17 results about "Fractional order calculus" patented technology

The invention discloses a PMSM (permanent magnet synchronous motor) control method for a mining electric locomotive. The method comprises a cooperative control framework of a fractional order sliding mode controller and a nonlinear extended state observer. Wherein the fractional order sliding mode controller constructs a novel sliding mode surface by introducing a terminal factor and a fractional order calculus theory, and introduces a state variable to design an adaptive fractional order reaching law, so that buffeting is effectively inhibited and controlled while system error convergence is accelerated; and the nonlinear extended state observer is used for estimating the uncertainty of a system model and the disturbance of an external load in real time, and introducing the uncertainty and the disturbance as feedforward compensation quantity into a control loop, so that the anti-interference capability of the system is remarkably enhanced. Through deep fusion of the fractional calculus theory, the sliding mode control and the nonlinear extended state observer, the problems of large buffeting, slow response, poor anti-interference capability and the like of a traditional control method of the mining electric locomotive under complex working conditions are solved, and the dynamic and steady state performance and the control precision of the system are remarkably improved.

The invention relates to a fractional order PID (Proportion Integration Differentiation) control method and system based on an FPGA (Field Programmable Gate Array). The method comprises the following steps of: 1, setting fractional order PID related parameters according to the requirements of a controlled object; 2, calculating a fractional order calculus weight coefficient according to the fractional order PID related parameters, and storing the fractional order calculus weight coefficient in the FPGA; 3, collecting a state feedback signal of the controlled object, and calculating an integral term operator and a differential term operator; step 4, calculating control output and performing amplitude limiting processing, and updating the state of the controlled object by using the control output after the amplitude limiting processing; and 5, repeating the steps 1-4 to realize fractional order PID closed-loop control. By optimizing a discrete convolution algorithm, adopting a parallel pipeline architecture and configurable parameter design and combining fixed-point number operation and security boundary constraint, the numerical stability and hardware security of the system under high-speed operation are ensured, the calculation speed is remarkably increased while the operation precision is ensured, and the method is suitable for large-scale popularization and application. And the method is suitable for control occasions with extremely high real-time requirements.

The invention discloses a fractional order sliding mode prediction control method for a V2G vehicle-mounted converter, and relates to the technical field of vehicle-mounted bidirectional converter control. According to the method, firstly, a fractional order mathematical model of a V2G (Vehicle-to-Grid) vehicle-mounted converter is established on the basis of a fractional order calculus theory; the method comprises the following steps: firstly, constructing a fractional order state space model of a system by introducing a fractional order differential operator, and deriving a fractional order state space equation of a vehicle-mounted bidirectional transducer; the invention provides a V2G vehicle-mounted converter control strategy combining a fractional order mathematical model, a sliding mode controller and a model prediction control method, and realizes accurate control of a front-stage totem-pole bridgeless PFC and a rear-stage CLLC resonant converter of the V2G vehicle-mounted converter. Through the control strategy, the limitation of modeling precision of traditional integer order modeling in V2G vehicle-mounted converter control is effectively solved, and the control precision and the dynamic response performance of the system are remarkably improved.

This invention discloses a transient control method for compound-wing unmanned aerial vehicles (UAVs) based on fractional-order sliding mode control, specifically relating to the field of compound-wing UAV flight control. It employs the Newton-Euler equations to perform integrated modeling of the transient process of the compound-wing UAV, deriving a longitudinal nonlinear mathematical model. Based on the traditional exponential power reaching law, a novel fractional-order reaching law is designed by combining a double power reaching law and the concept of fractional-order calculus. A fractional-order sliding mode controller is constructed for pitch angle, airspeed, and quadrotor altitude. An airspeed weighted control allocation strategy is used to distribute the forces and torques between the quadrotor system and the fixed-wing system, thereby solving for the actuator output. This invention applies sliding mode variable structure control to the transient control of compound-wing UAVs. The proposed fractional-order sliding mode control method improves the dynamic quality of the system, reduces steady-state control errors, enhances the robustness of the compound-wing UAV flight control system, and achieves smooth control of the transient process.

This invention relates to the field of voice coil motor servo control technology, specifically to a fractional-order high-order sliding mode control method for voice coil motors based on a third-order superspiral sliding mode observer (STSMO) and an adaptive reaching law. The method includes the following steps: S1, establishing a mathematical model of the voice coil motor, deriving the dynamic equations of the voice coil motor including parameter uncertainties and external disturbances, defining the position tracking error, and deriving the error dynamic equation; S2, designing a fractional-order high-order integral sliding surface, combining it with an improved Oustaloup filter to achieve rational function approximation of the fractional-order calculus operator, and constructing the first-order derivative equation of the sliding surface; S3, designing an adaptive hyperbolic tangent reaching law that integrates dynamic feedback of the error amplitude, and deriving the initial expression of the sliding mode control law based on the first-order derivative equation of the sliding surface and the adaptive hyperbolic tangent reaching law. This invention achieves real-time accurate observation and feedforward compensation of lumped disturbances through a third-order superspiral sliding mode observer (STSMO).

The present application relates to the technical field of unmanned aerial vehicle flight control, and particularly relates to a three-dimensional terminal game control method for unmanned aerial vehicle based on deep reinforcement learning, comprising: initializing a model and a maneuvering constraint boundary, and collecting a local and enemy state vector; performing fractional order calculus on the three-dimensional position of the enemy to extract a fractional order derivative vector, and splicing the fractional order derivative vector with the state vectors of both sides to generate a non-Markov state vector; inputting the non-Markov state vector into a strategy network to solve a three-dimensional action vector; performing physical mapping according to the maneuvering constraint boundary to generate a aerodynamic instruction to drive state transition, and obtaining a next time state vector; combining the foregoing vectors to construct a tracking error and a Lyapunov function, calculating a total derivative and performing divergence punishment to generate a Lyapunov reward value; storing a transition tuple into a replay pool to update model parameters in a closed loop, and outputting an optimal strategy. The present application solves the problems of prediction lag and easy divergence off-target when chasing a high dynamic target.

The invention discloses a wireless communication power control method based on a fractional calculus theory, which comprises the following steps of: firstly, constructing a continuous time stochastic differential equation channel model driven by a symmetric-stable Levy process, and respectively depicting heavy tail jump behaviors in long-term path loss and short-term multipath fading; then, on the basis of the channel model, a generalized Riesz fractional order derivative operator is introduced, a class of fractional order HJB (FHJB) control equations with non-local operators are deduced under the dynamic programming principle, and the fractional order HJB (FHJB) control equations are used for describing an optimal power control strategy under the infinite variance interference condition; and finally, in a multi-base-station multi-user same-frequency interference scene, constructing a fractional order FHJB power control solution framework, obtaining an optimal transmitting power distribution strategy by using a value function iteration method, and verifying the robustness and communication quality assurance capability of the optimal transmitting power distribution strategy under a jump fading channel through numerical simulation. According to the invention, adaptive control of the transmitting power in a non-stationary and heavy-tailed fading environment can be realized.

This invention discloses a speed control method for a permanent magnet synchronous motor based on a fractional-order sliding mode. This method exploits the slow decay of fractional-order calculus over time. First, a fractional-order sliding mode surface is introduced on top of the traditional sliding mode surface. Second, a novel fast reaching law is proposed that adaptively adjusts parameters based on the distance of the system state from the sliding mode surface. Finally, to avoid repeated trial and error in adjusting the reaching law parameters, a particle swarm optimization algorithm is introduced to tune the parameters. Simulation results show that, compared with the exponential reaching law and the novel reaching law, the speed loop sliding mode control designed using the proposed method not only improves the system's speed regulation performance but also reduces system chattering and enhances system robustness.

This invention discloses a nonlinear predictive function control method for a fractional-order turbine regulating system, belonging to the field of automatic control technology. First, a sudden load model of the turbine regulating system is introduced, incorporating fractional calculus and dynamic turbine transfer coefficients. Then, based on the series characteristics of the turbine regulating system, a predictive function controller based on a time-varying nonlinear state-space model is designed, effectively improving the unit's speed and stability. The fractional-order model part employs an improved Oustaloup approximation method and an optimal model order reduction algorithm, enabling efficient computer simulation calculations.

This invention provides a battery thermal management control method based on a fractional-order thermal model and a rolling time-domain chimpanzee algorithm. It introduces fractional-order calculus theory to reconstruct the battery's thermal dynamic equations, capturing the memory characteristics of the thermal system with high fidelity; constructs a rolling time-domain control architecture to achieve proactive prediction and intervention of future thermal states; and replaces the traditional iterative algorithm with an improved chimpanzee optimization algorithm that integrates a lens imaging back-learning mechanism. This invention aims to systematically innovate from three dimensions: mechanism modeling, control architecture, and optimization algorithm, thereby achieving multi-objective synergistic optimization of system energy efficiency, temperature control accuracy, and temperature uniformity while ensuring the safe operation boundary of the battery.

This invention discloses an adaptive data-driven fractional derivative positioning optimization method, belonging to the field of radio positioning technology, comprising the following steps: S1. Receive signal strength indicators at actual locations using sensors within a target area to generate an RSSI dataset; S2. Generate and train a fractional derivative kernel adaptive filter based on the RSSI dataset; S3. Input the actual location and RSSI dataset into the trained fractional derivative kernel adaptive filter to obtain the target location. Compared to traditional classical kernel adaptive filtering methods, this invention utilizes a weight update strategy constructed using fractional derivatives, resulting in higher and more robust filtering accuracy. This invention is the first to incorporate fractional calculus combined with q-Laplacian kernel technology into kernel adaptive filters to construct a positioning system. Experiments have shown that this algorithm achieves better positioning accuracy than the most advanced positioning algorithms currently available.

The present invention discloses a fractional-order derivative estimation method based on sliding mode technology. By using the properties of fractional-order calculus, a strategy for estimating the fractional-order derivatives of any bounded continuous signal or contaminated signal is designed. Then, an estimation system structure diagram is constructed to form a fractional-order derivative estimator, that is, a typical negative feedback closed-loop system + filter model. Then, with the help of stability theory and statistical linearization methods, relevant parameters of the above-mentioned fractional-order derivative estimator are determined, and an adaptive component is further added in the case of an upper bound of the fractional-order derivative that is unknown in advance, so that the adaptive gain can be automatically adjusted online as the error system changes. At the same time, computer software is used to perform simulation tests, and the gain coefficients at various locations in the optimization structure diagram are adjusted to improve the estimation effect. Then, the designed method is applied to practice to estimate the fractional-order derivatives of contaminated signals, and the design of a fractional-order controller for two inverted pendulums is realized.

The invention discloses a disturbance fractional order chaotic system quasi-synchronization method and device and a storage medium, and the method comprises the steps: constructing a fractional order chaotic master system with external disturbance and a fractional order chaotic slave system with external disturbance based on a fractional order chaotic system; setting a synchronization error according to the fractional order chaos master system and the fractional order chaos slave system; constructing a synchronization error system according to the fractional order chaos master system, the fractional order chaos slave system and the synchronization error; designing an intermittent synchronous controller according to the synchronous error; and acting the intermittent synchronous controller on the synchronous error system, so that the fractional order chaos slave system is synchronized with the fractional order chaos slave system. According to the method, under the condition that disturbance exists in the chaotic system, the fractional calculus is adopted to describe the system, and the fractional order chaotic system under external disturbance is constructed, so that the robustness of the system is improved, and the method has a wider application prospect; by designing the intermittent synchronous controller, quasi-synchronization of the fractional order chaotic system is realized, and the control theory of the fractional order chaotic system is enriched.

The invention discloses a fractional order active disturbance rejection control method for a fractional order chaotic system, and the method comprises the following steps: constructing a mathematical model of a fractional order Lorenz chaotic system according to a fractional order calculus theory; designing a fractional order tracking differentiator in order to accurately extract fractional order differential information of a system state variable; designing a fractional order expansion state observer for observing the total disturbance of the fractional order chaotic system; comparing the output of the fractional order expansion state observer with the output of the fractional order tracking differentiator to obtain an error signal, and designing a fractional order PID controller; and designing a fractional order active disturbance rejection controller to realize stable control of the fractional order Lorenz system. The fractional order active-disturbance-rejection control method for the fractional order chaotic system effectively makes up for the defects of the existing control technology, and remarkably improves the control precision, the anti-interference capability and the chaos phenomenon suppression capability of the fractional order chaotic system.

The invention discloses a permanent magnet synchronous motor inverse compensation iteration fractional order sliding mode control method based on an improved fractional order superspiral sliding mode observer. The specific process is as follows: establishing a mathematical model of a permanent magnet synchronous motor under an alpha-beta two-phase static coordinate system; and determining the input and output variables of the observer according to the established permanent magnet synchronous motor model. A traditional fractional order superhelix sliding-mode observer used for estimating the extended counter electromotive force is constructed, and a traditional integer order sliding-mode observer frame is extended by introducing a non-integer order integral operator according to the fractional order calculus theory. And designing an inverse compensation controller based on the mathematical model of the permanent magnet synchronous motor and the disturbance information estimated by the fractional order superspiral sliding mode observer. The permanent magnet synchronous motor adopting the control strategy has higher response speed, higher rotating speed tracking precision and stronger robust stability under the working conditions of starting, speed regulation, load abrupt change and the like, and the operation performance and reliability of the permanent magnet synchronous motor are improved.

The present invention discloses an intelligent calculation method for the time-varying deformation of RC components taking into account the stiffness of the corridor, and belongs to the technical field of time-varying deformation of concrete components. The method includes constructing an axial time-varying deformation model of reinforced concrete components; obtaining the reinforcement ratio of reinforced concrete components, the elastic modulus of steel bars, and the elastic modulus of concrete, and calculating stiffness information; calculating the stiffness of the corridor; constructing a group of fractional-order calculus constitutive equations; performing Laplace transformation on the group of constitutive equations, and then performing MATLAB calculations to obtain the creep flexibility expression of the axial time-varying deformation model of reinforced concrete components; and calculating the total strain of the vertical components based on the creep flexibility expression. The present invention combines the basic theory of fractional-order calculus and the time-varying characteristics of reinforced concrete, effectively utilizing the advantage that the mechanical model fitting effect of the fractional-order calculus unit is significantly better than that of the traditional mechanical unit model, and fully considering the time-varying deformation of reinforced concrete components in actual engineering.

The application provides a fractional calculus energy reduction guiding method for enhancing deep Transformer-Attention integrated prediction, which is composed of a Transformer-Attention network, an efficient time series prediction network combined with a time series attention unit and a fractional order random dynamic calculus controller. The method considers the energy consumption of a comprehensive energy system, takes energy consumption influencing factors and energy production as inputs, and outputs an optimal energy reduction guiding signal. The Transformer-Attention network and the efficient time series prediction network combined with the time series attention unit in the method can solve the prediction problem of benchmark energy consumption, and are used for outputting an optimal prediction result; the fractional order random dynamic calculus controller in the method can obtain an optimal energy reduction guiding signal through the predicted energy consumption and energy production. The method can reduce the overall energy consumption of the comprehensive energy system and improve the stability of the comprehensive energy system.