1801 results about "State observer" patented technology

The invention relates to the technical field of numerical control machine tools, and discloses a self-adaptive error compensation method and system for a high-precision numerical control machine tool, and the method comprises the steps: carrying out the mathematical modeling of a multi-dimensional error of a five-axis numerical control machine tool, and obtaining a thermal deformation displacement vector, a friction force vector and a path deviation vector; inputting into a multi-dimensional expansion state observer for error observation to obtain thermal deformation, a friction force value and a path error value; performing trust domain parameter optimization to obtain a thermal deformation compensation gain matrix, a friction force pre-compensation coefficient matrix and a path error compensation coefficient matrix; performing three-stage series compensation calculation to obtain a compensation position instruction, a compensation speed instruction and a compensation acceleration instruction; and track reconstruction operation is carried out to generate a position instruction sequence, a speed instruction sequence and an acceleration instruction sequence of each axis, so that self-adaptive error compensation of the high-precision numerical control machine tool is realized, and the machining precision of the high-precision numerical control machine tool is improved.

The invention discloses an integral type fast nonsingular self-adaptive super-spiral sliding mode control method for an energy storage converter, provides a solution for the problem of low accuracy of a traditional interference state observer, and designs a super-spiral interference observer. A superhelix algorithm is adopted to accurately estimate disturbance and uncertainty information of external changes and internal parameters of the energy storage converter system. Secondly, a finite time observer is adopted to accurately observe the output current of an inverter system, an integral type fast nonsingular self-adaptive super-spiral sliding mode control method is adopted, the controller weakens the buffeting problem, the control gain parameter design of the super-spiral sliding mode control algorithm depends on interference and uncertain boundary information, and the control gain parameter design of the super-spiral sliding mode control algorithm depends on the uncertain boundary information. The information is relatively difficult to obtain in the actual situation, and the adaptive gain can enable the control gain to be adaptively adjusted so as to ensure the stability and robustness of the system.

The invention provides an automatic energy-saving control method and device for a ring cooling fan based on load feedback, relates to the field of ring cooling fans, and solves the technical problem of delay of regulation and control in an energy-saving working state. The method comprises the steps that working condition data are input into a preset powder box model, and a feed-forward air volume instruction is obtained through calculation; and inputting the working condition data into a state observer to obtain an optimal estimated temperature value. And the deviation between the optimal estimated temperature value and a preset temperature set value is calculated, and a feedback air volume compensation instruction is obtained through calculation of a feedback controller according to the deviation. And fusing the feed-forward air volume instruction and the feedback air volume compensation instruction to obtain a final air volume control instruction, and issuing the final air volume control instruction to a fan frequency converter for execution. And continuously monitoring the numerical value and the change trend of the feedback air volume compensation instruction, taking the feedback air volume compensation instruction as a prediction error signal of the powder box model, and adaptively adjusting key thermal parameters in the powder box model. The method is used in the control process of the ring cooling fan.

The invention relates to a model predictive control charging optimization method based on a dynamic power state, which initiates a'dynamic power state collaborative optimization 'mechanism, takes a real-time power upper limit as an active optimization target instead of a fixed constraint condition, and breaks through the technical bottleneck of power limitation passive response in a traditional charging strategy. The method specifically comprises the following steps: constructing an electric-thermal-aging multi-physics field coupling model of the lithium ion battery, updating electric-thermal characteristic parameters in real time through an online parameter identification algorithm, and synchronously estimating a core temperature and an aging state in combination with a double-Kalman filtering state observer; innovatively establishing a four-dimensional objective function optimization model containing a dynamic power state, and performing multi-objective collaborative optimization on a power upper limit, a charging speed, a capacity fading rate and a current fluctuation rate; and designing a dynamic rolling optimization algorithm based on a model prediction control framework, and solving the optimal charging current meeting the dynamic power distribution requirement of the power grid in real time under the hard constraint of ensuring the maximum core temperature and terminal voltage.

The invention discloses a virtual marshalling multi-train cooperative adaptive sliding mode control method based on an extended state observer, and the method comprises the steps: firstly constructing an urban rail multi-train tracking error dynamic model based on a unit train dynamic equation; secondly, establishing a nonsingular terminal sliding mode surface according to the urban rail multi-train tracking error dynamical model to obtain an equivalent control law, combining the equivalent control law with a switching control law to obtain a nonsingular terminal sliding mode control law, and introducing a gain adaptive law and a saturation function into the nonsingular terminal sliding mode control law to obtain an adaptive nonsingular terminal sliding mode control law; and finally, an extended state observer is adopted to estimate external interference, an observation value of the interference is added to the output of the adaptive nonsingular terminal sliding mode controller to serve as feed-forward compensation, and the adaptive nonsingular terminal sliding mode control method based on the extended state observer is constructed. According to the method, the multi-train cooperative operation tracking control precision and stability can be remarkably improved under the external interference condition.

The invention relates to the technical field of motor control, and discloses a hybrid excitation synchronous motor control strategy optimization method and device. The method comprises the following steps: performing mathematical modeling on permanent magnet flux linkage, exciting current and rotor parameters of the hybrid excitation synchronous motor to obtain a state observer equation; collecting current parameters and position parameters, and performing filtering processing to obtain motor operation state parameters; inputting a five-layer deep neural network for current and rotating speed parameter prediction to obtain an optimal current parameter and an optimal rotating speed prediction parameter; constructing a multi-objective function, and solving to obtain a current reference value; inputting the current reference value into a cascade PI controller, and performing voltage regulation through feedforward decoupling control and a space vector pulse width modulation technology to obtain a control voltage signal; and performing performance calculation control parameter optimization on the control voltage signal to obtain a target control parameter, thereby improving the control precision of the hybrid excitation synchronous motor.

The invention relates to a micro-grid intelligent safety secondary voltage control method based on reinforcement learning, and belongs to the technical field of power grids. The method comprises the following steps: firstly, establishing a micro-grid secondary control model under hybrid network attack; a DoS attack defense network based on deep learning is designed, a self-adaptive FDI attack compensation state observer is designed, compensation for unknown FDI attacks is established, a self-adaptive law of compensation signals is designed, and estimation of the system state under network attacks is achieved. An evaluation-execution structure is constructed based on reinforcement learning, a virtual optimal controller and an actual optimal controller are designed in combination with a backstepping method, unknown parts in a system model, an evaluation network and an execution network are approximated by using a neural network, and a weight adjustment law is given. And introducing a log type barrier function into the performance index function, and constraining the output in a fixed constant interval to meet the constraint condition. The method can cope with DoS attacks and FDI attacks, and ensures stable control and safe operation of the secondary voltage of the micro-grid.

The invention provides an unmanned aerial vehicle motor rotating speed control method based on active disturbance rejection. The method comprises the following steps: 1) measuring the rotating speed of a motor by adopting a high-precision rotating speed sensor based on a quantum effect; 2) designing a tracking differentiator TD to smooth an expected rotating speed, and outputting a rotating speed tracking signal and a rotating speed tracking signal change rate; 3) introducing a dynamic weight matrix to form a dynamic weight expansion state observer DWESO, and taking an output state variable estimation value and a total disturbance estimation value as the input of the NLSEF; 4) automatically searching the optimal combination of the gain parameters of the DWESO by adopting an ALA (artificial Louver Mouse Algorithm), so that the optimal state variable estimation value and the optimal total disturbance estimation value are output to the NLSEF; compared with the prior art, the method for controlling the rotating speed of the unmanned aerial vehicle has the advantages that the dynamic response speed, the anti-jamming capability and the parameter adaptability of the system are remarkably improved, and the flight performance and the robustness of the unmanned aerial vehicle are improved.

The invention relates to the technical field of dynamic models, in particular to an elevator dynamic model correction system and correction method. The method comprises the following steps that elevator system basic data and elevator historical operation data are obtained; performing multi-scale dynamic characteristic analysis according to the elevator system basic data to generate multi-scale dynamic characteristic data; performing multi-scale stability analysis on the multi-scale dynamic characteristic data according to the historical operation data of the elevator so as to obtain multi-scale stability data; subsystem coupling sensitivity analysis is conducted on the multi-scale stability data according to structure parameters in the elevator system basic data, and therefore multi-scale coupling sensitivity data is generated; and performing global nonlinear characteristic mapping processing according to the multi-scale coupling sensitivity data to obtain a global nonlinear dynamic model. By constructing the extended state observer based on the high-frequency vibration mode, the state which is difficult to directly measure can be estimated, and the comprehensiveness and accuracy of system monitoring are improved.

The invention discloses a multi-agent robust specified time state estimation method based on discrete continuous mixing, and belongs to the field of distributed state estimation of an agent system, and the method comprises the following steps: S1, analyzing the uncertainty of a multi-agent system and a measurement noise model, and building a system dynamic equation; s2, designing a transformation matrix based on a null space and a system dynamic equation, and constructing a multi-agent system consistency error; s3, constructing a state space equation of the state observer based on the consistency error of the multi-agent system; and S4, based on the state space equation of the state observer, realizing specified time convergence of the estimation error through the power return-to-zero characteristic of the power zero matrix. According to the multi-agent robust specified time state estimation method based on discrete continuous mixing, state estimation is carried out only by using relative output information between neighbors without depending on relative input information between the neighbors, use of communication channels is avoided, and the method has the characteristic of network attack immunity.

Disclosed in the present invention is an output feedback control method for a pilot-operated electro-hydraulic proportional servo valve considering disturbance suppression. According to the control method, a nonlinear active disturbance rejection controller with both disturbance suppression and unknown state estimation is designed on the basis of a constructed disturbance observer in combination with an extended state observer. To address the problem of a valve core position control system of the pilot-operated electro-hydraulic proportional servo valve, the present invention not only ensures suppression of matched interference in the system, but also compensates for mismatched interference in the system, and utilizes a state observer to estimate unmeasurable state variables, so as to construct full-state feedback control, thereby ultimately achieving high-precision tracking control of the valve core position.

The invention belongs to the technical field of parallel robot controllers, and discloses a high-performance parallel robot controller based on an arm + fpga architecture, through deep heterogeneous fusion of an ARM and an FPGA, the control period is shortened to be within 10 microseconds, the trajectory tracking error is controlled to be 0.1 mm or below, and the performance bottleneck of a traditional architecture in a high-speed scene is solved; the multi-core ARM undertakes complex tasks such as global trajectory planning and dynamics solution, and realizes parallel processing by means of an NEON instruction set; the FPGA fully releases the hardware parallel characteristic of the FPGA, real-time tasks such as multi-axis motion control and sensor data fusion are synchronously completed through a distributed logic unit, and a complex decision-real-time execution assembly line cooperation mode is formed. Inertial parameters and load changes of the mechanical arm are estimated in real time through an LSTM neural network, and feedforward compensation is carried out on interference such as mechanical vibration and load abrupt change in combination with an extended state observer achieved through FPGA hardware; the innovatively designed double closed-loop control architecture supports seamless switching between a force control mode and a position control mode.

The invention discloses a multi-unmanned-ship cooperative target tracking game control method, and relates to the field of unmanned-ship cooperative tracking control, and the method comprises the steps: obtaining an estimation value of an unmanned ship after the offset of a tracking target through building a preset-time target state observer, obtaining a reference signal of the unmanned ship through a preset-time guidance law, and obtaining a target state estimation value of the unmanned ship; obtaining a speed error vector of the auxiliary system considering compensation input saturation; and then obtaining an optimal control law of the unmanned ships through the established optimal cost function, and obtaining an approximation optimal control law satisfying Nash equilibrium based on an adaptive law of the evaluation network, thereby realizing control of cooperative target tracking of the multiple unmanned ships. Through the establishment of the predetermined time guidance law, the problem of relatively long convergence time is solved, and the dependence of the convergence time on control parameters is reduced. And meanwhile, the influence of neighbor members in the formation is fully considered, a solution meeting Nash equilibrium is obtained by adopting an evaluation network, and the multi-unmanned ship Nash game problem of a nonlinear continuous time system with unknown interference is solved.

The invention discloses a mechanical arm specified performance high-precision trajectory control method based on an improved super-torsion expansion state observer. The mechanical arm specified performance high-precision trajectory control method comprises the following steps that a dynamic model of an n-joint mechanical arm is established; the kinetic model of the n-joint mechanical arm is re-described as a mechanical arm kinetic model based on total disturbance; an improved super-torsion expansion state observer is designed to estimate the total disturbance in the mechanical arm dynamic model based on the total disturbance; and according to the equivalent control law, the switching control law and the total disturbance estimation value, a recursive integral sliding mode controller based on funnel error transformation is constructed, and trajectory tracking of the mechanical arm is achieved. According to the method, the convergence speed of the system can be effectively improved, the buffeting phenomenon in the system can be effectively inhibited, and meanwhile, the method has good anti-interference performance.

The invention relates to the technical field of trajectory tracking control of piezoelectric motion tables, and discloses a trajectory tracking control method and device for a piezoelectric console, and the method comprises the steps: constructing an initial dynamic model of a piezoelectric motion table based on an asymmetric Bouc-Wen hysteresis model, and obtaining a to-be-identified parameter set; based on the root-mean-square error between the actual output displacement of the piezoelectric motion platform at the plurality of sampling time points and the predicted output displacement of the initial dynamical model, constructing a self-adaptation function of the parameter set to be identified; identifying and acquiring a target model parameter set by using a multi-modal Bayesian gradient optimization algorithm and taking the value convergence of the self-adaption function as an optimization target to obtain a target dynamic model; based on the target dynamic model, constructing a hysteresis state observer, and obtaining feed-forward compensation voltage; constructing a self-adaptive fuzzy PID feedback controller, and obtaining a feedback control voltage; and summing the feedforward compensation voltage and the feedback control voltage to generate a driving voltage so as to drive the piezoelectric motion table to perform trajectory tracking.

The invention discloses a prepreg tape tension detection method and device based on an extended state observer and a medium, and the method comprises the steps: carrying out the kinetic analysis of an unreeling shaft of an automatic tape laying machine, and constructing a tension model; converting the tension model into a state-space equation, and constructing a tension state observer according to the state-space equation; optimizing the tension state observer through a genetic algorithm based on an error between a tension estimated value output by the tension observer and a tension target value; the current corresponding to the unwinding torque, the real-time radius of the unwinding shaft and the conveying speed of the unwinding shaft are obtained and input into the optimized tension state observer, and a tension estimation value is obtained; the tension estimation value is decoupled through a controller to obtain a control signal, and the unwinding torque is controlled through the control signal; inputting the unwinding torque into a tension model to obtain an actual tension value; and setting a Lyapunov function, and judging whether the actual tension value is accurate or not through the Lyapunov function.

The invention provides a satellite attitude control system fault diagnosis and fault-tolerant reconstruction method and system, and relates to the technical field of satellites, and the method comprises the steps: obtaining attitude data through a Kalman filtering state observer, building a fault diagnosis model, generating a residual sequence, and carrying out the adaptive dynamic threshold calculation to obtain a fault feature vector; and inputting the feature vector into a pre-trained deep belief network for fault diagnosis, and determining the fault type and degree. According to a diagnosis result, a mixed integer programming model considering attitude control precision and actuator power constraint is established, an improved genetic algorithm is adopted for solving, an actuator reconstruction scheme and controller parameters are obtained, and fault-tolerant control is achieved. According to the invention, faults can be diagnosed rapidly and accurately, fault-tolerant reconstruction is carried out according to fault types and degrees, the reliability and stability of a satellite attitude control system are effectively improved, and the satellite attitude control precision is ensured.

The invention discloses a wide-speed-domain position-sensorless control method for a permanent magnet synchronous motor, and the method comprises the steps: building an extended state observer of the permanent magnet synchronous motor, and obtaining the counter electromotive force of the motor through the extended state observer; a self-adaptive vector filter is adopted to filter out higher harmonics in the back electromotive force obtained by the extended state observer, estimated back electromotive force is obtained, the obtained estimated back electromotive force serves as input, position information contained in the estimated back electromotive force is demodulated through a phase-locked loop position observer, and the rotating speed and the position angle of the motor are obtained; and controlling the permanent magnet synchronous motor according to the obtained rotating speed and position angle. The position observer is used for extracting position information from the rotor back electromotive force, a mechanical position sensor is omitted, the system structure is simplified, cost is reduced, the self-adaptive vector filter is used for filtering harmonic waves for estimating the back electromotive force, and estimation errors of the rotating speed and the position angle of the motor are reduced. And the high efficiency and the stability of position-sensorless control of the motor in a wide speed range are improved.

The invention discloses a vehicle stability adaptive control method under low attachment road surface multi-source interference, and belongs to the field of vehicle control, and the method comprises the following steps: S1, multi-source interference perception and attachment coefficient prediction; s2, dynamic correction of tire dynamic parameters: correcting tire cornering stiffness and slippage stiffness on line; s3, multi-source interference collaborative observation and estimation: dynamically estimating an interference source by using an enhanced extended state observer; s4, phase plane stability envelope analysis and weight adjustment: dynamically allocating control priorities; and S5, on the premise of considering an interference source, performing dynamic torque distribution and actuator cooperative control: optimizing four-wheel torque by using a quadratic programming algorithm to obtain a torque distribution result. By adopting the vehicle stability adaptive control method under the low-attached road surface multi-source interference, the problems of insufficient modeling precision, weak interference suppression, target conflict and redundancy deficiency in low-attached road surface vehicle stability control are solved, and the trajectory tracking precision and the yaw stability are remarkably improved.

The invention belongs to the field of cooperative control of a multi-agent system, and the method aims at a fully heterogeneous linear multi-agent system under a directed topological graph, takes event-triggered communication transmission as a background, and aims at realizing stable formation control on the premise of utilizing a fully distributed control structure. And the formation control problem of the fully heterogeneous multi-agent system based on the mixed event triggering mechanism is researched. According to the method, a mixed event trigger communication strategy is used, network transmission bandwidth occupation can be reduced, and data transmission energy consumption is saved; designing a local state observer and a distributed event trigger state observer to estimate the states of the followers and the leader according to the conditions that the states of the followers are unknown and communication links do not exist between the leader and part of the followers; the designed distributed formation control protocol does not depend on global information, can ensure that followers realize ideal time-varying output formation configuration in a dynamic environment, and can accurately track a motion trail formed by a plurality of leaders at the same time.

The invention discloses a decoupling control method and system for a matrix motor with harmonic suppression capability, and belongs to the technical field of motor driving systems, and the method comprises the steps: building a matrix motor current loop mathematical model which considers a DC disturbance term and an AC disturbance term at the same time; based on the matrix motor current loop mathematical model, establishing a self-adaptive quasi-resonance extended state observer which simultaneously considers direct current disturbance observation and alternating current disturbance observation and performs self-adaptive adjustment on control parameters; the direct current and alternating current lumped disturbance of a matrix motor current loop is observed in real time through an adaptive quasi-resonance extended state observer; compensating the observed direct current and alternating current lumped disturbance in a forward controller of the current loop and obtaining a voltage control quantity; and controlling the matrix motor through a voltage vector space transformation and SVPWM modulation method according to the voltage control quantity. The method is improved and optimized based on an existing matrix motor vector control system, and the system does not need to be modified on a large scale.

The invention discloses a constant force control method and system for a multi-joint flexible mechanical arm, and belongs to the technical field of robots. The method specifically comprises the steps that through a force sensor installed at the tail end of the flexible mechanical arm, the difference value of contact force between the tail end of the flexible mechanical arm and the environment and expected force serves as a force error, and the difference value of the change rates of the contact force and the expected force serves as the force error change rate; calculating a damping coefficient and a corresponding stiffness coefficient variable quantity; an impedance control model is constructed and solved, and an expected trajectory of the flexible mechanical arm is obtained; obtaining a track deviation and a speed deviation; a fast terminal sliding mode controller is constructed, and a control law is solved in combination with an extended state observer; and carrying out driving control on the flexible mechanical arm by utilizing the obtained control law to realize constant force control on the tail end of the flexible mechanical arm. According to the invention, the response speed of the system and the stability of the transition process are ensured, the problem of impedance coefficient selection is solved, automatic adjustment can be carried out according to real-time information, and the control precision, the response speed and the anti-interference capability are improved.

The invention discloses a dual three-phase permanent magnet motor current control method and system under high speed and low carrier wave ratio, and belongs to the technical field of permanent magnet motor control. The method mainly comprises the following steps: reconstructing a motor mathematical model by adopting VSD conversion and Park conversion; designing a linear expansion state observer; a reference value of an output voltage vector is obtained in combination with deadbeat predictive current control; and performing time delay compensation and angle delay compensation on the output voltage vector to obtain a reference value of a final output voltage vector, sending the reference value to an SVPWM module for modulation, and outputting a PWM pulse signal for driving a motor. No motor parameter is used in the current loop design process, system errors caused by mismatching of the motor parameters can be avoided, and the system robustness is improved; meanwhile, only one control parameter needs to be determined, the parameter setting difficulty is greatly reduced, and stable operation of the high-speed permanent magnet motor under the low carrier wave ratio is achieved.

The invention discloses a cable underwater robot trajectory tracking control method for coping with ocean current disturbance, and belongs to the technical field of underwater robot trajectory tracking, and the method comprises the following steps: S1, constructing a kinematics and dynamics model of a cable underwater robot, and simplifying the kinematics model of the cable underwater robot; s2, combining speed information of a Doppler velocimeter sensor, designing a super-spiral expansion state observer, and compensating a cable underwater robot system; designing a self-adaptive super-spiral expansion state observer by combining a self-adaptive law; and S3, designing a self-adaptive super-spiral integral terminal sliding mode controller based on the self-adaptive super-spiral expansion state observer. The real-time dynamic performance and stability of the underwater robot in sliding mode control are improved, the buffeting problem existing in sliding mode control is solved, it is ensured that under the condition of ocean current disturbance, the ROV can still achieve accurate trajectory tracking, and the robustness is very high.

The invention discloses a vehicle active braking control method based on extended state observation, and the method comprises the steps: estimating unknown parameters of a vehicle through constructing an extended state observer, obtaining the output torque of the vehicle through an accessibility control strategy, obtaining the actual vehicle speed of the vehicle, and determining a vehicle speed estimation error. Calculating a discrete estimation performance index through a discrete estimation performance index function of the extended state observer, iteratively optimizing the extended state observer through a particle swarm optimization algorithm, and iteratively obtaining an optimal solution of a parameter vector of the extended state observer so as to minimize the discrete estimation performance index of the extended state observer. And the unknown parameters of the vehicle are optimally estimated to obtain the optimal output torque of the vehicle, so that the active braking control of the vehicle is realized, and the stable operation of the vehicle under the optimal output torque is ensured. The dynamic behavior can be monitored and adjusted in real time in the running process of the vehicle, and therefore the braking performance and safety of the vehicle are improved.

The invention relates to an intelligent industrial control parameter self-tuning method and equipment. The method comprises the following steps: performing piecewise linearization processing on an actuator input and output characteristic curve in the industrial control system, constructing an upper-layer agent model and a lower-layer agent model, and combining to obtain a system dynamic characteristic prediction model; performing state observer design and gain matrix optimization on the industrial control system based on the system dynamic characteristic prediction model to obtain a system state observation vector and an interference compensation vector; inputting the system state observation vector and the interference compensation vector into a fixed time convergence controller for control parameter calculation to obtain a system control input matrix; and performing adaptive gradient descent operation and momentum item optimization on the system control input matrix, and outputting an optimal control parameter matrix in combination with the system dynamic characteristic prediction model. According to the invention, real-time automatic adjustment of the control parameters is realized, the steady-state error of the system is effectively reduced, and the control performance of the control system under different working conditions is ensured.

The invention belongs to the related technical field of multi-agent control, and particularly discloses a predetermined performance consistency tracking control method and system for a nonlinear multi-agent system, and the method comprises the steps: constructing a Lyapunov function based on the consistency tracking error of the multi-agent system, and obtaining a control law; consistency tracking control of the multi-agent system is realized according to the control law; wherein the system state quantity in the control law is estimated through a distributed state observer; the distributed state observer is designed through the following method: according to a universal approximation principle, a nonlinear function in a multi-agent system dynamic model is approximated based on a fuzzy logic system, and then the distributed state observer is obtained by combining the multi-agent system dynamic model. According to the method, the precision and robustness of the consistency tracking process of the multi-agent system can be remarkably improved.

According to the multi-unmanned-system fixed-time fuzzy self-adaptive event triggering formation control method, an unmanned system mathematical model considering environment disturbance factors is rewritten into a state equation, a fuzzy state observer based on the unmanned system mathematical model is established, and speed vector estimation of the unmanned systems is achieved; the problem that the speed information of the unmanned system cannot be measured is solved, a fixed time fuzzy adaptive event trigger formation controller based on an event trigger mechanism is established through a virtual controller in combination with a fuzzy state observer and a filtering error, and fixed time fuzzy adaptive event trigger formation control of multiple unmanned systems is realized. Based on the established event triggering mechanism, the problems of communication redundancy and communication limitation caused by uninterrupted information transmission of the formation control target can be solved, the number of times of updating the actuator is reduced, and the waste of network communication resources is reduced. And the fixed time formation control of the multi-unmanned system with unknown dynamics and unmeasurable speed can be realized.

The invention discloses a grid-connected inverter control method based on second-order linear active disturbance rejection, and particularly relates to the field of grid-connected inverter control. Voltage and frequency error signals between the output side of the inverter and the power grid are obtained, a pre-synchronization control model is constructed, and voltage amplitude and frequency synchronization is achieved; a second-order linear active-disturbance-rejection controller is introduced in the frequency synchronization control process, an extended state observer is adopted to estimate the output frequency, the frequency change rate and a disturbance term, and a state error feedback control law is combined to generate a frequency regulation control quantity, so that accurate frequency control is realized; after grid connection, a dual-channel LADRC power regulation controller is constructed, and decoupling tracking control is carried out on active power and reactive power; meanwhile, on the basis of fast Fourier transform processing as a stable grid-connected state criterion, the method has the advantages of being high in control precision, high in anti-interference capability, good in current waveform quality, high in adaptability and the like, and is suitable for various grid-connected application scenes.

The invention discloses a safety cooperative control method of a multi-robot system, and relates to the technical field of robot control. The method comprises the following steps: constructing a multi-mechanical-arm multi-robot system model; setting an end effector of the follower robot in a Cartesian space, and determining a dynamic model of the multi-mechanical-arm multi-robot system; according to the input-driven fuzzy state observer and the kinetic model of the multi-mechanical-arm multi-robot system, a distributed fuzzy observer error is obtained; according to the symbol graph network topology, constructing a bidirectional grouping cooperation error, a bidirectional grouping tracking error and a fuzzy estimation error; a backstepping method is applied to obtain a time-varying Tan type Lyapunov obstacle function; and then determining a distributed formation controller and an adaptive law, and determining a distributed bidirectional cooperative controller of the multi-mechanical-arm multi-robot system. The operation safety of the multi-mechanical-arm multi-robot system in a specific task space range is improved.