45 results about "Single-input single-output system" patented technology

A system and method for enhancing the data rate of a WLAN. Through the deployment of a MIMO system, the data rate ordinarily expected of a SISO type system can be doubled. Yet, the MIMO system of the present invention can remain backward compatible with conventional WLAN standards implemented by typical SISO type system. In particular, the packet preamble of the MIMO packet of the present invention is similar to that of a conventional SISO system so as to be backward compatible with conventional SISO receivers. Additionally, the data model of the MIMO system can be configured to support the detection of symbols in the MIMO packet of the present invention. Importantly, the present invention can include a least squares soft-detector for use in a wireless LAN compatible MIMO system.

A method of predictive control for a single input, single output (SISO) system, including modeling the SISO system with model factors, detecting output from the SISO system, estimating a filtered disturbance from the output, determining a steady state target state from the filtered disturbance and a steady state target output, populating a dynamic optimization solution table using the model factors and a main tuning parameter, and determining an optimum input from the dynamic optimization solution table. Determining an optimum input includes determining a time varying parameter, determining a potential optimum input from the time varying parameter, and checking whether the potential optimum input is the optimum input.

A method for controlling limit PID of single input / single output system includes carrying out identification on object after A/D conversion for obtaining digital signal of sampling signal, ensuring four parameters corresponding to PID controller to be position value by regulating bottom limit of controller parameters, judging polarity of digital amount input signal and calculating error signal according to it, calculating parameter value of limit PID controller and calculating increment value being sent to executor after D/A conversion for operating controlled object in set range.

The invention discloses a model-based decoupling and disturbance-rejection control method for HCCI. The method comprises model-based decoupling control, active disturbance rejection control (ADRC), feed-forward control and self-adaptation compensation control for valve mechanism action delay. The method comprises the steps of designing a decoupling compensator on the basis of a control model of the HCCI, and converting an HCCI system into a plurality of independent single-input single-output (SISO) systems; conducting inversion on transfer functions of all SISO systems to obtain a feed-forward controller; designing ADRC controllers for all SISO systems respectively, and observing and compensating deviations of the model and random disturbance of the outside in real time; and estimating the action delay of a valve mechanism in real time, actively delaying an oil injection action, and obtaining the response speed which is the same as that of the valve mechanism. By the aid of the method, the modeling burden of the HCCI control model and the standard workload of controller parameters can be reduced greatly, the robustness for engine working condition variations is high, and the ignition process control is stable.

The invention provides a design method for resolving a modal space controller of a hydraulic drive six-degree-of-freedom parallel mechanism. A modal matrix is directly calculated according to system structure parameters; a six-degree-of-freedom strong coupling multi-input multi-output system is converted into a six-decoupling single-input single-output system in a modal space by conversion of the modal matrix; and parameters of a dynamic pressure feedback controller in the modal space are designed according to a hydraulic dynamic pressure feedback technology. The problem about coupling of a system is solved, and each decoupled modal space channel has the optimal control performance. The design method is only related to the system structure parameters, so that the application range of a modal decoupling controller is greatly expanded.

The invention discloses an auto-disturbance-rejection control method, device and system. The method comprises the steps that multiple parallel auto-disturbance-rejection controllers are adopted to achieve decoupling control over a controlled object, and multiple control sub-systems are formed, wherein the controlled object is a multi-input multi-output system including multiple input variables andmultiple output variables, each control sub-system is a single-input single-output system including one input variable and one output variable; the determinacy disturbance of each control sub-systemis compensated for based on a dynamic feedforward module, and the nondeterminacy disturbance of each control sub-system is compensated for through an expansion observer; based on the input and outputrelation of the control sub-systems, the output quantity of each control sub-system is determined according to the compensated input quantity. According to the auto-disturbance-rejection control method, device and system, the advantages of instantaneity, robustness and precision of large-inertia robot motion control are achieved.

The invention discloses a hypersonic speed maneuvering flight anti-rudder surface saturation resistance robust control method, belongs to flight control methods in the technical field of aviation and aerospace, and aims to solve the problem of poor control system performance of a HSV (hypersonic vehicle) caused by operating control surface amplitude saturation and composite disturbance in the hypersonic speed maneuvering flight process. The method provides a novel saturation resistance auxiliary design system, the order of the system is as same as that of an attitude control system, and the system is applicable to an SISO (single input single output) system and an MIMO (multiple input multiple output) system. Variables of the auxiliary system is led into a back-stepping method error variables, HSV maneuvering flight control laws are designed by the aid of the back-stepping method ideologies, and the closed loop stability of a system is ensured. The invention provides a disturbance observer based on a mixed tracking differentiator, tracking and approach for composite disturbance are performed by the disturbance observer, and compensation control laws are designed.

The invention discloses a self-feedback interference time domain suppression method in a co-channel full duplex SISO (single input single output) system. A self-feedback channel estimation filter w (n) is iteratively updated, an estimated interference value caused by not independent identically distributed received signal samples is subtracted from an updated quantity of the self-feedback channel estimation filter w (n) in each time of iterative updating, the w (n) can be finally converged to a GHLI (n) in an unbiased manner, a self-feedback interference signal is subtracted in a time domain by the aid of the self-feedback channel estimation filter w (n), finally, transmitted signals are only amplified received signals from a source end to the co-channel full duplex system, and influence on signal quality or self-excitation due to self-feedback interference is basically avoided. Compared with a traditional method, the method can be used for more rapidly and accurately estimating self-feedback interference channels.

The invention proposes a dynamic linearization adaptive control law algorithm based on the latest updated information for a single-input single-output system. The purpose of the algorithm is to solve the problems of low tracking accuracy and weak convergence of the identification algorithm of adaptive control. The algorithm adopts the principle of matrix inversion and hierarchical identification method to carry out online identification and latest information update of the pseudo partial derivative of the dynamic linearization parameter of the nonlinear system, and sets the reset condition of the pseudo partial derivative, and then combines the model-free adaptive control law, thus forming a series of new dynamic linearization adaptive control law algorithms based on the latest updated information for single-input single-output systems. The adaptive control algorithm is run by adjusting weight factors, step factors, initial conditions, and reset conditions. Compared with the prior art, the present invention has stronger convergence and better restraint ability to overshoot, oscillation, etc.; has higher output precision and better adjustment ability, and has richer and more flexible parameter adjustment methods.

The invention discloses a decoupling control method for a MIMO system based on a SISO full-format model-free controller and partial derivative information. The method comprises firstly decomposing theMIMO system into multiple mutually-coupled SISO systems according to the coupling characteristics and the tendency characteristics of the MIMO system; controlling the SISO system by a SISO full-format model-free controller; and based on a BP neural network, using partial deviation information as input, by using the minimization of a system error function value contributed by all SISO systematic errors as a goal and by using a gradient descent method in combination with control input, performing systematic error back-propagation calculation on the gradient information of each parameter to be set in the controller, realizing online automatic setting of parameters such as the penalty factor and the step length factor of the SISO full-format model-free controller, and simultaneously achievingonline decoupling among multiple SISO systems. The method can achieve a good control effect and is an effective means to solve the control problem of the MIMO system.

Methods and apparatus are provided for detecting an anomaly in fuel demand data and fuel supply data generated by a fuel metering system for an engine. The method comprises collecting the fuel demand data and the fuel supply data during operation of the fuel metering system, generating expected fuel supply data based on the collected fuel demand data and a nominal response model describing the expected behavior of the fuel metering system, and detecting the anomaly if a difference between the expected fuel supply data and the collected fuel supply data exceeds a predetermined threshold.

The invention provides a sound reproduction method and a system based on wave field synthesis and wave field analysis. The method comprises steps of using wave field analysis to respectively record a first sound field of a recording room and a second sound field of a listening room, adopting a wave domain transformation formula to carry out spatial domain decomposition on the measured first sound filed and the second sound field to obtain signals after first wave domain decomposition and signals after second wave domain decomposition, transmitting signals after first wave domain decomposition to one reconstruction end of the sound field and adopting wave field synthesis to initially reconstruct the sound field recorded by the recording room, adopting single channel inverse filtering to remedy influences of listening room reflection signals on sound fields recorded by the initial recording room to obtain the sound field recorded in the recording room reconstructed finally. According to the system and the method, a broad listening area is provided and the area is not limited to certain multiple listening places, a multi-input multi-output system is decoupled into a plurality of single-input single-output systems via wave domain transformation, and computation complexity is thus reduced.

The invention provides a wind generating set system identification method based on the radial basis function (RBF) neural network technique. The wind generating set system identification method comprises the following steps that 1, data required by system identification are obtained, specifically, the input data and the output data which are required by identification are obtained according to the characteristics of a wind generating set system, the sampling time selects the system internal sampling time, an input signal is the generator torque Tg during torque loop identification and is the paddle pitch angle beta during propeller pitch loop identification, and the output data are the generator rotation speed omega; and 2, system identification is conducted based on the RBF technique, specifically, the wind generating set system is described, a torque loop or a propeller pitch loop is set as a nonlinear SISO system, a nonlinear extension autoregressive East China average model NARMAX is adopted for conducting describing, and the RBF neural network training process comprises the following steps that when a signal is forwards propagated, RBF neural network output is calculated, and when an error is reversely propagated, the weights among various layers of an RBF network are adjusted by adopting the delta learning algorithm. The wind generating set system identification method based on the RBF neural network technique has good operation speed, low calculation amount and good stability.

The invention provides a multimodal extremum search method based on Newton method extremum search. The method is characterized by: for a single input single output system, giving an input start point and performing extremum search for a preset period by using Newton method extremum search; determining whether a local extremum is found by judging a difference value between two close time points in a search ending period; if a local extremum is found, updating the input start point to search for the next local extremum, and otherwise prolonging search time and continuing to search for a local extremum corresponding to the start point. The method extends a Newton method extremum search algorithm, adds an external circle of changing input start points, and finds extremums in the vicinity of various start points by means of the Newton method extremum search algorithm through change of the start points, thereby finishing a process of extremum search for a multimodal function.

The invention discloses an MIMO (multiple input and multiple output) decoupling control method based on SISO (single input and single output) tight-form model-free controller and partial derivative information, comprising: dividing an MIMO system into multiple mutually-coupled SISO systems according to coupling features and tendency features of the MIMO system; controlling the SISO systems via theSISO tight-form model-free controller; by using partial derivative information as input based on a BP (back-propagation) neural network and comprehensively considering minimization of system error function values of all SISO system error contributions as a target, performing system error back-propagation calculating on gradient information of each parameter of the controller to be adjusted via agradient descent method in conjunction with control input, so that parameters of the SISO tight-form model-free controller, such as penalty factor and step factor, are self-adjusted online, and onlinedecoupling of the multiple SISO systems are synchronously achieved. The method provided herein provides good control and is an effective means to solve the MIMO system control problem.

The invention discloses a compressed sensing based channel shortening filter design method. The method includes: firstly, dividing received signals received by a receiving end of a single input single output system into multiple modules; secondly, selecting any one of the modules, computing a cross correlation matrix of the selected module and a module formed by all corresponding symbols in sending signals, and computing an autocorrelation matrix of the selected module; thirdly, according to the acquired cross correlation matrix and autocorrelation matrix as well as set maximum signal-to-noise ratio loss, acquiring an upper bound of mean square error appreciation after the selected module passes a channel shortening filter; finally, determining the channel shortening filter by adopting a reconstruction method in compressed sensing and according to the upper bound of the mean square error appreciation. The method has the advantages that the filter designed by the method is low in computation complexity and high in computation accuracy, computation complexity of an application system can be lowered, and degree of freedom of the application system is increased.

The invention discloses a MIMO (Multiple Input and Multiple Output) decoupling control method based on a SISO (Single Input and Single Output) partial format model-free controller and partial derivative information. According to the coupling characteristics and the tendency characteristics of the MIMO system, the MIMO system is decomposed into multiple mutually-coupled SISO systems, wherein each SISO system adopts an SISO partial format model-free controller for control; and based on a BP neural network, the partial derivative information is used as input, minimization of system error functionvalues of comprehensively considering error contributions of all SISO systems is used as a target, a gradient descent method is adopted, gradient information for each to-be-set parameter of the controller is combined and controlled to be inputted, system error back propagation calculation is carried out, online self-tuning of parameters such as a penalty factor and a step factor of the SISO partial format model-free controller is realized, and online decoupling among multiple SISO systems is synchronously realized. The method put forward in the invention can realize good control effects and is an effective means for solving the control problem of the MIMO system.

The invention relates to a discrete input decoupling device of a six-rotor unmanned aerial vehicle (UAV) and a control system containing the device. The device comprises a coefficient matrix Mco storage module, a structure matrix Mrel storage module, a module which multiplies a coefficient matrix by a structure matrix and stores the product as a mapping matrix Map, a mapping matrix dimension reduction module, a dimension reducing homogeneous linear equation solving module, a basic solution vector normalization module, a differential module, an amplifier gain module, a summation module and a nonlinear resolving module. The device has the following advantage: the all driven six-rotor UAV, a multiple input multiple output system, is decoupled into six single input single output systems, thusrealizing six degrees of freedom independent control of the UAV. The biggest advantages of the device are as follows: after decoupling, the system has simple form and is easy to design control algorithm; the actual rotating speeds of the motors can be quickly calculated by adopting the virtual additional control quantity; and the algorithm has certain robustness toward fluctuation of the rotatingspeeds of the motors.