance of a system or even cannot ensure system stability. The method comprises the following specific steps: 1) establishing a turntable servo system mechanism model according to a structure of a turntable servo system; 2) measuring a control quantity DA value needed for counteracting Coulomb friction moment Tc, and carrying out compensation on a control input signal of an open-loop transfer function model G(s) of the turntable servo system in the step 1); 3) obtaining accurate parameters taum<^>, taue<^> and K<^>; and 4) obtaining an optimal self-correction control link J(s). The method is used in the field of simulation turntable control.

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.

The invention discloses a dynamic parameter setting method for a superheater mechanism model by combining with field data. The method comprises the following steps that: according to a basic physicallaw, from the internal working process of a system, establishing a system mechanism simulation model; taking a superheater outlet parameter as a feature parameter, and carrying out modeling on the superheater in five sections in order to improve model accuracy; in addition, adding the dynamic parameter [Alpha] of the model; and according to practical operation features, carrying out optimal regulation on the simulation model. By use of the method, the superheater mechanism model is combined with a transfer function distinguishing model based on field data, a particle swarm intelligent algorithm is used to automatically set dynamic parameters in the mechanism model according to an error function on the basis of the time constant of the transfer function model distinguished by the field data, simplification and deficiency for the dynamic features of the practical process when the mechanism model is established can be effectively improved, and dynamic feature simulation accuracy and the development efficiency of a simulation system are improved.

The invention relates to a DCS (distributed control system) control method and a SMITH controller. The SMITH controller comprises a regulated variable actual value module, subtraction modules, a PID (proportion, integration and differentiation) controller, an actuator M / A station, an actuator output module, a process quantity module, a set value module, a multiplier, a proportionality coefficient modification function device, a multi-order inertia time constant function device, a pure delay time function device and first-order inertia elements. The control method includes procedures of (1), performing a step response test and determining a transfer function model of a controlled object; (2), configuring a DCS by the aid of the transfer function model, corresponding parameter modules and the corresponding function devices; (3), computing parameters of a unit under a load working condition; (4), inputting the parameters to the configuration graph function devices; (5), mounting the configured DCS in a DCS controller of an application system. The DCS control method and the SMITH controller have the advantages that modification parameters of the controller are computed by the aid of the transfer function model, the DCS is configured by the aid of the modification parameters, accordingly lagging in control procedures of a power plant is reduced or eliminated, and the production running control stability is improved.

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 provides a wind power active power / frequency coupling electrical power system frequency characteristic calculation method based on pitch control. According to a one-time frequency modulation response transfer function model of a single wind turbine unit, a single steam turbine-speed governor model transfer function and a single water turbine-speed governor transfer function, a weighted equivalent polymerization method is used for separately calculating out a wind power plant one-time frequency modulation response transfer function model, a multiple steam turbine-speed governor model transfer function, a multiple water turbine-speed governor transfer function. A one-time frequency modulation control strategy based on the pitch control is taken into consideration, and electrical power system equivalent inertial time constants in different wind power permeability are calculated and solved. By the combination of the models and parameters, an improved SFR frequency response model is constructed, and a closed-loop system transfer function is calculated and solved according to the improved SFR frequency response model, wherein power shortage disturbance serves as input and system frequency deviation serves as output, and therefore a system frequency deviation frequency domain / time domain analytical solution is calculated under a sudden load increase step response. Finally, the validity and accuracy of a calculation method are systematically verified through a simulation example.

The invention relates to an unmanned vehicle formation driving method based on a directed communication network. The method comprises the following steps that 1) the transfer function model of the individual unmanned vehicles of the unmanned vehicle formation is identified; 2) the communication network topology of the unmanned vehicle formation is set and the input degree of each vehicle is acquired; 3) the H2 optimal formation controller of the individual unmanned vehicles is constructed according to the performance index; 4) a filter fi(s) is connected in series after the H2 optimal formation controller and the stability domain of the performance degree is acquired, and compromise of the nominal performance and the robust performance can be realized through quantitative adjustment in thestability domain; 5) the H2 optimal formation controller of the individual unmanned vehicles is converted into the optimal PID controller; and 6) the optimal PID formation controller is discretized so as to acquire the control signal sequence and output the formation control command. Compared with the methods in the prior art, the unmanned vehicle formation driving method has the advantages of distributed individual design, facilitating actual application and balancing the nominal performance and the robust performance.

The invention provides a prediction function control method for the rotating speed of a main driving system of a heading machine. The method includes the following steps: (1) establishing a transfer function model of a driving system; (2) resolving a relation of each input and each output so as to obtain a plurality of practical models, wherein each practical model includes a single input and a single output; (3) identifying a first-order prediction model of each practical model; using measurable disturbance feed-forward compensation to design a prediction-function controller. The prediction function control method of the driving system applies the prediction function control method to rotating speed control of the chipper disk driving system of the heading machine so as to realize comparatively high robustness and excellent tracking capability of the driving system; randomly jumped load torque and periodically time-varying transfer errors are used as measurable disturbances of the chipper disk driving system of the heading machine and the measurable disturbance feed-forward compensation is used to design the prediction function controller so that the anti-disturbance capability of the driving system is improved and the dynamic output characteristics of the system are improved.

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 a transfer function model parameter recognition method and device based on an improved particle swarm algorithm. A coevolution idea and a Gaussian disturbance strategy are introduced into a basic particle swarm optimization algorithm, a hybrid algorithm is formed with a bat algorithm under a coevolution framework, and a Gaussian disturbance term is added in the optimizationprocess to form a hybrid coevolution Gaussian particle swarm optimization algorithm; sampling the input and output of the to-be-identified object model and the estimation model, and solving the standard deviation between the actual output value of the system and the output value of the estimation model at the moment k; feeding back the standard deviation to an HCGPSO algorithm to obtain an optimal result of the current parameter; and replacing the original value with the optimal value of the current model parameter, updating the estimation model, and sequentially iterating until the requirement of an output recognition criterion is met, thereby realizing parameter recognition of the transfer function model.

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.