61 results about "Optimal control algorithm" patented technology

The invention relates to a lithium ion battery remaining useful life (RUL) prediction method based on a fusion algorithm and belongs to the technical field of battery management. The method comprisesthe following steps: S1, acquiring battery capacity attenuation data, and determining parameters of a RUL prediction model based on an optimal control algorithm; S2, fitting data of a training set, iteratively outputting an optimal control algorithm mode parameter filtering estimation value and a battery capacity attenuation data filtering estimation value, and obtaining an initial RUL predicted value by virtue of the model parameter filtering estimated value; S3, based on a difference value between the filtering estimation value of the optimal control algorithm and experimental data, buildingan original error sequence, taking the original error sequence as an input of a neutral network algorithm, performing continuous iteration training on the error sequence, and outputting a predictionresult of the error sequence; and S4, after the data of the training set is used, obtaining a final lithium ion battery RUL prediction result by synthesizing an initial predicted value of the optimalcontrol algorithm and the error sequence prediction result obtained by virtue of the neutral network algorithm.

The invention discloses a mixed flow assembly production scheduling control method based on a bee society self-organization model. The method comprises the following steps of: 1, setting algorithm parameters according to scale of mixed flow assembly production scheduling problems; 2, selecting a random +NEH method for an initialization function aiming at characteristics of the mixed flow assembly production scheduling problems; 3, dynamically adjusting a searching scale in neighboring areas; 4, performing an employment bee algorithm on each employment bee, and triggering a scout bee algorithm to replace the employment bee when the employment bee meets a limit parameter; 5, performing an observation bee algorithm on each observation bee, and triggering the scout bee algorithm to replace the observation bee when the observation bee meets the limit parameter; 6, performing an optimal control algorithm on the employment bee population and observation bee population; and 7, stopping the operation when iteration conditions are met, otherwise repeating the steps from 3 to 7. The method has high speed, high neighboring searching precision, high solution efficiency and good control effect, and local optimum is effectively avoided.

A method for determining a chest pressure profile for cardiopulmonary resuscitation (CPR) includes the steps of representing a hemodynamic circulation model based on a plurality of difference equations for a patient, applying an optimal control (OC) algorithm to the circulation model, and determining a chest pressure profile. The chest pressure profile defines a timing pattern of externally applied pressure to a chest of the patient to maximize blood flow through the patient. A CPR device includes a chest compressor, a controller communicably connected to the chest compressor, and a computer communicably connected to the controller. The computer determines the chest pressure profile by applying an OC algorithm to a hemodynamic circulation model based on the plurality of difference equations.

The invention relates to an active control method and system for milling chattering time delay of a motorized spindle. The method and the system are applied to the motorized spindle comprising an actuating device. The method comprises the steps: inputting vibrating signals acquired from mutually-orthogonal directions of a motorized spindle system, measured motorized spindle system parameters and a cutting force coefficient to a continuous-milling chattering active control state equation containing state time delay; carrying out discretization on the continuous-milling chattering active control state equation, then, calculating optimal active control force for the motorized spindle system by using a discrete optimal control algorithm, and then obtaining a driving voltage which drives a piezoelectric actuator to apply the active control force to the motorized spindle system. By adopting the method or the system provided by the invention, the chattering during milling can be effectively inhibited, a stable region of milling is enlarged, the machining effect is improved, and the machining efficiency is increased.

The invention discloses a grid-connected control system and method for miniature internal combustion engine generator sets. The system comprises a grid-connected controller and a rotation speed regulator ASR, wherein the grid-connected controller is used for carrying out processing of a grid-connected synchronous control algorithm, carrying out processing of an optimum control algorithm after gridconnection, sending a regulation signal obtained via the processing to a voltage regulator AVR and the rotation speed regulator ASR, detecting and comparing whether frequencies, voltage values and voltage phases of a generator set and a mains supply are the same tor not, controlling a grid-connected switch and sending a grid-connected operation signal to the rotation speed regulator ASR; and therotation speed regulator ASR is used for carrying out processing of a traditional rotation speed PID control algorithm on the regulation signal obtained by the grid-connected controller via the processing and the acquired generator rotation speed before grid connection, carrying out processing of a variable gain control algorithm after the grid connection, and using the result obtained via the processing to control a throttle percentage. The system and method are capable of solving the problem that no controllers are designed for switching between grid connection and grid separation in the prior art, and solving the defect that the electric power waves are easy to fluctuate after grid connection.

The invention discloses a concurrent transmission method of a uniform interface test of a power consumption information collection system. The method comprises the following steps: using a sum of a to-be-sent data transmission request amount and a transmission data size in a last period as a to-be-transmitted data request amount in the current period; calculating a load estimation value according to the to-be-transmitted data request amount and the maximum transmission amount of a transmission path; separately calculating an available bandwidth and a congestion degree according to the feedback information of the data request of the transmission data size in the current period; adjusting the to-be-sent data transmission request amount in the next period adaptively and dynamically according to the available bandwidth, the congestion degree and the load estimation value depending on an adjustment strategy; and performing optimization and adjustment on the segmentation threshold of a load factor based on a dynamic plan. The concurrent transmission method has the beneficial effects that the dynamic adjustment of key segmentation threshold of the data transmission request amount based on the optimum control algorithm, and the high efficiency of concurrent processing of test data is ensured.

The invention discloses a catalyst feeding optimal control system and method for a continuous stirred tank reactor. The system comprises a continuous stirred tank reactor, a reactant concentration sensor, a catalyst concentration sensor, an analog to digital converter, a field bus network, a distributed control system, a main control room status display module, a digital-to-analog converter, a catalyst control valve, a coolant control valve end, and a temperature sensor. The reactant concentration sensor and the catalyst concentration sensor acquire the concentration of the material componentsin the reactor in real time. The DCS obtains an optimal control strategy of the catalyst input amount and the coolant input amount in the specified production time range by performing the internal control variable parameterization optimal control algorithm, and converts the optimal control strategy to an opening control command of the catalyst control valve and the coolant control valve to allowthe catalyst control valve and the coolant control valve to perform corresponding actions. The catalyst feeding optimal control system and method minimizes the catalyst and coolant use amount while minimizing the catalyst concentration, the reactant concentration, and the temperature deviation.

The invention discloses an automatic hole punching piling machine control system aiming at complicated terrains, and belongs to the field of building engineering. The automatic hole punching piling machine control system consists of a power distribution cabinet (1), a control cabinet (2), an air compressor (3), a windlass (4), a brake air cylinder (5), a brake operation rod (6), a clutch air cylinder (7), a clutch operation rod (8), an air pipe (9), a height sensor (10), a clamp hammer sensor (11), a pile frame (12) and a pile hammer (13), and is characterized by also comprising a FFT (fast Fourier transform algorithm) conversion system, an excessive rope optimum control algorithm system and an excessive rope expert control system. The automatic hole punching piling machine control system has the advantages that the flexible response to various geological conditions can be realized, in addition, the reliability and the stability of the system are improved, meanwhile, the hammer lifting signal collecting speed is also accelerated, and the operation time of a microcontroller is reduced.

The invention relates to an autonomous balance riding bicycle mechanical power system and a multi-rigid-body dynamic model thereof, the mechanical power system comprises a mechanical system and an electrical control system, and the mechanical system comprises a bicycle body, a rear wheel, a front fork and a front wheel; the electric control system comprises an industrial personal computer, a direct-current power supply and an electronic gyroscope, a front fork tail adjusting device is arranged at the joint of a front fork and the vehicle body, a servo driving motor is arranged on a rear wheel,and a direction adjusting servo driving motor is arranged on the front wheel and connected with the industrial personal computer through a bus; a Kane method is adopted to establish a multi-rigid-body dynamic model of the autonomous balance riding bicycle. The method has the beneficial effects that a reliable theoretical basis is provided for the structure, parameter optimization and control system design of the autonomous balance riding bicycle; an autonomous balance running bicycle state space model is established by means of a multi-rigid-body dynamics model, and autonomous balance runningof the bicycle is achieved based on a cascade stage optimal control algorithm of a speed function.

The invention provides a load balancing method. The method comprises the following steps: step one, acquiring a current value and a voltage value at each of a power source end and a load end; step two, computing the corresponding active factor, inactive factor, power factor and load rate according to the current value and the voltage value; step three, controlling a static var compensator to perform the current compensation according to the power factor; step four, computing the optimal output power through an optimal control algorithm according to the active factor, the inactive factor, the power factor and the load rate; step five, controlling a voltage regulator to output the optimal output power; step six, repeating the steps one to five. The invention further provides a load balancing device and an electricity driver. Through the adoption of the method provided by the invention, the input power of a motor can be dynamically adjusted, the capacity of a transformer is reduced, the required input power of the motor can be automatically matched, the circuit loss is reduced, and the high power factor and the obvious energy-saving effect are realized.

The invention discloses an improved PID optimal control algorithm based on an RBFNN and a BAS. Firstly, aiming at a real-time control system with undefined parameters, an RBFNN model is designed, andonline system parameter identification is carried out; secondly, according to the control requirement of a real-time system, an RBF-PID model based on a local error is designed; rough setting is carried out on PID parameters to obtain a PID parameter range suitable for the system, a BAS-PID model based on ITAE optimization indexes is designed on the basis, and optimal adjustment is carried out onthe PID parameters by using the BAS-PID model to obtain optimal PID parameters. The real-time system with unknown parameters is controlled through the method, and the control effect is better than that of a self-adaptive RBFNN method, a traditional PID method and the like.

The invention provides a hypersonic gliding aircraft linear pseudo-spectrum reentry guidance method and system. The method comprises the steps of: decoupling longitudinal plane motion and transverse plane motion of a target aircraft, and establishing a longitudinal plane dynamic model of the target aircraft; based on a state equation satisfied by the state quantity of a differential flat system, establishing a target linear state equation set which simultaneously satisfies an optimal solution under an optimal control algorithm and a terminal constraint of the differential flat system; solving the target linear state equation set based on a pseudo-spectral discrete method to obtain a control quantity of longitudinal plane motion of the target aircraft; determining a course angle error control quantity of the target aircraft on a transverse motion plane based on a course angle error corridor, and constructing a heeling angle overturning logic based on the course angle error control quantity; and based on the control quantity of the longitudinal plane motion and roll angle overturning logic, guiding the target aircraft. The hypersonic gliding aircraft linear pseudo-spectrum reentry guidance method and system mitigate the technical problems of poor adaptability and low efficiency in the prior art.

The invention relates to an NNs-MRAS-based speed sensorless doubly-fed induction generator LQR control method. A differential algorithm is adopted to design a neural network (NNs) model, the neural network model is trained by a deviation backpropagation algorithm, and thus, a good rotation speed observation ability is achieved. A controller based on a linear quadratic (LQR) optimal control algorithm for stator current under a two-phase synchronous rotating reference frame is designed, the gains are controlled through state feedback, optimal control on the current closed loop parameters is realized, and the dynamic and static performance of the system is improved.

The invention relates to a control algorithm for a pitch of a controllable pitch propeller and a rotating speed of a host machine in a stable navigation state of a ship. The method comprises the following steps that: (1), a thrust P is obtained by a formula; (2), a ship efficiency is obtained by a formula; (3), a current output power W of the ship is obtained by a formula; (4), a control criterion J is obtained by a formula according to the thrust P, the ship efficiency and the current output power W of the ship; (5), a rotating speed n is equally divided into 500 parts and a pitch H is equally divided into 100 parts; and a two-dimensional array is established; when a relationship between W [i] [j] and W(external) satisfies that the W [i] [j] is less than and equal to the W(external) and J [i] [j] reaches a maximum value, the rotating speed n and the pitch H are controlled target values. Beneficial effects of the optimized control algorithm are as follows: a rotating speed n and a pitch H are obtained though an algorithm, so that an optimized control objective including the maximum host output power, the highest fuel efficiency and the best ship maneuvering property is realized.

The invention provides a networked control device and method of a lamination high-frequency vibration fine screen. The device comprises a high-frequency vibration fine screen, an execution module connected with the high-frequency vibration fine screen, a sensor module connected with the high-frequency vibration fine screen, and a control module connected with the sensor module; the execution module is connected with the control module; the high-frequency vibration fine screen is controlled through an embedded ARM microcontroller in the control module; and the embedded ARM microcontroller is lower in system cost and more flexible in design, and can realize the newest and most optimal control algorithm. Through the structure of a networked control system, the control module is separated fromthe vibration fine screen, and the connection is realized through sharing of a communication network to leave from bad scene environment of the vibration fine screen, so that the influence on the controller by disturbance can be prevented, the centralized control of enterprise staff is convenient, the control device is prominently improved, and the enterprise benefit is obviously improved.

The invention discloses a path planning method for an overwater unmanned ship, and relates to the field of path planning. The water unmanned ship path planning method comprises the following steps: constructing a mathematical model of the movement of the water unmanned ship; analyzing an optimization target of the water unmanned ship in path planning; according to the established mathematical model, obtaining dynamics and kinematics models of the unmanned ship, and describing a ship motion law; researching the autonomous obstacle avoidance strategy of the water unmanned ship in the local area; performing optimal control research on global path planning of the water unmanned ship, wherein the global path planning refers to path planning made after all surrounding related environments are known, and the global planning needs to grasp all environment information in a motion space and arrange path planning according to the information; and researching a plurality of global path planning methods, seeking an optimal control algorithm, and finally performing simulation verification on the obstacle avoidance strategy and the path planning algorithm.

The invention provides a missile control strategy determination method and device, a storage medium and electronic equipment, and the determination method comprises the steps: determining the control quantity data of a to-be-analyzed missile system based on an initial control strategy set by the to-be-analyzed missile system; performing iterative solution based on the control quantity data to obtain a first control strategy, and obtaining a reference value function and a reference control strategy based on the first control strategy; updating the first control strategy by using the reference control strategy until the updated control strategy meets a preset control strategy updating condition, and obtaining an optimal control strategy and an optimal value function; and determining an unknown parameter matrix in the to-be-analyzed missile system based on the optimal control strategy, and determining a control strategy for the to-be-analyzed missile system in combination with a parameter equation of the to-be-analyzed missile system. In this way, unknown parameters are determined by combining the optimal control algorithm and utilizing the missile state data, and optimal control over missile trajectory tracking is achieved.

The invention discloses a multi-ship-borne isomer ship surface collaborative trajectory planning and control method based on isomorphism-tracking, and belongs to the technical field of ship surface collaborative planning and control. The method comprises the following steps: firstly, simplifying a rod traction aircraft system into a virtual aircraft system, simplifying a heterogeneous system into an isomorphic system formed by a virtual/taxiing aircraft system, and establishing an optimal control model for multi-isomorphic collaborative trajectory planning; then, solving the model by adopting an optimal control algorithm to obtain standard optimal tracks and control quantities of each virtual aircraft system and each taxiing aircraft system; and finally, enabling each rod traction aircraft system to track the virtual aircraft system standard optimal trajectory constructed according to the rod traction aircraft system, establishing an optimal control model for trajectory tracking of the rod traction aircraft system, and adopting an optimal control algorithm to solve and obtain the trajectory and the control quantity of each rod traction aircraft system. According to the method, the problem of multi-ship-borne isomer collaborative trajectory planning and control can be effectively solved, and the calculation efficiency and robustness are improved.

The invention provides a navigation processing method, device and equipment, and a storage medium. The method comprises the steps of obtaining a preset route track point set; based on the preset routetrack point set, generating a navigation guide line by adopting an optimal control algorithm based on fault-tolerant optimization, the optimal control algorithm based on fault-tolerant optimization being used for carrying out fault-tolerant processing on abnormal route track points in the preset route track point set; and performing navigation processing on the vehicle based on the navigation guide line. When the navigation guide line is generated, fault-tolerant processing is carried out on the abnormal route track points in the preset route track point set, so that the problems that the navigation guide line fails to be generated due to the abnormal route track points and potential safety hazards are brought to vehicle navigation are solved, and the stability and safety of vehicle navigation are improved.

The invention provides an unmanned driving anti-swing positioning method and system based on self-adaptive neural fuzzy control. The method is based on a multi-layer forward neural network and a first-order Sugeno fuzzy model, a fuzzy inference system is established through adaptive modeling, and the neural network technology is used for learning a large number of known data to achieve rapid anti-swing and accurate positioning of unmanned driving. The fuzzy inference system is established by utilizing the self-learning capability of the neural network, the membership function is adjusted and the fuzzy rule is automatically generated according to a data set generated by the optimal control algorithm, and problems of randomness of determination of the membership function of the fuzzy systemand difficulty in extraction of the fuzzy rule are solved. Under the condition that the rope length changes within a small range, the unmanned driving anti-swing positioning method and system based onself-adaptive neural fuzzy control have the advantages of being good in robustness, simple in algorithm, high in anti-swing positioning precision and the like.

The invention provides a method for comparing control efficiencies of a tensegrity structure based on input energy of actuators, and relates to the technical field of structural engineering. The method comprises the steps that form finding of the tensegrity structure is conducted; control algorithms for the tensegrity structure are selected; actuator layout schemes are selected; a common target value of control input energy of all the different control algorithms is determined through trail calculation; a weight coefficient is determined; the time domain and frequency domain dynamic response of the tensegrity structure is obtained; control effects are compared and selected; the actuator layout schemes are replaced, the control efficiency coefficients and frequency response functions of allthe algorithms under the actuator layout scheme are obtained, the control efficiencies of the different actuator layout schemes are compared, and thus the optimal control algorithm and the optimal actuator layout scheme are obtained. According to the method, the control efficiencies of the control algorithms in the time domain and frequency domain can be well compared, the control efficiencies ofthe different control algorithms can be compared, the control efficiencies of the different actuator layouts and different numbers of the actuators are obtained, and support is provided for selectionof the actuator layouts and the actuator number.

The invention discloses a humanoid robot motion planning parameter optimization method based on a FPGA. The method is characterized by comprising the steps that a fixed-point model of humanoid robot motion planning parameters is established; and a reconfigurable computing system structure is designed according to the fixed-point model, and the coarse and fine granularity reconfigurable unit speed-up ratio is provided. An algorithm model is optimized according to the characteristics of a FPGA platform so that computing hardware resources can be saved, hardware working speed can be enhanced and the humanoid robot motion planning parameters are enabled to have the optimal control algorithm.