226 results about "Design control" patented technology

The invention provides an HVAC system temperature control and energy consumption optimization method based on deep reinforcement learning. Through an entropy-based data screening method, a strategy evaluation module and a design reward function, HVAC system temperature control and energy consumption optimization are realized under external condition interference. According to the entropy-based data screening method, the value of data for agent training is calculated through an error formula, high-value data is repeatedly used for agent training, and the training effect is enhanced; the strategy evaluation module is used for further solving the problem of overestimation of a Q value on a double-Q structure, correcting the output of the Q value, reducing the influence of a random Q value, and adding regularization of a strategy and an actual action into a loss function updating process, so that the influence of random noise on the Q value is eliminated, and the accuracy of strategy output is ensured; a reward function for controlling the temperature and optimizing the energy consumption is designed, so that the intelligent agent can balance the contradiction among multiple tasks, and the optimal solution of multi-target task intersection is searched, so that the HVAC system can control the temperature to be always kept in the temperature range, and meanwhile, unnecessary energy consumption is reduced.

The invention provides a heat storage heat pump system control method based on a physical information neural network, and belongs to the technical field of heat storage pump system intelligent control. Aiming at the problems that in the prior art, an algorithm is difficult to adapt to dynamic energy consumption requirements, engineering application of a model is difficult due to building space heterogeneity, high-order RC model prediction credibility is weak, engineering feasibility is poor and the like, a solution combining a physical information sequence to sequence neural network technology and a finite-state machine control strategy is provided. On the model level, a 2R2C resistance-capacitance RC model of building temperature change is established, and then a PI-Seq2seq prediction model is proposed based on the physical model. On the control flow optimization level, on the basis of an industrial and commercial time-of-use electricity price policy, an FSM control model is designed, a system state set is defined, parameters and a transfer function are input, and a control rule is constructed in combination with the working period of a building heat pump and the characteristics of a heat storage tank. And finally, energy consumption cost optimization and indoor temperature stabilization under the peak-valley electricity price are realized.

The invention discloses a hemispherical resonator gyroscope attitude drift error compensation method, and relates to the technical field of resonator gyroscopes, and the method comprises the following steps: S1, system modeling: firstly, establishing a mathematical model of a hemispherical resonator gyroscope, including dynamic characteristics and a noise model, for designing a PID controller; s2, a PID controller is designed, the proportion P, integral I and differential D parameters of the PID controller are designed according to the system model, and the parameters determine the response speed and stability of the controller to error signals; s3, error signal calculation: calculating an error signal between the actual output and the expected output of the system in real time, and taking the error signal as the input of a PID (Proportion Integration Differentiation) controller; by comprehensively applying the steps, the robustness of the HRG can be remarkably enhanced, the HRG can still keep high precision and stability when facing environment change, system aging or non-ideal working conditions, and a closed-loop control mechanism is combined to ensure that the system can maintain good performance under various conditions.

The invention belongs to the field of aircraft control, and particularly relates to a helicopter adaptive command filtering backstepping tracking control law design method, which comprises the following steps: firstly, decomposing a helicopter kinetic model into a plurality of strict feedback systems with uncertainty, and then designing a controller by using a backstepping method; a hybrid command filter is adopted to solve the problem of calculation explosion of backstepping, and a filtering compensation mechanism is introduced. In addition, an uncertain part in the model is approximated by adopting a neural network, and network parameters are updated online by adopting an adaptive law. And finally, designing a Lyapunov function to prove the effectiveness of the method.

The invention discloses an air robot control method and system oriented to a complex environment, establishes a kinetic model of an air robot according to the control requirement of the air robot for executing contact operation in the complex environment, and provides a hierarchical control framework. The framework includes an outer torque estimator, an impedance-based force / trajectory tracking module, and a position controller and an attitude controller. Firstly, a generalized torque estimator is introduced, and effective estimation of external disturbance is achieved under the condition that no additional sensor is needed; secondly, the contact force tracking performance is improved while the track precision is maintained by using an impedance control module; and finally, a position controller and an attitude controller ensure rapid convergence of the position and the attitude. Theoretical analysis shows that the designed control law can ensure the stability and convergence of the system when uncertainty and external contact force exist, and an effective control method is provided for autonomous operation of the aerial robot in a complex task environment.

The invention relates to a four-rotor unmanned aerial vehicle pose control method based on a global sliding mode. The invention relates to the technical field of unmanned aerial vehicle control, and the method comprises the steps: carrying out the modeling of a dynamic model of a quad-rotor unmanned aerial vehicle, and obtaining the nonlinear state space description of the quad-rotor unmanned aerial vehicle; secondly, respectively designing global sliding mode control laws for the position subsystem and the attitude subsystem according to the nonlinear model; according to the output of a position subsystem controller, the expected acceleration is mapped into expected lift force and attitude angle by designing control distribution; and finally, constructing a nonlinear programming problem corresponding to a nonlinear model prediction controller by taking a previously designed global sliding mode control law as a contraction constraint, and solving the problem to obtain a control quantity. According to the method, the quadrotor unmanned aerial vehicle can effectively perform trajectory tracking under the conditions of output constraint and convergence guarantee, and the control precision, the response speed and the safety in the flight process are improved.

The invention discloses an aircraft active side lever force feedback control method based on feedback linearization. The method is suitable for pitch axial force feedback control and roll axial force feedback control of an aircraft active side lever. The method comprises the following steps: establishing a kinetic equation of a mechanical transmission system and a pitch axis motor or a roll axis motor, and establishing a state-space equation of an active side lever system according to the equation; designing a linear expansion observer, and estimating the thrust applied to the active side lever by the driver based on the linear expansion observer; and designing a feedback linearization control method, deducing a control law according to a state-space equation of the active side lever system, and introducing the estimated thrust applied to the active side lever by the driver into the control law to realize real-time compensation of external interference. Under the condition that the thrust of the driver cannot be measured, the thrust of the driver is obtained through the linear expansion observer, the thrust of the driver is compensated by designing the control law, and therefore the dynamic performance and the steady-state performance of the servo system are improved.

The invention provides a heavy duty gas turbine control system which comprises a signal conditioning module and a plurality of parameter control modules, and a rotating speed control module, a load control module, a temperature limit control module and an acceleration control module in the parameter control modules are all used for achieving closed-loop control according to the deviation between a set value and a corresponding observation value; the starting control module is used for acquiring a starting fuel quantity instruction through a designed control strategy; the IGV and VGVs control module obtains an IGV and VGVs angle instruction according to the turbine inlet temperature set value, the turbine outlet temperature set value and the deviation maximum value of the corresponding observation value; the fuel quantity control module obtains a total fuel quantity instruction based on a full working condition range fuel quantity control strategy; the fuel gas distribution control module is used for obtaining an opening degree instruction of each fuel valve according to the total fuel quantity instruction; the adaptability, the reliability and the usability of the control system in application scenes such as autonomous design and technical improvement are improved.

The invention discloses a self-adaptive finite time fuzzy safety control method for a flexible joint mechanical arm, which comprises the following steps that a flexible joint mechanical arm state space model influenced by spoofing attack is established, and a control signal comprises an unknown time-varying parameter and an unknown bounded attack function; introducing a Nussbaum function meeting a preset limit integral property; designing a control method based on a finite time stability principle, and ensuring that a system state converges to a bounded residual set within finite time; a fuzzy logic system is adopted to approach an unknown nonlinear function in the mechanical arm model; defining an error variable through coordinate transformation, and constructing a parameter which exponentially decays along with time; constructing a Lyapunov function containing the exponential decay parameter, and designing a virtual control function, a controller and a parameter adaptive law based on the function; and the Nussbaum function is constructed to be used for processing the unknown time-varying parameters. According to the invention, the influence of spoofing attacks on state signals can be reduced.

The invention discloses a multi-stage control method for a lower limb exoskeleton, is applied to the field of exoskeleton robots, and aims to solve the problem that the design control precision is reduced due to the uncertainty of a model in the prior art. According to the controller designed by the invention, in a high-level control layer, a human body training mode is determined by a motion intention of an operator so as to generate a reference gait track; in the middle control layer, a variable admittance controller is designed, and three training modes of human exoskeleton cooperative movement, namely a passive mode, an active mode and a passive-to-active mode, are planned. In a low-level control loop, a method with a radial basis function neural network estimation function and a fixed-time convergence controller with input dead zone compensation are provided so as to ensure that an exoskeleton joint position tracks an expected trajectory output by an admittance loop. In order to avoid the Zeno phenomenon of the designed controller, an event trigger mechanism is used to determine the execution time of sampling and transmitting signals. Finally, the effectiveness of the proposed control strategy is verified through simulation and experimental results.

The invention belongs to the technical field of intelligent control, and discloses a speed tracking self-adaptive iterative learning control method for an extrusion rod of an extruding machine, which comprises the following steps of: determining a dynamic model of the extrusion rod and a control target according to the physical property and the motion mode of the extrusion rod; based on an approximation theory, establishing a neural network model for an uncertain part in the extrusion rod motion model, and determining a speed tracking error system of the extrusion rod; designing virtual control input and actual control input based on a self-adaptive iterative learning control theory; based on the Lyapunov stability theorem, the stability of the controller is analyzed and designed. According to the speed tracking self-adaptive iterative learning control method for the extrusion rod of the extruding machine, limited time speed tracking of the extrusion rod can be effectively controlled, accurate motion control over the extrusion rod is achieved, and the size precision, the surface quality and the production efficiency of products are ensured.

The invention provides a self-adaptive fixed time tracking control method based on event triggering, which is used for solving the technical problem that a virtual control law is easy to generate singularity in the traditional backstepping method design. The method comprises the following steps: establishing a mathematical model of a non-strict feedback nonlinear system with input time delay, and introducing an auxiliary system to counteract delay influence; an error dynamic system is obtained through coordinate transformation; according to system fixed time convergence, designing a piecewise function, introducing a backstepping method to design a controller and an adaptive law, using an RBFNN to approach an unknown function therein, designing a virtual control signal corresponding to each error signal, and obtaining an actual controller and an adaptive law; according to the actual self-adaptive controller, event triggering conditions are designed, when the event triggering moment is reached, the event triggering conditions containing input are triggered, and information transmission and response are carried out. An event triggering mechanism is designed, the number of times of control instruction transmission is reduced, communication resources are saved, and rapid convergence and safe operation of the system state are achieved.

The invention discloses an engineering system fault-tolerant tracking control method based on data driving, and belongs to the technical field of engineering control methods. Comprising the following steps: S1, establishing an engineering system equivalence model under a fault, and defining a performance index function and a corresponding value function so as to convert an optimal control problem into a zero-sum game problem; s2, aiming at the problem that the state of the engineering system is unmeasurable, reconstructing the state by utilizing historical input and output data so as to design and solve an optimal control strategy; and S3, introducing and defining a Q function, designing a controller gain and a disturbance gain # imgabs0 #, and optimizing the # imgabs1 # in combination with a designed model-free non-strategy Q-learning output feedback algorithm to obtain an optimal controller. Through an injection molding industrial process and a depth control simulation experiment of an autonomous underwater vehicle (AUV), convergence of the algorithm and an excellent tracking control effect of a designed controller are verified.

The invention provides a command control structure control plane architecture design method based on software definition. The method comprises the following steps: step 1, inputting service resources and deploying communication resources; 2, designing a control structure; step 3, designing control information content; and 4, designing a control interface. Service resources needing to be controlled and available communication resources in a command control structure serve as input, logic control relations and physical link relations between controllers and resources and between the controllers are designed in multiple centralized and peer-to-peer control modes, and a control structure is formed. A control structure mathematical representation model and a control structure characteristic evaluation model are established, the robustness, the high efficiency and the comprehensive quality of the control structure can be quantitatively calculated, control information content, formats and interfaces in multiple control modes are designed, state perception, function configuration and service information flow definition of a control plane to resources are achieved, and the control structure is more accurate and reliable. Therefore, generation of the command control structure capability is guaranteed.

A non-strategy output feedback optimal tracking control method for a time-delay industrial process with unknown interference belongs to the field of advanced control of industrial processes, can overcome the problem that a conventional time-delay process control method excessively depends on a system model, and specifically comprises the following steps: step 1, describing a time-delay space expression form with interference, introducing a state increment and an output error to establish a new augmentation model; 2, introducing a time delay performance index, and designing a control strategy; 3, proposing a Q learning algorithm with fault-tolerant performance under a time delay condition, and solving an optimal control gain through continuous learning; according to the method, the optimal controller gain matrix can be found through continuous learning under the condition that a system accurate model is unknown, and a system output track can well track an expected value and achieve a good control effect under the condition that the system has state time delay and unknown interference.

The invention discloses a cross-scale decomposition and control method for an electro-hydraulic servo macro-micro rigid-flexible multi-body system, and belongs to the technical field of intelligent control. The invention aims to research a cross-scale decomposition and control method for an electro-hydraulic servo macro-micro rigid-flexible multi-body system based on a trajectory tracking control law of self-adaptive dynamic programming and a three-parameter four-scale singular perturbation decoupling problem for the electro-hydraulic servo macro-micro rigid-flexible multi-body system with uncertainty and variable load. The dynamics of the electro-hydraulic servo macro-micro rigid-flexible multi-body system mechanical arm is decomposed for three times, and then a slow-varying subsystem rigid motion controller, a secondary slow-varying subsystem flexible vibration controller, a secondary fast-varying subsystem micro mechanical arm controller and a fast-varying subsystem hydraulic controller are designed; and finally, combining all the controllers according to a multi-time scale theory to obtain a combined controller. According to the invention, a complex system can be greatly simplified, and the respective design of the controller is more practical.

The invention relates to the technical field of nuclear power plant system design, in particular to a nuclear power system design drawing generation method and device, electronic equipment and a storage medium. According to the nuclear power system design drawing generation method provided by the embodiment of the invention, design control demand data of a target nuclear power control system is acquired; performing control key point analysis based on the design control demand data to obtain target control key point data; performing schematic diagram construction on the target nuclear power control system according to the target control key point data to obtain a target system schematic diagram; in response to a condition that the target system schematic diagram meets a system principle verification condition, performing application diagram construction on the target nuclear power control system according to the target system schematic diagram and the target control key point data to obtain a target system application diagram; and in response to the condition that the target system schematic diagram meets the system application verification condition, determining the target system application diagram as a target system design diagram of the target nuclear power control system. Therefore, the efficiency of generating the design drawing of the control system of the nuclear power plant can be improved.

The present invention discloses a control method and system for modular design of a power distribution unit of an intelligent power distribution cabinet, belonging to the technical field of design control; an environment perception functional area, an intelligent control functional area and a power regulation functional area are set for the power distribution unit of the intelligent power distribution cabinet; the environment perception functional area acquires temperature data and humidity data; the intelligent control functional area controls the operation of components in the intelligent power distribution cabinet and adjusts the optimal temperature and humidity range; calculates the power generated by the components during operation; calculates the comprehensive current data and comprehensive voltage data of the components; based on the comprehensive current data and comprehensive voltage data, calculates the comprehensive power and operation influence degree of the components; preset thresholds, analyzes and outputs early warnings to the intelligent control functional area. The present invention optimizes the energy utilization efficiency, improves the safety and reliability of the system through dynamic regulation and intelligent early warning, and at the same time has good scalability and adaptability, and can meet the requirements of modern intelligent power systems.

The invention provides a sewage treatment process adaptive neural network control method with time-varying asymmetric constraints, is used for a sewage treatment process with unknown parameters, and belongs to the technical field of urban sewage treatment process intelligent control. A controller is designed by adopting a self-adaptive control method, and the concentration of dissolved oxygen and the concentration of nitrate nitrogen in the sewage treatment process are accurately controlled. Firstly, due to the fact that the fuzzy neural network has excellent robustness, unknown dynamics appearing in a sewage treatment plant can be effectively approached. Secondly, control input is designed by constructing a time-varying asymmetric obstacle type Lyapunov function, and a fault-tolerant control method is designed in consideration of an actuator fault condition. And finally, performing a simulation experiment by using the reference simulation model 1, and verifying the effectiveness of the proposed method by a simulation result.

A spacecraft attitude preset performance control method based on an improved preset finite time function comprises the following steps: step 1, determining a control object and a control target according to a motion law of a spacecraft: designing a control law so that the control object and the control target are controlled under the influence of saturation factors of an execution mechanism; a spacecraft system attitude quaternion error vector part qev and an angular velocity error We of a spacecraft body coordinate system track an expected signal; 2, constructing a class sliding mode variable S, a self-adaptive boundary preset finite time function and auxiliary variables e and v; 3, designing a control law to enable the variable S to move in an envelope formed by a preset finite time function # imgabs0 #; and 4, checking and improving the performance of the preset finite time controller. According to the method, the problem of singularity easily occurring when an existing preset finite time control method faces internal and external interference and the problem that the angular velocity is too large in the large-angle maneuvering process are solved, meanwhile, the actual physical limitation of an executing mechanism is considered, and it can be guaranteed that higher reliability is obtained.

The invention relates to a mechanical arm actuator fault tolerance control method based on sliding mode control and a neural network, and belongs to the field of industrial robots. The method comprises the steps that modeling is conducted on the fault condition of a mechanical arm actuator, and a fault model is established; defining a joint angle tracking error, designing a sliding mode controller, and establishing a sliding mode surface of the sliding mode controller as linear sliding; designing a mechanical arm dynamic form according to the linear sliding surface and the fault model; estimating a total dynamic item by adopting an RBFNN neural network to obtain an estimated value of a system dynamic item, and taking the estimated value as an output quantity of the RBFNN neural network; designing a control law; calculating and generating a corresponding control input quantity according to a control law by adaptively updating a fault matrix of the weight matrix; and the mechanical arm actuator controls the mechanical arm according to the control input quantity so as to achieve fault compensation. According to the method, high-precision trajectory tracking is achieved under the condition that dynamics and actuator faults are unknown, and an accurate fault model or a fault detection system is not needed.

To accurately identify a parameter of a vehicle body motion model to be used in designing a controller that controls air supply and exhaust to air springs so that an inclination angle of the vehicle body of a railroad vehicle follows a target angle.SOLUTION: A control design device comprises a waveform acquiring unit that acquires, for each of a plurality of air supply / exhaust conditions, a time series waveform representing the motion of a vehicle body when an air supply / exhaust command to supply / exhaust a certain amount of air to / from an air spring on either side is input to an air supply / exhaust device, a model parameter acquiring unit that acquires parameters of a vehicle body motion model that is identified so that the frequency transfer characteristic of the transfer function estimated on the basis of the combination of the acquired time series waveform and the air supply / exhaust command corresponds to the frequency transfer characteristic of the vehicle body motion model that models the body motion of a railroad vehicle, for the worst air supply / exhaust condition among the plurality of air supply / exhaust conditions, and a control design unit that designs a controller by using the vehicle body motion model having the acquired parameters.SELECTED DRAWING: Figure 5

The invention discloses a long flexible blade reduced scale model design method suitable for a large fan wind tunnel experiment. The method comprises the following steps: selecting a reasonable similarity criterion, selecting a section airfoil of a model blade, optimizing the distribution of chord length and torsion angle in the length direction of the blade, and optimizing a model rotor variable pitch control strategy; the design objectives that the thrust coefficient of the reduced-scale model rotor in the experimental wind speed range is equal to that of the original-size fan rotor in the corresponding original-size wind speed range, and the first-order inherent frequency in the flapping and shimmy directions of the blades of the reduced-scale model is equal to that of the original-size blades are achieved, and the long flexible blade reduced-scale model is provided for a large-scale fan wind tunnel experiment. According to the method, the first-order inherent frequency of the flapping and shimmy directions of the model blade and the blade of the original size is equal, the thrust coefficients are equal under multiple working conditions, the wind tunnel experiment similarity criterion is met, different airfoil choices are appointed for different design control sections, and the method has high optimization solution efficiency.

The invention discloses a fault compensation and H-infinity fault-tolerant tracking control method for an autonomous underwater vehicle, and belongs to the technical field of engineering control methods. Comprising the following steps: S1, aiming at actuator faults, sensor faults and external disturbance problems in vertical plane motion of an autonomous underwater vehicle, introducing a depth variable and establishing a high-order all-drive fault model; s2, designing an intermediate estimator based on a high-order all-drive model, and realizing estimation of a system state and a fault; and S3, designing a controller based on the high-order all-drive model, solving a game Riccati equation by using a Minmax method, obtaining an optimal control strategy, and realizing fault compensation and external disturbance suppression. The effectiveness of the method and the excellent tracking control effect of the designed controller are verified through a depth control simulation experiment of the autonomous underwater vehicle.

The invention provides a design and application method of a sliding-mode deadbeat reaching law, and relates to the technical field of electrical engineering, and the method comprises the steps: designing a sliding-mode deadbeat reaching law SMDRL, designing a control strategy through a deadbeat control principle, defining a state change law on a sliding-mode surface through a sign function, and achieving the design of the sliding-mode deadbeat reaching law SMDRL. It is ensured that the system state converges to the sliding mode surface at the fastest speed in a control period; an improved sliding mode deadbeat reaching law ISMDRL is designed, a traditional sign function is replaced with a hyperbolic tangent function, and parameters of the hyperbolic tangent function are adjusted according to the system state; the SMDRL and the ISMDRL are applied to a speed driving system of a permanent magnet synchronous motor (PMSM), and the speed driving system comprises a PMSM mathematical model, a sliding mode speed controller with a speed disturbance observer and model prediction current control. The SMDRL is introduced from the traditional sliding mode reaching law for the first time through theoretical derivation, the convergence time of the SMDRL is the shortest, and the SMDRL is applied to a permanent magnet synchronous motor speed driving system.

The invention relates to a subcritical unit load real-time control method based on multivariable model predictive control. The subcritical unit load real-time control method comprises the following steps: S1, establishing a time sequence prediction model of subcritical unit power generation load and main steam flow based on an LSTM model; s2, on the basis of the data predicted in the S1 and historical operation data, working condition online identification and load section division are firstly carried out, then state-space equations of different load sections of the subcritical unit are identified in real time by using a least square method, and a multi-section linear state-space equation set is established; and S3, designing a controller based on the multi-stage state space equation set in the S2, performing optimization solution through quadratic programming to obtain the optimal control quantity at the future moment, correcting the current actual control quantity in advance, and improving the load response rate. The method can effectively improve the load response characteristic of the unit and improve the economic performance of the unit, is suitable for large-range working condition changes, and meets the peak regulation and frequency modulation requirements.

The invention discloses a modeling and closed-loop displacement control method for a shape memory alloy driver, and the method comprises the steps: taking an inverse hysteresis feed-forward compensation and SMC-PID feedback displacement control method as a core, building a positive model of the shape memory alloy driver, carrying out the inversion to obtain an inverse model, designing a self-adaptive SMC-PID feedback controller, and carrying out the closed-loop displacement control of the shape memory alloy driver. Combining the positive model, the inverse model and an SMC-PID feedback controller to construct a control system for closed-loop displacement control of the shape memory alloy driver; matlab / Simulink software is used for carrying out modeling simulation testing on the designed control system, and the closed-loop displacement control effect of the shape memory alloy driver is observed by selecting different tracking signals. The modeling and closed-loop displacement control method for the shape memory alloy driver has an excellent control effect under various motion working conditions such as back-and-forth reciprocation, continuous heating deformation and continuous cooling deformation of the shape memory alloy driver, is high in tracking precision and small in delay, and realizes high robustness for system delay and parameter uncertainty.

The invention provides a plasma virtual control surface and control mechanism control distribution method for reentry flight of a high-speed aircraft. The method comprises the following steps: firstly, determining that the aircraft enters a reentry flight stage; secondly, the needed torque is calculated according to an attitude controller; then designing control distribution models of a plasma active flow control system, a pneumatic control surface control mechanism and an RCS backstepping control system based on a depth deterministic strategy gradient reinforcement learning algorithm; and the high-speed aircraft completes reentry flight based on the control distribution parameters obtained by the control distribution model. Auxiliary control is achieved through the plasma jet, and a new way is provided for accurate control over the aircraft. According to the method, control means can be reasonably distributed according to the early stage, the middle stage and the later stage of reentry flight, and relevant parameters of all control systems are determined. The reinforcement learning algorithm is used for processing the nonlinear characteristics of the input power and control output of the plasma exciter and the nonlinearity and uncertainty of aerodynamic characteristics in an attitude control model, the stability of a control system can be improved, and the method has a good application prospect.

This invention provides a low-computational-complexity, pre-set performance-tolerant control method for steer-by-wire systems. The control method includes: determining the control objective based on a pre-set performance control method; subsequently designing a new pre-set performance function and error transformation function; designing virtual control laws and control laws in the controller using a robust control method; establishing a dynamic model of the steer-by-wire system based on system dynamics; establishing a dead-zone model and a fault model based on the impact of dead zones and faults in the vehicle actuators on the control performance of the steer-by-wire system; simultaneously obtaining the input nonlinear model of the steer-by-wire system; subsequently establishing a state-space model of the steer-by-wire system; and finally, verifying the controller's control effect and optimizing its internal parameters using the state-space model. This invention considers fault and dead-zone issues, improving the robustness of the controller; and considers the limited computational resources of the vehicle, with a simple controller structure that improves the overall computational efficiency of the vehicle.

The invention discloses a carrier rocket test-launch process refined information management and control system based on a handheld terminal. The system comprises a decision-making area, a design management and control area and a test-launch execution area. From the perspective of converting files into data information transmission, a new process management and control design method and concept are adopted, carrier rocket launching site process information management and control design is carried out, a hierarchical management and control framework of different professional systems is established through a modularization method according to a launching site process operation mode, an information transmission management mode in refined management and control is constructed, and the management and control efficiency is improved. Unified management and template process scheme design in process management and control are realized, and the design scheme is implemented in a handheld terminal. Flow design work and result and state check and confirmation are completed among the stages through a handheld terminal, refined management and control of work flow information of a carrier rocket in a launching site are achieved, the test launch execution efficiency and reliability of a carrier rocket launching task are improved, and high-quality launch task completion is achieved.