127 results about "Linear quadratic" patented technology

The invention relates to a methods and systems for determining an insulin dosing recommendation. The invention employs Linear Quadratic methodology to determine the insulin dosing recommendation based on a patient's present physiological state, which is estimated by an adaptive filter methodology employing a dynamic model, which utilizes real-time measurements of blood glucose concentration.

The invention belongs to the technical field of vehicle intelligent aided driving and vehicle safety, and particularly relates to a self-adaptive cruise system which changes system self-adaptive cruise vehicle following performance by learning driver style behaviors online and has driving style learning capacity and an implementation method. The self-adaptive cruise system with the driving style learning capacity and the implementation method are designed for solving vehicle self-adaptive cruise control problems. The system is applicable to L2 automatic drive vehicles, and aims at achieving the purpose of self-adaptively following a vehicle in front in an actual driving scene through environment perception and information fusion; meanwhile, driving styles of specific drivers are consideredin a driving strategy of the system, so that the system has consistent satisfaction degree and acceptability for different people. To achieve the purpose, a mode of combining a linear quadratic typecontrol method and a reinforcement learning online learning method is adopted for better optimizing the system performance.

The invention provides an inertial system spacecraft attitude control/angular momentum management method including four steps. The invention aims to solve the problems of control moment gyro angular momentum accumulation caused by gravitation gradient moment and other interference moments in an inertial system, the gravitation gradient moment is adopted to balance the gestures, and a space station angular momentum management controller based on pole assignment is designed. A space station linear model is established under the inertial system, the infeasibility of the inertial system angular momentum management in the pitch axis direction is analyzed, the pitch axis is decoupled from a rolling/yaw axis, and the CMG angular momentum in the pitch axis direction is not restrained, constant disturbance, disturbance being one-time of the track frequency, and disturbance being twice of the track frequency are brought into a state equation to suppress the influence to the pitch axis gestures, and a linear quadratic algorithm based on pole assignment is adopted to solve a feedback gain matrix. The algorithm prevents the selection of cost matrix Q, and based on the requirement of the system performance, the closed-loop poles can be configured to a specified area at the left side of a complex plane imaginary axis, and at the end, the feasibility of the algorithm is verified by the simulation results.

The invention discloses a multi-zone automatic generation control coordination method based on the differential game theory. The method comprises the following steps: step 1, a dynamic model of zone interconnected network automatic generation control (AGC) is established; step 2, traditional AGC amount based on a proportion integration link is replaced by AGC amount based on the differential game theory and a coordination control model, based on the differential game theory, of zone interconnected network automatic generation is established; step 3, the coordination control model of the zone interconnected network automatic generation is solved through the linear quadratic type differential game theory and the obtained Nash equilibrium strategy serves as automatic generation control amount of multiple zones; and step 4, compared with other existing control methods, the multi-zone automatic generation control coordination method based on the differential game theory enables distribution of frequency modulation among the zones to be fair and convictive. The multi-zone automatic generation control coordination method based on the differential game theory has the advantages of being strong in robustness and the like.

Two new adaptive homing guidance laws are developed which are variants of Augmented Proportional Navigation (PRONAV). The first guidance law commands flight path angle rate and is referred to as adaptive matched augmented PRONAV (AMAAP). The second guidance law commands linear acceleration and is referred to as adaptive matched augmented linear PRONAV (AMALP). The major attributes of these guidance laws are (1) they are the solutions of a linear quadratic control problem, (2) they do not require an estimate of time-to-go (t.sub.go), (3) they are matched to a nonlinear model of the target's motion, (4) they adapt in real time to provide optimal guidance over each small segment of the intercept trajectory, and (5) they optimally account for missile deceleration.

The invention relates to an observability constraint-based random planet landing track optimizing method, and belongs to the technical field of the deep space probe navigation and guidance. According to the method, a deep space landing guidance control task based on the monocular vision navigation is used as the background, the dual problem between the effective control and the reliable estimation is considered, the system uncertainty is used as partial cost and is introduced into a quadratic performance index through an expansion-state space, so that a random optimization feedback control law can be provided by adopting a linear quadratic type control technique, an expansion-state space description model of a established probe system is substituted, the real-time optimization of a planet landing track is realized. The dynamic planning and the burden in calculation based on a searching method are avoided, the problem of observability shortage in the landing process is effectively overcome, and the navigation estimation performance of the system is improved, so that the overall performance during the planet probe navigation and guidance control is ensured, and the final target that a planet is reliably landed is achieved.

The invention discloses an on-line support vector machine (SVM)-based building structure earthquake response intelligent control design method, which is implemented by the steps of: 1, selecting a structural model, acquiring earthquake wave, performing earthquake response analysis on the structure, substituting in an LQG (Linear Quadratic Gaussian) controller, and calculating required optimal active control force; 2, arranging a plurality of MR (Magnetic Resonance) dampers for each floor of the structure according to a predetermined control level, determining MR damper parameters by taking the optimal active control force as target force and designing a structural LQG MR damper control system; and 3, estalibhsing a core module of a structure-SA (Semi-Active)-SVM-MR damper intelligent control system, and executing learning, training, prediction and control functions of on-line SVM. Numerical verification shows that the intelligent control system is more effective than the LQG MR damper control system. According to the method, the problem of poor structure acceleration response control effect or amplification of the LQG MR damper control system is solved, and a better control effect on structure acceleration response is achieved; and along with increasing floors of the structure, the intelligent control system has more obvious control advantage for the structure acceleration response.

The invention belongs to the technical field of engine air inlet systems, and relates to a fuel cell engine air inlet system control method based on map and linear quadratic model. The purpose is to control the peroxy ratio and the cathode pressure of a fuel cell stack, so that the fuel cell engine has good dynamic property and quick response capability. The method comprises the steps of firstly,modeling a fuel cell engine air inlet system; building the models of a compressor, an intake manifold and a stack cathode, secondly, calculating state balance points and steady-state control quantityunder various working conditions, and using linear quadratic form optimal control to design state feedback gain of a model after linearization of the fuel cell engine air inlet system under various working conditions; and finally, calibrating the feed-forward steady-state control quantity and the feedback gain by using the map, and designing a feed-forward and feedback controller. In order to verify the effectiveness of the controller, a simulation model is built in MATLAB/Simulink for verification.

A mobile robot visual servo trajectory tracking predictive control method based on a primal-dual neural network comprises the following steps: 1) building a mobile robot kinematical model; 2) fixing acamera on a ceiling, so that the camera can obtain global visual information, and building a visual servo mobile robot error model; 3) according to the error model, obtaining a prediction equation and defining a predictive control performance index; and 4) establishing a performance index minimization problem as a minimization problem based on the primal-dual neural network, and solving controller gain by combining a primal-dual neural network module in Matlab-Simulink, so that a trajectory tracking task is completed. The method provided by the invention transforms a problem into a multi-constrained linear quadratic programming problem and quickly finds optimal solution by utilizing a PDNN.

The invention provides an automatic driving vehicle transverse motion control method and device and an automatic driving vehicle. The automatic driving vehicle transverse motion control method comprises the steps: setting control parameters of a linear quadratic controller; obtaining vehicle overall parameters; according to the control parameters and the vehicle overall parameters, acquiring a control parameter gain; according to control parameter gain, acquiring a real-time control parameter gain; acquiring a state error feedback quantity, a track curvature and a vehicle inclination angle; acquiring a control quantity and a compensation quantity according to the real-time control parameter gain, the state error feedback quantity, the track curvature and the vehicle inclination angle; acquiring a steering wheel expected angle according to the control quantity and the compensation quantity; and outputting the steering wheel expected angle to a steer-by-wire system. According to the method, the transverse motion static-error-free optimal control of the automatic driving vehicle can be realized, the calculated amount is greatly reduced, the convergence of the optimal control gain is ensured, and the expected driving track is tracked with high reliability and high precision.

A ducted unmanned aerial vehicle anti-sway method based on optimized quadratic form control of artificial bee colony includes eight steps: 1, the mathematical model for pendulum oscillation is built; 2, control structure and control law are designed; 3, the parameters of the artificial bee colony algorithm and the employed bee colony are initialized; 4, the performance indicator function of the linear quadratic form is calculated according to individual parameters; 5, worker bees select bee individuals with better fitness as leading bees according to the fitness value of each employed bee, and each worker bee continues to seek for honey sources near the leading bee solution space and the fitness value is calculated; 6, if the number of searches Bas is greater than the set threshold, the employed bees seek for new honey sources again, namely parameter values are initialized again; 7, by the greedy selection method, the positions of the employed bees are updated with larger fitness values, and searches proceed near solution spaces; and 8, the Step 4 is carried out repeatedly until T > Tmax, and the optimum component weighted value parameter, the optimum feedback gain matrix and the optimum fitness value are output.

The invention relates to a transverse control method for an automatic driving truck, and the method comprises the following steps: S100, receiving an input reference track, finding a track point closest to the truck, and calculating a tracking error; S200, the tracking error serving as a state variable of the linear quadratic regulator to be input into an LQR closed-loop feedback controller, and obtaining output of a linear quadratic regulator controller; inputting the reference track into a model reference self-adaptive controller to obtain model reference self-adaptive controller output; s300, combining the output of the linear quadratic regulator controller and the output of the model reference adaptive controller to obtain a steering wheel instruction, and sending the steering wheel instruction to a drive-by-wire system of the truck; and S400, cycling the steps S100-S300, so that the output of the truck is consistent with the expected output. The invention further provides a transverse control system of the automatic driving truck. Through LQR+MRAC, the robustness of the control algorithm can be greatly improved, so that the truck still has good stability under different loadsand special working conditions.

Two linear quadratic tracking controllers and a minimal prototype controller are presented for the control of a discrete single input and single output (SISO) tracking control system. The minimal prototype controller is an unconstrained controller. Depending on the models of the set point and the plant transfer function, this controller might be desirable. But usually one would choose one of the two linear quadratic controllers which minimize the sum of squared errors between the output and the set point variables with a penalty on that of the input variable. The one degree of freedom (1-DOF) controller performs well, but for nonminimum phase systems the two and a half degrees of freedom (2.5-DOF) controller is the stronger one as it can suppress the inverse response of a non-minimum phase system. The 1-DOF controller gives the stochastic regulating controller counterpart known as the linear quadratic Gaussian controller. A digital control chip for implementation of the controllers is also disclosed.

The invention relates to development of a robust controller for adjusting concentration equilibrium of CO2 and O2 in a small closed artificial ecosystem. Firstly, the simulation model of the robust controller of the gases is established based on relevant mechanisms and properties of controlled objects, secondly, the feasibility of the structure and the parameters of the algorithmic model is preliminarily studied by the method of completely digital simulation and finally, the real-time simulation experiment is carried out to check the actual effect of the controller. The sensor can be calibrated with the measured value of the other sensor under the condition that one sensor fails to realize robust fault-tolerant control by designing monitoring logic of a finite-state machine and learning and predicting an artificial neural network. The controlled light intensity is computed by the linear quadratic Gaussian algorithm, thus effectively affecting the growth rate of the microalgae in the artificial ecosystem, directly achieving the aim of adjusting the concentration of CO2 and O2 and ensuring the concentration to be steadily balanced in the set range and have good dynamic response property.

A state observer for a steam generator of a thermal power plant is provided. Accordingly, provision is made for the state observer to be a multi-variable state observer which has a Kalman filter designed for linear-quadratic state feedback. The state observer can be used for validating measured variables of the steam generator of the thermal power plant, wherein measured variables of the steam generator are compared with output variables of the state observer.

The invention discloses a mechanical arm autonomous calibration method based on vision measurement. The method comprises the following steps that step 1, an unsteady-state multi-sensor mechanical armvision system is constructed; step 2, a calibration model is established according to a Gaussian motion method; step 3, multiple identification points are measured according to extended Kalman filtering; step 4, a motion trail is corrected according to a linear quadratic form regulator; step 5, an optimal measurement point is screened based on a Monte Carlo method; and step 6, model parameters areapproximated by adopting a DH augmentation model. According to the method, through an EKF algorithm filtering process, an LQR method correction process and a calibration data preferred screening process based on error distribution, the optimal calibration precision can be obtained under the condition that mechanical arm motion errors and measurement errors exist at the same time; and moreover, the method is low in cost, high in efficiency and relatively convenient, and can be widely applied to long-term and frequent calibration and maintenance of mechanical arm equipment.

The invention discloses a definition method for an initial gesture of a marine optical fiber gyro strapdown system, comprises first, preparing preheat for a SINS, second, adjusting the SINS to enter into a rough alignment period for an initial alignment after the preheating preparation of the SINS is finished, collecting a marine gyroscope output and an accelerometer output, calculating three error misalignment angle phi xn, phi yn, and phi zn between a geographic coordinate system and a real geographic coordinate system through a rough initial strapdown gesture matrix which is obtained after the rough alignment is finished, entering into an extractive alignment when the three error misalignment angle are less than 10 degree, if not, the rough alignment is need to be renewed, third, the extractive alignment, continuously collecting the marine gyroscope output and the accelerometer output on the basis of the rough alignment, adopting an optimal control technique of a linear quadratic form LQ, and obtaining optimal correcting controlling angle speed which is needed in the process of the extractive alignment. The invention seeks a tradeoff between time and aligning accuracy, the aligning accuracy of an initial gesture resolving proposal is equal to a traditional proposal, but aligning time and convergence speed are greatly increased.

A rational function for the transfer function model of a multivariable discrete control system is suggested and its controllers are obtained. There are two types of control systems depending on the nature of the disturbance. For tracking control systems, the disturbance is a set of set point changes. For regulating control systems, the disturbance is a vector ARIMA time series. The quadratic performance controllers for these systems are similar but opposite in nature. For tracking control systems, a two and a half degrees of freedom controller can be designed for an enhanced quadratic performance. This controller uses the future values of the disturbance which are the set points of the control system for further reduction of the error. The controller is particularly useful for nonminimum phase tracking control systems.

The invention discloses a control method for piston motion track of a free piston engine, and belongs to the technical field of control. The invention aims to provide the control method for the piston motion track of the free piston engine, and the control method establishes a free piston internal combustion engine generator mechanism model system under an MATLAB environment according to the working mechanism of the free piston internal combustion engine generator, can effectively compensate interferences and keeps stable operation of the free piston internal combustion engine generator. The control method comprises the following steps of: establishing a free piston electric generator simulation model; controlling piston track of the free piston electric generator; enabling track of the piston to trace reference track, wherein the reference track is that a FPEG works under load needed for a driver; establishing a control-oriented model; designing a quadric-form secondary optimal controller; expanding design of a state observer; and performing uncertainty compensation. According to the control method disclosed by the invention, a control-oriented simplified model of the system is established, a piston motion control method based on linear quadratic type (LRQ) and extended state observer (ESO) is disclosed, and piston motion track of EPEG is controlled by regulating circulating oil spray amount.

The invention discloses a linear quadratic type optimal dynamic feedforward-feedback PID control system based on a closed-loop identification model and a control method thereof. The method comprises the following steps of sampling field closed-loop operation data, identifying an ARX model in a closed-loop manner, and converting the ARX model into a discrete time state space model capable of observing a standard shape, and obtaining a measurable disturbance quantity feedforward control model; designing a quadratic type performance index; minimizing the performance index to obtain a linear statefeedback control matrix; calculating the state quantity estimation of the measurable disturbance quantity, and further obtaining a feedforward control law of the linear optimal quadratic type dynamicfeedforward controller; and combining the linear quadratic type optimal dynamic feedforward controller with a PID controller to design a feedforward-feedback PID control system. The control method disclosed by the invention is suitable for the dynamic feedforward design of a non-minimum phase system; the feedforward control law is designed by utilizing the quadratic type performance index, and agood and flexible feedforward control law can be obtained. By combining with an industrial field PID control system, the change on the field control strategy is small, and the method has good application prospect.