51 results about "Discrete system" patented technology

The invention discloses a sub-microsecond simulation-based network construction type multi-converter modeling method, and relates to the technical field of converter modeling and simulation. Discretizing a switch element, and constructing a generalized constant admittance switch model based on an LC equivalent circuit; then, expansion modeling from a single converter to a multi-converter system is realized through a discrete system state matrix, and a complete network-forming type multi-converter model including a control link is established in combination with inertia characteristics of a virtual synchronous generator; and finally, building a simulation model of the network construction type multi-converter system in the PSCAD / EMTDC, and verifying the correctness and effectiveness of the method. According to the method, the generalized constant admittance switch model and the inertia characteristic of the virtual synchronous generator are fused, good applicability and stability are achieved under the sub-microsecond-level simulation step length, the system simulation precision and efficiency are remarkably improved, and meanwhile rapid convergence of the transient process of the network construction type multi-converter and active supporting of the power grid voltage frequency are achieved.

The invention relates to a model prediction control method and device based on disturbance prediction, equipment and a medium, and relates to the technical field of system control, and the method comprises the steps: obtaining the disturbance data and actual state quantities (height, speed and attitude angle) of an aircraft at the current moment in real time, determining a disturbance prediction sequence based on the current and historical disturbance data, and obtaining a disturbance prediction result; and constructing a discrete system state prediction model, performing rolling optimization solving by taking minimization of a preset cost function as a target to obtain an optimal control sequence in a future prediction time domain, and outputting a first control quantity in the optimal control sequence as an actual control instruction at the current moment to an execution mechanism. According to the invention, automatic control of a multivariable complex system is realized, high precision and high real-time performance of control are ensured, and the ability of the system to deal with extreme conditions is improved.

The application discloses a short-fiber reinforced ablative material bulk ablation simulation method, and belongs to the technical field of multifunctional composite materials and structure numerical simulation.The application comprises the following steps: constructing a discrete system composed of a series of spherical particle units by using a discrete element method; calculating the contact area, contact force and connecting force of the particle units by using a Hertz-Mindlin contact model and a parallel-bond model at each calculation time step; calculating the temperature of the particle units by using an energy conservation principle and a Fourier heat conduction law; calculating the displacement and angular displacement of the particle units by continuously integrating the momentum conservation equation twice; updating the velocity, displacement and diameter of each particle unit, and updating the porosity and pore pressure of the discrete system; iteratively solving and visualizing until a specific condition is met, and ending the simulation.The application characterizes the internal structure features of the short-fiber reinforced ablative material by using the discrete element method, so that the numerical simulation accuracy of the ablation process is improved, and the possibility of capturing the micro ablation mechanism is provided.

The invention discloses a structural vibration detection method based on an inequality constraint hybrid least square algorithm in the technical field of structural vibration detection. The method comprises the following steps: S1, system model construction: establishing a linear discrete stochastic system state space model; s2, designing an algorithm: proposing a hybrid least square algorithm with input inequality constraints; s3, solving a system model: applying a proposed inequality constraint hybrid least square algorithm to a discrete system to realize simultaneous optimal estimation of a system state and input; and S4, performing comparison simulation: performing simulation by taking a two-layer shear structure as an example, comparing the state and input estimation of the shear structure under the conditions of no constraint and existence of inequality constraint, and verifying the effectiveness of the method. According to the invention, the hybrid least square algorithm of the input inequality constraint is provided, and the filtering effect is optimized by using part of input information, so that the accuracy of structural vibration detection is improved.

The present invention provides a method for optimizing the trajectory deviation of the end of a multi-section arm of a concrete pump truck, comprising: S1: using a Jacobian matrix to establish a nonlinear three-dimensional space dynamic equation of a rule tracking system of a multi-section arm concrete pump truck; S2: using a fuzzy logic expression method to transform the obtained three-dimensional space dynamic equation into a fuzzy model of the nonlinear three-dimensional space dynamic equation; S3: introducing an integral sliding film function, using a BP neural network to approximate the influence of unknown position deviation, and reconstructing the solution of the learning algorithm in a robust control framework of the discrete system; S4: designing a BP neural network optimization learning algorithm based on state feedback control; the method for optimizing the trajectory deviation of the end of a multi-section arm of a concrete pump truck provided by the present invention can reduce the deviation of the motion trajectory of the end of the segment arm of the concrete pump truck, make the pouring process safer and more reliable, and is suitable for further promotion and application.

The invention provides a synchronous correction method for a quantum key distribution system, which can be applied to the technical field of quantum communication. The method comprises the following steps: based on a preset time scale, processing time sequence data collected by a time-to-digital converter by using an optical pulse period of a discrete QKD system and a discrete time calibration optical pulse period to obtain a multi-time-scale statistical counting array; processing the multi-time-scale statistical counting array, and performing multi-time-scale synchronous correction on the discrete QKD system by using the obtained peak position of the discrete time calibration light pulse; processing the voltage amplitude data acquired by the analog-to-digital converter by using the optical pulse period of the continuous QKD system and the period of the continuous time calibration optical pulse to obtain a multi-time scale voltage variance array; and processing the multi-time scale voltage variance array, and performing multi-time scale synchronous correction on the continuous QKD system by using the obtained peak position of the continuous time calibration light pulse.

The invention discloses a novel discrete memristor coupling heterogeneous neuron model construction method and application, and designs a novel discrete memristor model to simulate two different neuron models of synaptic coupling to obtain a final novel discrete memristor coupling heterogeneous neuron model. A phase diagram, an iterative sequence, a bifurcation diagram, a Lyapunov exponential spectrum and other methods are used for analyzing the dynamic characteristics of the model, and it is found that the model presents rich dynamic behaviors such as hyper-chaos, chaos and periods and a neuron discharge mode. The high complexity shows that the novel discrete memristor coupling heterogeneous neuron model can be applied to the security field of image encryption and the like. The constructed coupled neuron model is a discrete system, so that the digital circuit of the model is easy to realize through a DSP (Digital Signal Processor). The coupling neuron model-based application to image encryption is good in effect and high in security.

This invention provides an online iterative compensation system and method for servo errors, comprising: a disturbance observer module: treating the internal nonlinearity and external disturbances of the system as a lumped disturbance during the compensation of slow-cut servo errors by a fast-cut servo system, and estimating and compensating for them; a dual-loop high-bandwidth control module: designing a positive acceleration-velocity-position feedback damping controller in the inner loop to suppress lightly damped resonant modes; an online iterative compensation module: predicting the tracking error of the robust high-bandwidth controller and iteratively compensating it through online reference trajectory correction; and an overall control scheme implementation module: including a disturbance observer, a high-bandwidth dual-loop controller, and an online iterative compensation module; predicting the system state within the prediction interval based on a linear model of the discrete system difference equations, and modifying the reference trajectory online for error compensation. This invention enables real-time iterative compensation, improving the tracking accuracy and anti-interference capability of the fast-cut servo system during the compensation of slow-cut servo errors.

The invention belongs to the technical field of automatic driving automobile speed tracking, and particularly relates to an automatic driving automobile speed tracking cooperative control method based on hierarchical MPC and fuzzy PID, comprising the following steps: S1, constructing a longitudinal dynamic model of an automatic driving automobile; s2, designing a fuzzy rule; s3, obtaining a discrete system state equation by using a forward Euler method; s4, determining that the output of the system at the future moment is expressed in a matrix form; s5, converting an MPC problem and a quadratic programming problem; s6, the execution control layer converts the expected acceleration into throttle valve and brake master cylinder pressure control quantity through fuzzy self-adaptive PID; and S7, switching logic is adopted to judge driving / braking control, and speed tracking control is carried out. According to the method, buffeting can be effectively suppressed on the premise of ensuring that the system can reach a stable state, high robustness to external disturbance is achieved, and speed tracking of the self-driving automobile is ensured.

The present invention discloses an online transfer heuristic dynamic programming method based on a disturbance observer, belonging to the field of nonlinear time-varying delay system control, and adopting a method combining transfer learning and adaptive critic control; using sample data collected from source tasks to obtain prior knowledge, designing a robust optimal control strategy for nonlinear discrete systems, and using it to guide the online control process of the nonlinear system of the target task; proposing a new type of attenuation function with a truncation mechanism to avoid negative transfer effects and save computational resources; proposing a disturbance compensation control mechanism to solve uncertainties; proving the characteristics of uncertain nonlinear systems under robust optimal control and that the weight errors of neural networks are ultimately uniformly bounded under certain given conditions.

The invention provides a vibration noise suppression method for a permanent magnet synchronous motor of an electric vehicle. The method comprises the following steps: establishing permanent magnet synchronous motor mathematical models under different coordinate systems; constructing a torque and flux linkage observer to obtain an electromagnetic torque estimated value and a stator flux linkage estimated value; obtaining an electromagnetic torque reference value through rotating speed loop control, and based on the electromagnetic torque reference value, introducing a cloud drift optimization algorithm to obtain a stator flux linkage reference value; obtaining a discrete system, constructing a cost function, and solving to obtain a reference voltage vector; and carrying out inverse coordinate transformation on the reference voltage vector, generating a three-phase pulse width modulation signal by adopting hybrid random space vector pulse width modulation, and sending the three-phase pulse width modulation signal to an inverter to drive the permanent magnet synchronous motor so as to realize vibration noise suppression of the permanent magnet synchronous motor. Vibration noise can be effectively suppressed, and the control performance and the operation stability of the permanent magnet synchronous motor are improved.

The invention discloses a piezoelectric ceramic driver control method based on a multi-grid method, and belongs to the technical field of precise driving control. Aiming at the problems of low positioning precision caused by inherent nonlinear characteristics of hysteresis, creep and the like of a piezoelectric ceramic driver, many parameters of a traditional complex model and large calculation amount, the method comprises the following steps: firstly, establishing an electromechanical coupling nonlinear power system model, and accurately converting an original system into a linear system through a feedback linearization technology; then constructing an optimal control problem, deducing a regular equation set by using a Pontryagin minimum principle, and performing time discretization by using an implicit Euler format to ensure numerical stability; and finally, introducing a multi-grid algorithm to efficiently solve the large-scale discrete system. According to the method, the calculation complexity is remarkably reduced while the model precision is reserved, the convergence speed is increased by more than 8 times compared with a traditional iteration method, the robustness to parameter changes is high, a precondition device does not need to be adjusted, the positioning error can be controlled within the range, and the method is suitable for the high-end manufacturing fields such as precise positioning and optical focusing.

This invention discloses a modeling method for grid-type multi-converter based on sub-microsecond simulation, belonging to the field of converter modeling and simulation technology. The method involves discretizing the switching elements to construct a generalized constant admittance switching model based on the LC equivalent circuit. Then, by discretizing the system state matrix, an extended modeling from a single converter to a multi-converter system is achieved. Furthermore, by combining the inertia characteristics of a virtual synchronous generator, a complete grid-type multi-converter model including control elements is established. Finally, a simulation model of the grid-type multi-converter system is built in PSCAD / EMTDC, verifying the correctness and effectiveness of the method. This invention demonstrates good applicability and stability in integrating the generalized constant admittance switching model with the inertia characteristics of a virtual synchronous generator at a sub-microsecond simulation step size. It significantly improves the simulation accuracy and efficiency while achieving rapid convergence of transient processes in the grid-type multi-converter and active support for grid voltage and frequency.

The present invention discloses an application of a high-precision enhanced radial point interpolation gridless calculation method in computational acoustic problems, which relates to the application of grid calculation methods in the field of computational acoustic problems. First, the wave propagation problem domain is discretized into a series of scattered points, and the interpolation format of the general scalar field is constructed based on the radial basis function, and each scattered point interpolation basis function is derived; in order to improve the interpolation accuracy of the obtained interpolation format, a new node degree of freedom is constructed at each scattered point, and the node degree of freedom is a local numerical approximation composed of a local enhanced interpolation basis function and a coefficient to be determined. Based on the obtained local numerical approximation, a global interpolation format of the general scalar field is constructed under the premise of satisfying the unit decomposition characteristics. The final discrete system matrix equation is obtained, and the matrix equation is solved to obtain the sound pressure of any point within the entire acoustic problem calculation domain. The present invention realizes high-order interpolation without increasing unit nodes, which can reduce numerical calculation errors.

The application relates to a multi-platform mixed power model simulation method, system and computer equipment. The method comprises the following steps: determining a next time synchronization point of a power model and writing a state signal and the time synchronization point into a first shared memory, providing an accurate benchmark for discrete system simulation; triggering the discrete system to advance according to the time synchronization point and updating a second shared memory, guaranteeing simulation timing and data synchronization; reading the updated target simulation signal in the second shared memory to continue power model simulation, ensuring a circulating dynamic updating process of "benchmark setting-simulation advancing-data feedback", realizing collaborative simulation under non-real-time multi-platform mixing, and improving overall simulation synchronization and accuracy.

The application belongs to the field of multi-agent cooperative control, and particularly relates to a multi-agent consensus cooperative control method based on event-triggered impulse; the method comprises the following steps: constructing a communication topology of a nonlinear multi-agent system; constructing a dynamic model of an agent in a second-order discrete system and initializing the system; setting a non-continuous saturation constraint impulse control protocol; each agent communicates with each other according to the communication topology, continuously acquires state information of neighbor agents and saves its own state information in the communication process; all agents are updated by using the non-continuous saturation constraint impulse control protocol at the impulse moment; all agents are updated according to the dynamic model at the non-impulse moment; an error system is constructed according to the state information of the agents, and when the error system is stable, the agents reach the consensus; the application can realize the state consensus at a faster speed and with fewer event triggers.

The invention discloses a subsynchronous oscillation mode identification method and device based on SMSST-CDSSI, and the method comprises the steps: employing a ridge extraction method, screening out a time-frequency coefficient representing each subsynchronous oscillation component according to the energy of the time-frequency coefficient in each second-order multiple synchronous compression transformation coefficient matrix, and obtaining an optimal instantaneous frequency track; performing time domain reconstruction of each oscillation mode according to the optimal instantaneous frequency trajectory; the method comprises the following steps: constructing a state space model of an n-order system according to input and output signals of a power system and considering deterministic and random noise, and constructing a corresponding Hankle matrix according to input and output variables; performing LQ decomposition on the input / output Hankel matrix to calculate an oblique projection matrix Oi; and performing singular value decomposition on the oblique projection matrix Oi, calculating a state matrix A of a discrete system, performing eigenvalue decomposition on the state matrix A, solving a discrete eigenvalue of the state matrix A, and solving the frequency fi and the modal damping ratio xii of the subsynchronous oscillation according to the relationship between the discrete system and the continuous time system. The device comprises a processor and a memory.

The present invention discloses a state-dependent H∞ control method for a two-dimensional switching continuous discrete system, comprising the following steps: obtaining a two-dimensional switching continuous discrete system model; constructing a state-dependent switching law that depends only on continuous variables to obtain a stability condition for the two-dimensional switching continuous discrete system; applying the stability condition for the two-dimensional switching continuous discrete system to a switching repetitive process to determine an along-channel stability condition for the two-dimensional switching continuous discrete system; and designing a state feedback control law that considers H∞ control of the switching repetitive process, so that the two-dimensional switching continuous discrete system has the desired H∞ performance. The method of the present invention relies only on the state-dependent switching law of continuous variables to analyze the stability of the two-dimensional switching continuous discrete system, obtains the stability condition using the Lyapunov function method, applies the stability result to the switching repetitive process, and implements H∞ control of the switching repetitive process by establishing a new state-dependent switching law.

The invention belongs to the technical field of production system data processing, and discloses a toughness evaluation method and device for a multi-process machining system. According to the method, modeling and normalization of a production line are carried out, failure analysis is carried out on a system composed of degraded machine operation nodes based on fault tree analysis, and a system time recovery curve is comprehensively established; constructing toughness evaluation and prediction of the discrete system; evaluating the credibility of the disturbance event based on a fuzzy analysis method, an entropy weight method and European closeness, and evaluating the influence degree of the disturbance event in combination with a risk matrix; and building system toughness evaluation of the system. According to the method, a normalization formula and a composite attribute matrix are designed, multi-dimensional indexes are converted into unified scores, the overall toughness of the system is conveniently and visually judged, and meanwhile, transverse comparison of priorities of different disturbance events is supported.

The invention belongs to the field of solid propellant performance prediction, and discloses a high-precision modeling method and system for a solid propellant, and the method comprises the steps: obtaining parameters of propellant components; the method comprises the following steps: constructing a solid propellant into a discrete system consisting of spherical particle units, and endowing the particle units with real physical parameters according to component thermodynamic parameters, reaction kinetic parameters and mechanical parameters of the propellant; establishing parallel bond bonds among particle units, and endowing the parallel bond bonds with real physical parameters according to the thermodynamic parameters, the reaction kinetic parameters and the mechanical parameters of propellant components; based on the real physical property parameters of the particle units and the parallel keys, a solid propellant high-precision model is established and used for providing a high-precision initial structure model for propellant ignition combustion process simulation and combustion performance prediction. According to the method, the problems that actual formula parameters such as particle size distribution and gradation are insufficiently considered and a microscopic combustion mechanism is difficult to capture in an existing method are solved, and the accuracy of a propellant numerical model is improved.

The invention discloses a two-dimensional switching continuous discrete system H-infinity control method based on state dependence. The method comprises the following steps: acquiring a two-dimensional switching continuous discrete system model; constructing a state dependence switching law which only depends on continuous variables, and obtaining stability conditions of the two-dimensional switching continuous discrete system; applying the stability condition of the two-dimensional switching continuous discrete system to a switching repetition process, and determining an along-channel stability condition of the two-dimensional switching continuous discrete system; and designing a state feedback control law, and considering H-infinity control in a switching repetition process, so that the two-dimensional switching continuous discrete system has expected H-infinity performance. According to the method, the stability of the two-dimensional switching continuous discrete system is analyzed only by depending on a state dependence switching law of continuous variables, a stability condition is obtained by utilizing a Lyapunov function method, a stability result is applied to a switching repetition process, and H-infinity control of the switching repetition process is realized by establishing a new state dependence switching law.

The present invention relates to the field of modeling and simulation technologies, and specifically discloses a Modelica modeling method for a time-sequential discrete system. Based on the Modelica language, this method uses the method of creating discrete source modules and general discrete modules to establish discrete task models, and then constructs a time-sequential discrete system model. By configuring the task period and execution time of the discrete source modules of each task model, multi-rate group task time-sequential design and simulation are realized; by introducing a structured data recording module, the single-step / multi-step delay method of structured data is broken through, and the cyclic dependence problem existing in the modeling and simulation of discrete systems is solved. The Modelica modeling method for a time-sequential discrete system provided by the present invention solves the key problem of modeling time-sequential discrete subsystems in the unified modeling and simulation of large-scale systems across the entire field.

The present invention discloses a waveform adaptive selection method based on deep reinforcement learning, comprising: firstly, modeling a simulation scenario by constructing a discrete system state space model; then, constructing a target entropy state by minimizing the Cramer-Rao lower bound of the target parameter estimation, and constructing a real entropy reward for a waveform parameter selection action by using the real entropy states at previous and next moments; then, using a cubature Kalman filter to predict the target state at the next moment of different waveform parameter selection actions at the current moment; then, constructing a feedforward loop path composed of predicted entropy rewards based on the predicted entropy states; finally, designing an action reward function for a multi-node scenario, and using a DQN network to approximate the value of the reward expectations of different actions under different states to obtain the final waveform parameter selection action; the present invention can quickly adapt to the environment learning action selection strategy in a dynamic environment, and quickly and adaptively select the emission waveform parameter action based on the feedback of the environment, with strong robustness.

The invention relates to a zero dynamic attack detection method for a wind power system based on off-phase sampling, and the method comprises the steps: obtaining the dynamic information between main sampling points of a discrete system through introducing an offset phase sampling mechanism, and achieving the detection of zero dynamic attacks. The offset phase sampler is placed at an offset phase compared with the main sampler, and obtains internal system dynamics in a sampling interval; and the data abnormity is judged through residual error accumulation detection. The method is high in engineering feasibility, can effectively detect extremely hidden zero dynamic attacks on the premise of not changing a system structure and not introducing redundant hardware or a high-safety communication link, and breaks through a blind area of a traditional detection method.

An embodiment of the present invention provides a method for unconditionally maintaining the strong stability of a hyperbolic conservation law in computational fluid dynamics, comprising: spatially discretizing the hyperbolic conservation law equation in computational fluid dynamics using a preset spatial discretization method to obtain a semi-discrete system of the hyperbolic conservation law; introducing a stabilization term into the semi-discrete system of the hyperbolic conservation law to form a stabilized semi-discrete system of the hyperbolic conservation law; temporally discretizing the stabilized semi-discrete system of the hyperbolic conservation law using an explicit integrating factor Runge-Kutta method to obtain a fully discrete system of the hyperbolic conservation law; and reasonably approximating the exponential function in the explicit integrating factor Runge-Kutta method of the fully discrete system of the hyperbolic conservation law to obtain a fully discrete format of the hyperbolic conservation law that unconditionally maintains strong stability. This method ensures that the hyperbolic conservation law can maintain strong stability at any time step.

This invention relates to a system call analysis method based on multi-dimensional correlation, belonging to the field of data processing technology. It solves the problems of high performance overhead and difficulty in balancing accuracy and real-time performance in existing call analysis methods. The method includes: filtering and capturing system call events generated by a target application according to filtering rules, and dynamically adjusting the filtering rules by real-time monitoring of system load; correlating the captured system call events along process, time, and resource dimensions to obtain multiple system call sequences; precisely matching each system call sequence with atomic behavior rules to obtain the behavior type of successfully matched system call sequences; performing feature matching of unmatched system call sequences with historical behavior data to obtain the corresponding behavior type; and outputting structured behavior data based on each system call sequence and its behavior type. This achieves accurate and real-time analysis of discrete system call events.

The invention belongs to the technical field of LPF closed-loop system simulation, and particularly discloses an LPF closed-loop system construction method and system based on a state space model. The method comprises the following steps: establishing a state space model of each subsystem included in the LPF closed-loop system; according to the data sampling time, classifying subsystems except the noise model into a continuous system and a discrete system; respectively connecting the continuous system and the discrete system; discretizing the connected continuous system and the noise model respectively, and then connecting the discretized system and the connected discrete system to form a complete LPF closed-loop system; and recombining and simulating the state space model of the LPF closed-loop system. According to the LPF closed-loop system construction method provided by the invention, the operation is more simplified, a required function can be realized by using a simple function, the operation efficiency is high, and a model basis is provided for subsequent data processing and analogue simulation.

The invention discloses an enhanced moving least square meshless method for calculating a steady-state sound propagation problem, and relates to the technical field of numerical simulation calculation and numerical forecasting of the steady-state sound propagation problem, and the method comprises the steps: S1, constructing an interpolation function of a steady-state sound field; s2, constructing a local enhanced interpolation primary function; s3, constructing a global interpolation format; s4, constructing a numerical calculation model for discretization of the steady-state sound propagation problem; s5, constructing a discrete system matrix equation; s6, sound pressure solving is carried out; s7, result verification and analysis; according to the enhanced moving least square meshless method for calculating the steady-state sound propagation problem, the problem that high-frequency errors are large in existing steady-state sound propagation calculation is solved.

The application discloses an anaerobic ammonia oxidation activity prediction method and system based on a TabPFN model, and comprises the following working steps: step S1, collecting anaerobic ammonia oxidation system operation data, and constructing an original data set with anaerobic ammonia oxidation activity SAA as a prediction target, wherein the operation data comprises heterogeneous table data composed of numerical continuous operation parameters and discrete system information of a category; step S2, preprocessing the original data set, and sequentially completing missing value completion, abnormal value identification and cleaning, and category feature encoding conversion to obtain a standardized heterogeneous table data set; and step S3, dividing the standardized heterogeneous table data set into a training set and a test set. According to the heterogeneous table data characteristics of SAA, the application can simultaneously process continuous variables and category variables, and improve the adaptation capability to complex operation data; and the application can learn the nonlinear mapping relationship and interaction between SAA and multiple factors, so that the prediction precision and generalization capability are improved.

This invention proposes a multi-model non-disruptive switching control method and system for steam temperature under all operating conditions in thermal power units, relating to the field of thermal power generation. The method includes: acquiring steam temperature data and load conditions in the steam temperature loop of the thermal power unit; constructing steam temperature models under different load conditions across all operating conditions based on adaptive weight positive and negative feedback using a slime mold algorithm, using the steam temperature data and load conditions as input; constructing a continuous system model set from the steam temperature models under different load conditions across all operating conditions, and then discretizing it into a discrete system model set; using the discrete system model set as input, controlling the steam temperature data under a single operating condition using a step-wise generalized prediction method; non-linearly fitting weight allocation parameters to multiple models across all operating conditions, and obtaining a flexible switching curve through smoothing; and controlling the steam temperature across all operating conditions using the flexible switching curve. This invention achieves non-disruptive switching between different operating conditions, realizing precise steam temperature control across the entire operating range of thermal power units with limited computing resources.