92 results about "Output feedback" patented technology

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 discloses an electromagnetic micromirror output feedback tracking control method and device based on adaptive Q learning, and the method comprises the steps: constructing an electromagnetic micromirror model based on a physical structure of an electromagnetic micromirror; combining the electromagnetic micro-mirror model with a reference trajectory to construct an augmentation system so as to convert a trajectory tracking problem into a state adjustment problem; based on the augmented system, designing a Q function Bellman equation to establish a data-driven performance evaluation framework; based on the augmented system, the state of the augmented system is reconstructed through historical input and output data, so that angular velocity measurement is avoided; obtaining an optimal control input and a new Q function Bellman equation based on the reconstructed augmented system state and the Q function Bellman equation; and based on the optimal control input and the new Q function Bellman equation, solving a control problem by using an adaptive Q learning algorithm. The method breaks through the limitation that a traditional model depends on a control method, and achieves optimal tracking control only through historical input and output data.

The invention belongs to the field of automatic control, and particularly relates to a nonlinear system dynamic gain global trajectory tracking control method based on a self-adaptive neural network observer, which comprises the following steps: converting an uncertain nonlinear system model with unknown interference according to the requirement of output feedback control to obtain a first nonlinear system model; enabling an unknown nonlinear continuous function in the first nonlinear system model to be expressed as a function only containing an output signal and other system state estimation values; performing approximate approximation on an unknown nonlinear continuous function in the first nonlinear system model by using the first radial basis function neural network vector to obtain a second nonlinear system model; designing a second radial basis function neural network vector to construct a dynamic gain state observer of the second nonlinear system model, and obtaining an estimated value of a system state and an estimated value of an unknown nonlinear continuous function in the model; according to an inversion control method, defining a dynamic system tracking error index containing an intermediate virtual control signal, designing a Lyapunov function, and obtaining a change rate of a dynamic gain, a weight adaptive update rate of a second radial basis function neural network vector, and a control rate of the intermediate virtual control signal and a system input signal; different from most existing nonlinear system control methods, the method combines a novel dynamic gain neural network observer with an inversion controller with dynamic gain, and provides a robust global trajectory tracking control solution for a dynamic system operating under uncertain conditions.

The invention discloses an active disturbance rejection controller control method and device, and the method comprises the steps: receiving an actual output feedback signal of a controlled object and a historical output control signal of a controller based on a linear expansion state observer, calculating the total disturbance of a system in real time through a three-order state-space equation, and obtaining a disturbance estimation value; receiving the disturbance estimation value and the control input gain coefficient based on a compensator, calculating a dynamic compensation amount for offsetting the total disturbance of the system, and outputting the dynamic compensation amount to a signal synthesis node; a deviation signal of a set value signal used for defining the target state of a controlled object and a feedback signal actually output by the controlled object is received based on a controller, and an anti-interference basic control signal is generated in combination with the bandwidth of the controller; and subtracting the dynamic compensation amount from the anti-interference basic control signal based on the signal synthesis node to generate an active-disturbance-rejection control amount, outputting the active-disturbance-rejection control amount to a controlled object, and suppressing external interference and internal parameter drift of the controlled object.

The invention discloses a fast output feedback control method for a networked nonlinear system triggered by a dynamic event. By designing the dynamic gain, the dynamic gain is bounded, tracking error coupling is avoided, and meanwhile, the influence of a nonlinear term containing an unknown quantity and external disturbance on the system is compensated. In addition, a dynamic event triggering mechanism is provided based on the dynamic gain, and dynamic compensation of a triggering threshold value is achieved. And constructing a composite Lyapunov function by recursively constructing a virtual control quantity, and enabling the Lyapunov function to meet a fast finite time stability criterion in combination with parameter design of dynamic gain and nonlinear term power. Therefore, tracking errors are converged to a tight set, and the states of all closed-loop systems and observers are globally bounded. According to the method, rapid finite-time dynamic event triggering output feedback actual tracking control of a non-strict feedback system can be realized, and the method has urgent engineering application requirements and is of great significance in promoting the development of a networked nonlinear system control theory and an engineering technology.

The invention discloses a sea surface ship formation preset time output feedback control method with multiple quantization mechanisms, and the method comprises the following steps: building a sea surface ship formation system model, and carrying out the approximate processing of an unknown nonlinear function in the sea surface ship formation system model through a fuzzy logic system; a fuzzy state observer is constructed to process an unmeasurable state, and in addition, a state quantization mechanism and an input quantization mechanism are introduced; a dynamic surface technology is adopted and a second-order filter is introduced to process a discontinuous problem of a virtual control signal so as to construct a Lyapunov function; in combination with a backstepping method technology, an adaptive law and a preset time quantization controller are designed, and the output state of the sea surface ship formation system is converged to an expected precision range within a preset time. On the basis of guaranteeing the stability of the system, the control precision is improved, the communication overhead is effectively reduced through a state quantization and input quantization mechanism, and it is ensured that the sea surface ship formation system can still operate stably and reliably in a complex environment.

A Hardware Security Module (HSM) (900), and method thereof, suitable for use in securely servicing cryptographic requests from multiple tenant applications to preserve end-to-end privacy is provided. A Link Encryption and Key Diversification interoperability (43) between two processors provides cryptographic and logical isolation between multiple tenant applications on the HSM (900) that use and share more than one PCIe Physical Function (30) over more than one Virtual Function (VF) (21) to one or more Crypto Units (CU) (61) for satisfying a request (46) of an HSM cryptographic services. An Output Feedback (OFB) block with CRC support is further provided with encryption and decryption. The HSM as configured is more resistant to side channel attacks.

The invention provides a flexible intelligent material driver output constraint control method considering butterfly-shaped hysteresis input for an output constraint flexible intelligent material driving system with butterfly-shaped hysteresis input, aims to realize high-precision control in different application scenes, and comprises the following steps of: on the basis of a traditional KP model, selecting a KP model; according to the invention, a new butterfly-shaped KP (Butterfly Kranoselskii-Pokrovskii, BKP) kernel is obtained through derivation, and the KKP (Butterfly Kranoselskii-Pokrovskii, BKP) kernel is used as a kernel of the KKP. A new BKP model is established to describe butterfly hysteresis in the flexible intelligent material driver by performing weighted stacking on the BKP core; an unknown time delay function in the system is approached by using a radial basis function neural network and a finite coverage lemma, and the time delay problem of the control system is solved; a high-gain K-filter is designed to overcome the problem that the state in the system cannot be measured, and the problem of output constraint control of the butterfly hysteresis system is solved by combining a barrier Lyapunov function and an adaptive dynamic surface output feedback control algorithm; a butterfly pseudo-inverse algorithm is designed, the requirement for solving a hysteresis inverse model is avoided, and butterfly hysteresis nonlinearity is weakened to a great extent. Compared with a traditional control scheme, the method has a better effect on tracking performance and tracking errors, the tracking errors are effectively reduced, the control precision is remarkably improved, and precise control over the intelligent material driving system is achieved.

The invention discloses an active defense security control method for a hidden false data injection attack, and relates to the field of information physical system security control, in particular to an active defense security control method. The invention aims to solve the problem that the existing detection method can encrypt a transmitted signal, but is limited to detection of a specific type of attack, or dynamic coupling changing the configuration of a control system can increase the burden of a state estimator, and even causes the performance reduction of the system. The method comprises the following steps of: 1, acquiring output feedback gains of the information physical system under different switching signals; and 2, based on the output feedback control gain obtained in the step 1, performing active attack detection and positioning on the FDI attack, and when the attack is detected and positioned, performing active switching by a controller of the information physical system so as to construct an active security controller aiming at the FDI attack.

The invention provides a finite time position tracking control method of a magnetic suspension system with output constraint, which comprises the following steps of: establishing a mathematical model of the magnetic suspension system, determining an error system, and obtaining upper and lower bounds of suspension air gap constraint and system state information; designing a fractional obstacle Lyapunov function by considering upper and lower bounds of suspension air gap constraint, and solving partial derivative to obtain a constraint processing mechanism function; designing a continuous finite time state feedback constraint controller by using system state information based on a constraint processing mechanism function by applying a finite time control technology and a homogeneous system theory; and based on the constraint processing mechanism function, when the system speed state information cannot be measured, designing a non-smooth filter, and designing a finite time output feedback controller by using the filter output information and the system output information. Unified finite time control of the magnetic suspension system under symmetric / asymmetric suspension gap constraint is realized, and the method has high tracking precision, strong anti-interference robustness and engineering practicability.

The invention discloses a self-adaptive fuzzy PID flow field control method and device, and the method comprises the steps: generating an initial PID gain parameter in real time through a fuzzy reasoning module, introducing an RBF neural network module to carry out the dynamic optimization compensation of the initial parameter, and generating a correction gain. And a final PID parameter is dynamically synthesized by adopting a weighted fusion formula, and a weight coefficient is adjustable so as to balance the contribution of fuzzy rules and neural network learning. The nonlinear approximation capability of the RBF network is utilized, network parameters are updated in real time through a gradient descent method, a Jacobian matrix of a controlled system is output, and the sensitivity of the control quantity to input changes is accurately recognized. The parameter updating rate is dynamically adjusted through a momentum item and an exponential decay function in combination with environmental sensor data, flow feedback and historical deviation, and a closed-loop control loop of monitoring, fuzzy reasoning, RBF optimization, PID output and feedback is formed. The accuracy of flow field control is improved.

The invention discloses an energy storage converter control method based on a fractional order superspiral terminal sliding mode, the energy storage converter comprises a front-stage converter and a rear-stage converter, specifically, a given power reference value is subjected to PQ control to obtain a current reference value, a state space averaging method is adopted to establish a disturbed state space averaging model of the rear-stage converter, and the disturbed state space averaging model of the rear-stage converter is calculated. A high-gain observer is designed according to a state-space equation, a disturbance estimation part in the observer is improved, a lag compensation link is introduced, output of the observer serves as feed-forward compensation and is combined with output feedback control, a fractional order super-spiral terminal sliding mode controller is designed, the fractional order super-spiral terminal sliding mode controller serves as current inner loop control, and the current inner loop control is achieved. SPWM modulation is carried out on the control rate output by the controller to obtain a control signal of a switching tube, and control over the output current of the converter is achieved. According to the method, the chattering problem which is difficult to avoid in integer-order nonsingular terminal sliding mode control in the prior art is solved.

A batch process model-free output feedback control method with non-repetitive interference belongs to the technical field of industrial process control, and specifically comprises the following steps: step 1, giving a mathematical description for an optimal tracking control problem of a non-repetitive batch process; 2, designing an optimal control law based on output feedback; 3, a game Q function construction method based on two-dimensional output feedback in the intermittent process; 4, solving a two-dimensional output feedback problem of batch operation by utilizing reinforcement learning; 5, solving an optimal control strategy based on output feedback through iteration to enable the optimal control strategy to be finally converged to an ideal optimal value; according to the method, the problem that a traditional method for processing the complex characteristics of a two-dimensional system is too tedious is solved, through the output feedback control method based on reinforcement learning, the method does not depend on a system model, the influence on the control performance is reduced, and the control effect is greatly improved.

The invention discloses a self-adaptive anti-saturation output feedback control method for a complex system based on gain adjustment, belongs to the field of self-adaptive control, and is suitable for the complex system containing nonlinear and unknown time-varying vectors and bounded external interference. The method comprises the following steps: firstly, acquiring a real-time output signal of a controlled object, and then estimating an unmeasurable internal state of the controlled object by a state observer; an initial control signal is generated based on a dynamic model, an actuator saturation limit and the like, and after optimization of a dynamic gain updating law, whether the signal is close to saturation is judged through monitoring conditions; and when approaching, triggering a planning moment, adjusting the signal amplitude to a safety range by a planning function, generating a self-adaptive anti-saturation output feedback control signal, outputting the final output feedback control signal to an actuator, and circularly executing the steps. The method ensures that a controlled object outputs a stable tracking reference signal, the control signal is always in a saturation limit, and stable operation of the system is realized without a sesame phenomenon.

A system and method for adaptive data processing combining compression and encryption. The system analyzes input data characteristics, compares probability distributions, and creates a transformation matrix to convert data into a dyadic distribution. It generates a main data stream of transformed data and a secondary stream of transformation information. The system dynamically selects and applies processing techniques, including transformation, encoding, compression, and encryption algorithms, based on analyzed characteristics and real-time performance metrics. It compresses the main data stream using Huffman coding and implements security measures to protect the output. A feedback loop monitors technique effectiveness, updates a knowledge base, and influences future selections. The system can operate in lossless, lossy, or modified lossless modes, adapting to different application requirements. This approach offers an efficient solution for scenarios where both data reduction and security are critical concerns.

The present invention discloses a collaborative formation control method based on a distributed filtering synchronization estimator, comprising the following steps: constructing the state space equation of an intelligent agent according to its mathematical model; defining a global instruction system and generating a global reference instruction; establishing a communication network for a multi-agent system and modeling the channel perturbation of the global reference instruction; constructing a distributed filtering synchronization estimator based on a disturbed output for the global reference instruction affected by the channel perturbation; solving the regulator equation to obtain a feedforward gain matrix of a deterministic equivalent output feedback controller; designing a deterministic equivalent output feedback controller to generate the control input of the intelligent agent, thereby achieving the desired formation control effect. The present invention proposes a type of distributed filtering synchronization estimator based on a disturbed output and designs a distributed deterministic equivalent controller to achieve closed-loop system stability and the intelligent agent motion trajectory approaches the set trajectory, which has broad application prospects.

The invention discloses a quantitative control method and device for preset time output feedback of a double inverted pendulum system, and relates to the field of automation, and the method adopts a fuzzy logic system and a fuzzy state observer which are respectively used for processing unknown nonlinear dynamic characteristics of the system and estimating an unmeasurable state. In the design process of the controller, a second-order command filter and a backstepping technology are combined, a state quantization mechanism is introduced, and a novel self-adaptive quantization control method is provided. According to the method, the problem of discontinuity of virtual control signals can be effectively solved, and meanwhile control singularity is avoided. By introducing the preset time stability criterion, it is proved that the closed-loop system can achieve stable convergence within the preset time. A simulation result verifies the effectiveness of the control method, which indicates that the method can ensure that the output state of the double inverted pendulum system is converged to an expected precision range within a preset time, and the response speed and the control precision of the system are improved.

The application discloses a self-adaptive fuzzy PID flow field control method and device, and the method comprises the following steps: generating initial PID gain parameters in real time through a fuzzy reasoning module, introducing an RBF neural network module to dynamically optimize and compensate the initial parameters, and generating corrected gains. The final PID parameters are dynamically synthesized by using a weighted fusion formula, and the weight coefficient is adjustable to balance the contribution of fuzzy rules and neural network learning. By using the nonlinear approximation ability of the RBF network, the network parameters are updated in real time through the gradient descent method, the Jacobian matrix of the controlled system is output, and the sensitivity of the control quantity to the input change is accurately identified. In combination with the environmental sensor data, the flow feedback and the historical deviation, the parameter update rate is dynamically adjusted through the momentum term and the exponential decay function, and a closed-loop control loop of monitoring-fuzzy reasoning-RBF optimization-PID output-feedback is formed. The application improves the accuracy of flow field control.

The application discloses an adaptive tracking control method for a random nonlinear system based on output feedback, comprising the following steps of S1, constructing a mathematical model of a random nonlinear system with hysteresis input, unknown control direction, arbitrary switching and output constraint; S2, designing a linear state observer, and reconstructing unmeasurable states of the random nonlinear system by using output and control input of the random nonlinear system; S3, introducing a Nussbaum type function to process the unknown control direction, and constructing a barrier Lyapunov function to ensure that the output constraint is not violated; and S4, designing a framework based on a backstepping method, combining a radial basis neural network to approximate unknown nonlinear functions, designing a virtual control law, an adaptive law and an actual control law, and realizing adaptive tracking control of the output of the random nonlinear system on a reference signal.

This invention discloses an output feedback control method and system for a flexible joint manipulator. The method includes: constructing a general state-space model of the flexible joint manipulator; converting the state-space model of the flexible joint manipulator into a linear state observer, which is used to output the auxiliary estimation states of the link angular velocity and the motor angular velocity; defining trajectory tracking error variables step by step; based on the trajectory tracking error variables, link angular position, motor angular position, auxiliary estimation states of link angular velocity and motor angular velocity, deriving and constructing the first to third virtual control laws step by step using the backstepping method; and solving the final control input command according to the first to third virtual control laws to form a linear feedback closed-loop controller. This invention only requires conventional position sensors to achieve output feedback control, which can significantly improve the trajectory tracking accuracy and engineering robustness of the flexible joint servo system.

The invention discloses an operational amplifier circuit safety control method based on a WTOD protocol, and belongs to the technical field of network safety control. The method comprises the following steps: establishing a networked Markov jump system based on a state equation of an operational amplifier circuit; a logarithm quantizer and a WTOD protocol are introduced; a redundant channel is designed for the random DoS attack; establishing an output feedback controller depending on a mapping mode and a scheduling signal; establishing a closed-loop system based on a Markov jump system, a logarithm quantizer, a WTOD protocol, a redundant channel and an output feedback controller; based on a Lyapunov function method, generating a stability criterion of the closed-loop system; and based on the stability criterion, solving the feedback gain of the output feedback controller. The stability of the operational amplifier circuit under random DoS attacks can be improved, unnecessary data transmission can be reduced under the condition that communication resources are limited, and the transmission burden of a communication channel is effectively reduced.

The invention discloses a specified performance output feedback robust fault-tolerant control method, and the method comprises the steps: firstly building a preliminary model of a control system according to the structure of the control system; secondly, giving out a partial failure coefficient of the actuator, and establishing an actuator fault model; and then considering transmission delay and an actuator fault model, designing a fault-tolerant controller, and introducing specified performance indexes into fault-tolerant control. And finally, establishing a closed-loop system with time lag and faults based on the preliminary model of the fault-tolerant controller and the control system with the introduced specified performance indexes, and completing fault-tolerant control. According to the method, the fault stability is ensured, the performance standard is met, and the controller can obtain good dynamic performance while having certain fault-tolerant capability.

The invention belongs to the technical field of linear system dynamics analysis and control, and particularly discloses a linear period time-varying system output feedback stabilization control design method and device, and the method comprises the steps: obtaining a state transition matrix through a numerical calculation method based on a linear period time-varying system; based on the state transition matrix and a preset new input variable, obtaining a transformed input variable, a transformed output variable and a discrete linear time-invariant system; designing an observer and a state feedback control law based on the discrete linear time-invariant system, the preset new input variable and the transformed output variable; and constructing output feedback stabilization control of the linear period time-varying system based on the transformed input variable, the transformed output variable, the observer, the state feedback control law and the preset new input variable. According to the method, system stabilization can be effectively achieved, strict mathematical conditions and hypotheses do not need to be introduced for solving, the application range is wider, and the method can be applied to a generalized linear period time-varying system.

The present invention discloses a model predictive control method based on a dynamic output feedback strategy, which is applied to polyhedral uncertain systems. When physical devices in the polyhedral uncertain system are operating, data is transmitted through sensors. The model predictive control process is as follows: a dynamic output feedback strategy including a controller and an observer is established. Based on the model predictive control problem, the polyhedral uncertain system, the controller, and the observer are described using state equations. The observer is used to constrain the data transmitted by the sensor and process measurement wild values in the data. The controller is used to perform model predictive control on the processed output data to obtain the control input at the next moment, and the control input is applied to the physical device through an actuator. The present invention is targeted at polyhedral uncertain systems with measurement wild values. The study uses a saturation function to study an observer-based dynamic output feedback strategy, mitigate the impact of measurement wild values, and ensure the robustness and asymptotic stability of the system.

The application discloses an output feedback control method for a mechanical arm against random jump interference, firstly establishes a discrete-time mechanical arm Markov jump linear system model, analyzes the discrete-time mechanical arm system model based on the Markov jump process, then designs a state observer and a measured disturbance observer, constructs a compound output feedback controller, estimates the system state to realize state feedback control, and finally guarantees the finite time boundedness and performance of the system through a Lyapunov method and linear matrix inequality technology. The application solves the problem of not considering the influence of the measured interference on the mechanical arm system in the prior art, thereby causing poor stability and control performance of the designed scheme.

The application discloses a complex system adaptive anti-saturation output feedback control method based on gain adjustment, belongs to the field of adaptive control, and is suitable for a complex system containing nonlinear, unknown time-varying vectors and bounded external disturbances. The method first acquires real-time output signals of a controlled object, then estimates unobservable internal states of the controlled object by a state observer; initial control signals are generated based on a dynamic model, actuator saturation limits and the like, are optimized through a dynamic gain updating law, and whether the signals are close to saturation is judged through a monitoring condition; when close to saturation, a planning time is triggered, the signal amplitude is adjusted to a safe range through a planning function, adaptive anti-saturation output feedback control signals are generated, the final output feedback control signals are output to actuators, and the steps are executed in cycles. The method ensures that the output of the controlled object stably tracks a reference signal, the control signals are always within saturation limits, system stable operation is realized, and no Zeno phenomenon occurs.

The invention discloses a flexible joint mechanical arm preset time fuzzy output feedback control method under output constraint. The method comprises the following steps that a state space model of a flexible joint mechanical arm is established; based on a preset time stability theory, designing a Lyapunov function framework which ensures that the system converges to a bounded set within preset time; a fuzzy logic system is adopted to carry out approximation on an unknown nonlinear dynamic function of the mechanical arm; a barrier Lyapunov function is introduced to process system output constraints, and it is ensured that output does not violate physical constraints; constructing a state observer based on a fuzzy logic system to estimate an unmeasurable state; designing a virtual control function, a controller and a parameter adaptive law; and a preset time filter is designed to reduce the calculation complexity, and finally stable control of the closed-loop system within the preset time is realized. According to the invention, the preset time stabilization control of the closed-loop system is successfully realized.

The application relates to the technical field of inverter control, and proposes an HJI inverter robust control method based on a disturbance observer. The method can effectively control a second-order system in the case of external disturbance, uncertainty and unknown disturbance. In order to eliminate the time delay influence of a remote signal on output feedback during transmission, a second-order disturbance observer is used to identify external disturbance. In addition, an SMC control law is designed according to HJI theory to improve the robustness of the system, and the stability of the system is analyzed by using the second Lyapunov method. Compared with the prior art, the application can effectively improve the control of the second-order system, and verifies the feasibility of the theory on an auxiliary power inverter.

The invention provides a chaotic encryption and control method for an aircraft instruction, and relates to the technical field of information security, and the method comprises the steps: receiving plaintext data of an aircraft control instruction, respectively injecting the plaintext data into state equations of a plurality of chaotic systems, and generating a plurality of paths of key streams; performing internal permutation operation on the multiple paths of key streams by using predefined permutation vectors respectively, and performing external interleaving operation on the multiple paths of key streams subjected to internal permutation by using an interleaving sequence specified by predefined interleaving vectors so as to combine and generate a path of composite key stream; encrypting the plaintext data by using the composite key stream to obtain a ciphertext instruction, and sending the ciphertext instruction to an aircraft control end; and at the control end, decrypting the ciphertext instruction based on a preset permutation vector and an interleaving vector, restoring the plaintext data, and generating an aircraft control signal through an output feedback control algorithm according to the decrypted plaintext data.

The invention discloses an anti-DoS attack and actuator saturation power system memory event trigger insurance cost control method and system, and relates to the technical field of network control systems. Establishing a state-space equation based on the dynamic characteristics of the power system; key influence factors in operation of the power system and external influence factors in a network environment are identified; constructing an output feedback controller based on a dynamic memory event triggering mechanism; a convex hull method is adopted to process saturation nonlinear characteristics of the actuator, a closed-loop system is obtained in combination with the state-space equation, and a guaranteed cost function is designed; and judging whether the closed-loop system meets the requirements of local asymptotic stability and a preset weighted disturbance attenuation level, solving a linear matrix inequality, and obtaining an output feedback controller gain and an event trigger weight matrix. The objective of the invention is to solve the problem that the system stability is difficult to guarantee under the complex conditions that a power system suffers from DoS attacks, actuator saturation exists and external disturbance faces.