1059 results about "Performance control" patented technology

The invention relates to a vehicle queue cooperative control method fusing deep reinforcement learning communication time delay compensation, and belongs to the technical field of intelligent vehicle control. For the problems of control error accumulation and queue instability caused by communication time delay in the vehicle-road cloud cooperative system, a solution integrating deep reinforcement learning prediction and preset performance control is provided. According to the technical scheme, the method comprises the following steps: constructing a vehicle state prediction model based on a DDPG algorithm, and generating a time delay compensation amount in real time; establishing a vehicle dynamics model containing communication time delay, and designing a sliding mode controller based on a barrier function; and dynamically adjusting the control constraint in combination with an adaptive error boundary mechanism. According to the method, through closed-loop fusion of prediction compensation and dynamic constraint, under the scene of burst communication delay (100-400 ms), the queue spacing error is reduced by 62%, the speed tracking error is still kept to be smaller than 0.3 m / s, and the queue stability and the anti-jamming capability are remarkably improved.

The invention discloses a six-rotor unmanned aerial vehicle control method and system with disturbance and performance constraints. The method comprises the steps that 1, a six-rotor unmanned aerial vehicle power model is built; 2, errors are determined based on the dynamic model, functions are combined, and a finite time scheme is determined; step 3, based on the dynamic model, establishing an observer, and knowing a disturbance state; step 4, a performance control scheme and an unknown disturbance state are stipulated in finite time, an error dynamic model is established, and the error dynamic model is established based on reinforcement learning; 5, setting a base scheme, setting a virtual controller and an actual controller, and setting an adaptive law for the base neural network; 6, the controller follower can track the leader, and tracking control is completed; establishing a controller by adopting a backstepping method, establishing a disturbance observer, and compensating negative effects; a reinforcement learning algorithm and a backstepping method technology are combined, and a controller is arranged to realize control; according to the method, the stability is proved by using a Lyapunov judgment stability theory, and the feasible effectiveness is verified by a simulation example.

The invention provides a mechanical arm predefined time trajectory tracking control method and system based on time delay estimation, and relates to the technical field of multi-degree-of-freedom mechanical arm trajectory tracking control. Constructing a predefined time error conversion function to define a system error and conversion error system, designing a barrier function and a feedback control rate based on the conversion error system, and designing a Lyapunov function to prove the stability of the system so as to track an expected trajectory; according to the method, time delay information is deeply fused, dependence on a complex model approximate structure is not needed, stable convergence of the mechanical arm system state within predefined time can be achieved when a mathematical model is not accurate, the system control performance and robustness are effectively improved, and the requirement of modern industry for mechanical arm high-performance control is met.

The invention relates to the field of motor control, and discloses a permanent magnet synchronous motor enhanced active-disturbance-rejection control method based on a superhelix control law, which comprises the following steps of: firstly, establishing a permanent magnet synchronous motor mathematical model by considering load disturbance, current sampling disturbance and flux linkage parameter change disturbance in actual motor operation; according to the mathematical model of the permanent magnet synchronous motor and the mathematical characteristics of the active disturbance rejection controller, constructing an observer equation by using a differential relationship, and solving the problem of observation error accumulation through the differential relationship; a lumped disturbance compensation function is introduced into the observer, the anti-interference capacity of the control system is enhanced, and decoupling of steady-state and dynamic performance control parameters is achieved; and finally, designing a state error feedback control law by adopting a super-spiral sliding mode control law, so that the anti-interference capability of the active-disturbance-rejection controller is further improved, and the inherent buffeting of the system is weakened. A simulation result shows that compared with a traditional PI control method, the control method has better dynamic response performance and anti-interference performance.

The invention relates to a multi-robot system global flexible preset performance control method under an unknown state and a DoS attack, and belongs to the technical field of multi-robot system control. Aiming at the problems in the prior art that the communication topology is unstable due to attack, the initial error constraint is strict, and the input saturation conflicts with the performance, the following scheme is provided: dynamically reconstructing the attacked communication topology based on a bipartite consensus layering algorithm; designing a global error constraint mechanism fusing the scale function and the tunnel type performance function; constructing a balance control input and performance boundary of the input saturation self-adaptive auxiliary system; and estimating an unknown state and compensating an observation error by adopting a state observer. The method has the technical effects that the DoS attack resistance of the system is enhanced, the global preset performance control of any initial error is realized, the contradiction between input saturation and tracking performance is dynamically coordinated, and the multi-robot collaborative operation under the unbalanced topology is supported.

The invention provides a fault-tolerant control method for preset performance of a morphing aircraft based on sliding-mode control. The fault-tolerant control method comprises the following steps: establishing a longitudinal nonlinear dynamic model of the morphing aircraft; based on the longitudinal nonlinear dynamic model of the morphing aircraft, establishing a longitudinal nonlinear dynamic model of the morphing aircraft under the fault condition of the execution mechanism; the method comprises the following steps: extracting a speed subsystem and an attitude subsystem aiming at a longitudinal nonlinear dynamic model of a morphing aircraft under an execution mechanism fault condition; carrying out sliding-mode control-based preset performance fault-tolerant controller design on the attitude subsystem; aiming at a speed subsystem, combining an attitude subsystem controller, and carrying out sliding mode control-based preset performance fault-tolerant controller design; the two designed controllers are utilized to realize the fault-tolerant control of the variant aircraft under the condition of executing mechanism fault. The sliding mode control and the preset performance control are combined, so that the conservative property is improved by quick response, the fault-tolerant capability is enhanced by switching the control law, and the stability is improved.

The invention discloses a reinforcement learning-based quadrotor unmanned aerial vehicle attitude preset performance control method, which comprises the following steps of: establishing an unmanned aerial vehicle attitude kinetic equation by considering a time-varying inertial parameter and external unknown interference; a sub-channel preset performance controller is constructed, and a robust control quantity is generated in combination with preset performance and a non-singular fast terminal sliding mode control technology; designing a reinforcement learning parameter generator, and dynamically optimizing 12 time-varying parameter estimated values through a time sequence feature extraction network and a residual network; and establishing an online reinforcement learning training mechanism, constructing a multi-target reward function, and optimizing the output of the parameter generator through the multi-target reward function. According to the method, a reinforcement learning method is adopted to replace a traditional self-adaptive method to estimate time-varying parameters, multi-degree-of-freedom decoupling optimization is achieved through a sub-channel control architecture, tracking error preset performance constraint is achieved under the working condition of time-varying inertial parameters, and the dynamic adjustment capacity and anti-interference robustness of an attitude system are remarkably improved.

To provide a game machine equipped with main control-performance control means for improving amusement properties of a game.SOLUTION: In a game machine of the present invention, main control means is capable of counting the number of winning game balls in an open state of a big winning port, and controlling the big winning port to a closed state when the number of winning game balls reaches a predetermined number, and transmitting a big winning port winning command (not including count information on the number of winning game balls) based on the entry of a game ball into the big winning port to performance control means. The performance control means performs counting different from that of the main control means according to the big winning port winning command, and can display a result of the counting.SELECTED DRAWING: Figure 44

The invention discloses an unmanned agricultural machine path tracking preset performance control method and system, and the method comprises the steps: collecting the pose information of an unmanned agricultural machine, building an unmanned agricultural machine path tracking error kinematic model, and designing a finite time preset performance function based on the unmanned agricultural machine path tracking error kinematic model. The constraint is converted through nonlinear mapping; based on the Lyapunov stability theory, adopting a backstepping method to recursively design an actual control law, and according to the actual control law, performing inverse transformation on the input of the unmanned agricultural machine tracking control system in the error kinematics model of the unmanned agricultural machine tracking control system to obtain the front wheel steering angle of the unmanned agricultural machine. According to the method, convergence is completed within finite time, and transient control performance and steady control performance of a path tracking control system are considered.

The invention discloses an intelligent adaptive fault-tolerant control method for an aircraft. According to the method, the extended state observer with fixed time convergence is designed to obtain the lumped disturbance including the fault influence, the design of the super-spiral sliding mode controller is completed under the preset performance control framework, and the compensation of the total disturbance is generated by means of the good robustness of the sliding mode controller and in combination with the observer. The influence of aircraft faults on a control system is effectively reduced, the preset performance super-spiral sliding mode controller can realize rapid and accurate tracking of a control instruction in a short time, overshoot and oscillation in the control process are reduced, and the influence of buffeting of a traditional sliding mode algorithm on the aircraft control system is reduced; meanwhile, a reinforcement learning agent is designed to carry out online self-adaptive adjustment on parameters of the super-spiral sliding mode controller with the preset performance, so that performance reduction of the controller caused by various sudden faults which occur randomly and have random fault types is dealt with, and the influence of the faults on aircraft tasks is reduced.

The invention provides a distributed driving vehicle preset performance fault-tolerant control method and system based on an adaptive neural network observer. The method comprises the following steps: constructing a vehicle dynamics model containing motor faults and unknown disturbance; in order to realize real-time estimation of faults and disturbance and break through the limitation on disturbance derivative boundaries, a self-adaptive neural network observer is designed; aiming at the problem that the control direction is uncertain, an upper-layer controller is designed based on a preset performance control theory, a Nussbaum function and an obstacle Lyapunov function are introduced, it is ensured that system dynamic errors meet preset performance constraints all the time, and accurate tracking control over the transverse force, the longitudinal force and the yawing moment of a vehicle is achieved; in order to improve the system coordination capability under the multi-motor fault working condition, an optimal torque distribution model fusing the motor torque constraint and the tire force limit is constructed, collaborative optimization control of the driving and steering system is realized through a quadratic programming algorithm, and the stability and safety of the whole vehicle in the fault state are improved.

The invention discloses a permanent magnet synchronous motor parameter optimization method based on an improved moth flame particle swarm algorithm. In order to solve the problems that a traditional PID controller is difficult in parameter setting, poor in adaptability, insufficient in control precision and the like under complex working conditions, in the strategy, an MFPSO algorithm fuses a particle swarm optimization (PSO) algorithm and a moth flame optimization (MFO) algorithm. An adaptive inertia weight and Gaussian mutation strategy is introduced, so that particles can focus on local fine search, and the speed of convergence to an optimal solution is accelerated. The optimization capacity of the algorithm in different stages is enhanced by adopting a nonlinear acceleration coefficient, and local optimum is effectively avoided. A grouping evolution mechanism is designed to promote intra-group information sharing and inter-group competition, the population diversity is enriched, and the ability of the algorithm to jump out of a local optimal solution is further improved. The fuzzy PID controller based on the MFPSO algorithm optimization parameters can better meet the requirements of high-performance control of permanent magnet synchronous motors in different fields, and has application prospects and economic values.

The invention relates to an optimal cooperative control method for preset performance of multiple intelligent vehicles under a non-convex input constraint, and belongs to the technical field of multi-agent cooperative control. The problems that non-convex input constraint processing is conservative, preset performance and optimal control are designed separately, and the timeliness of a traditional method is insufficient are solved. Designing a non-convex constraint operator to directly map, control and input to a feasible direction extreme value; constructing a distributed preset time observer to realize accurate estimation of the state of the leader; preset performance control is converted into an optimal control problem in combination with a time-varying performance function and error conversion; and solving an HJB equation based on a reinforcement learning iterative algorithm to approach an optimal control law. The conservative property of a traditional convex approximation method is broken through, and it is ensured that control input strictly meets the non-convex constraint; eliminating time uncertainty through preset time observation; fusing preset performance and optimal control to realize multi-target collaborative optimization; the reinforcement learning algorithm has global convergence and real-time performance, and is suitable for multi-vehicle cooperative control in a complex dynamic environment.

The invention belongs to the technical field of spacecraft attitude control, and discloses a spacecraft attitude preset performance control method and equipment, and a computer storage medium. The method comprises the following steps: S1, establishing a spacecraft error attitude dynamics and kinematics model considering unknown bounded input time delay; s2, constructing a preset performance function, and performing preset performance constraint on the attitude error of the spacecraft through the preset performance function; introducing an error conversion function, and converting a constrained attitude error into an unconstrained error; performing state conversion on the spacecraft error attitude dynamics and kinematics model to obtain a spacecraft error attitude dynamics and kinematics model related to state variables; and S3, designing a preset performance control law based on the tracking error variable, so that the attitude error moves in a preset performance function envelope. According to the method, errors caused by unknown bounded input time delay can be compensated, and meanwhile, the steady-state and transient-state performance of spacecraft attitude control can be met.

The invention discloses an electro-hydraulic system adaptive neural network preset time control method, which integrates a neural network real-time learning technology, innovatively introduces a preset time performance function, and designs an adaptive neural network preset time performance controller. For the electro-hydraulic system position tracking control problem, it can be ensured that system output transient performance and steady-state performance converge to a specified performance index range within a preset time, safe and reliable operation of the system is ensured, the unknown dynamic state of the system can be learned in real time through a neural network, high-precision motion control performance is achieved, and the control precision is improved. And the problem of differential explosion in traditional backstepping control of the electro-hydraulic system can be avoided, and the influence of measurement noise on the control precision is reduced.

The embodiment of the invention discloses a voice coil motor fast reflector generalized internal model control method and device and a medium, belongs to the technical field of voice coil motor fast reflectors, and solves the problem that the performance of a controller is reduced due to perturbation of system parameters. Comprising the following steps: analyzing input and output data of the voice coil motor fast reflector system to obtain a corresponding nominal model; and performing loop shaping on the nominal model through a pre-compensator, and performing loop shaping controller calculation based on a standard H-infinity control algorithm to obtain a performance controller. The additive uncertainty of the nominal model and the model under the real working condition is determined, and an upper bound function corresponding to the additive uncertainty is obtained through curve fitting. And performing iterative processing on the preset controller to obtain a robust controller. And based on the performance controller and the robust controller, solving to obtain an inner ring controller so as to realize generalized internal model control of the voice coil motor fast reflector.

The invention belongs to the technical field of EL system control, and discloses a preset performance control method considering dynamic and constraint of an execution mechanism. The method comprises the following steps: firstly, establishing a system dynamics model considering dynamic and input saturation constraints of an executing mechanism; then, designing an asymmetric tubular performance boundary to restrain a system tracking error, and defining a conversion error according to the system tracking error; meanwhile, a disturbance observer based on immersion and invariance is designed, and composite disturbance is estimated. Furthermore, a tubular preset performance controller is designed by adopting a backstepping method, a virtual control law and an expected torque are constructed, and a multi-state auxiliary system is introduced to compensate the input saturation influence. And finally, a control instruction is generated by integrating the auxiliary system state, the virtual control law, the expected torque and the interference estimation value, and the control instruction acts on the system after being processed by a saturation function. According to the method, actuator dynamics, input saturation and external disturbance can be processed at the same time, and tracking errors are ensured to strictly follow a preset performance boundary.

The invention relates to a mechanical arm control method combining interactive DAgger and reinforcement learning. The mechanical arm control method comprises the following steps that 1, states are collected and preprocessed; step 2, initializing a unified policy network; step 3, interactive DAgger selective expert intervention is carried out; 4, environment interaction and experience storage; step 5, mixing loss calculation; step 6, updating the unified strategy network, and dynamically adjusting the dynamic weight; and 7, the steps are repeated until the performance of the unified strategy network is converged, and the final control action of the mechanical arm is output. According to the method, imperfect and non-optimal guidance of experts can be effectively utilized to accelerate the initial learning process and ensure the safety, meanwhile, the intelligent agent can autonomously learn and improve from interaction with the environment in combination with the self-exploration and optimization capability of reinforcement learning, and finally, a high-performance control strategy exceeding the original teaching level of the experts is obtained, so that the safety of the intelligent agent is improved. And the dependence on continuous and intensive intervention of experts is obviously reduced in the process.

The invention discloses a performance control method of a limited nonlinear information physical system, which belongs to the technical field of intrusion tolerance control of information physical systems, and comprises the following steps of: establishing a control-oriented dynamic model of the limited nonlinear information physical system with external disturbance under spoofing attack; mathematical characterization is carried out on bounded multiplicative and additive spoofing attacks; a Lyapunov function based on a preset performance control method is constructed, and a system stability determination method based on a Nusb inequality is given; and coordinate change is introduced to meet full-state constraint, and a fixed time controller is designed by using a backstepping method, so that preset performance control of the limited nonlinear information physical system under spoofing attack and external disturbance is realized. The invention develops a fixed time intrusion tolerance controller based on a preset performance method, which can ensure the stable operation of a limited nonlinear information physical system under a spoofing attack with a small tracking error.

The invention relates to an automobile finite time path tracking fault-tolerant control method considering steering actuator faults. The method comprises the following steps: firstly, establishing a vehicle dynamics model and a steering execution mechanism dynamics model, designing a path tracking control strategy by applying a model prediction control method, and establishing an upper-layer path tracking controller; then, on the basis of a differential driving auxiliary steering principle, a preset performance control method of finite time convergence and a nonsingular fast terminal sliding mode control theory are combined, and a steering actuator fault-tolerant controller is established; and finally, designing a torque distribution controller by adopting an optimal control theory, and solving an optimal four-wheel driving torque control quantity through quadratic programming. According to the method, the influence caused by the failure of the steering actuator can be effectively compensated, the safety and the stability of the vehicle are remarkably improved, and a feasible solution is provided for the fault-tolerant control of the steering actuator in a future intelligent vehicle path tracking scene.

The invention relates to an intelligent optimization method and system for BOPP film making process parameters, and the method comprises the following steps: obtaining historical data of BOPP film making, including process parameters and corresponding product performance data; constructing a product performance control model by taking the process parameters as input and the product performance data as output, formulating a control strategy according to requirements, and solving to obtain a first process parameter through a multi-objective optimization algorithm; preparing a BOPP film by using the first process parameter, and obtaining equipment operation data; constructing an equipment operation control model by taking the first process parameter as input and the equipment operation data as output, and solving to obtain a second process parameter; and producing the BOPP film by using the second process parameters. According to the intelligent optimization method and system for the BOPP film manufacturing process parameters, the process parameters of two dimensions of product performance and equipment operation are optimized, so that the optimal operation state of the equipment is kept to the greatest extent while high product quality is ensured.

The invention belongs to the technical field of parameter estimation of machines, and particularly relates to a permanent magnet synchronous motor parameter identification method based on an improved eel-grouper algorithm. The method comprises the following steps: establishing a full-rank discrete voltage equation set of a mathematical model of a PMSM under a dq coordinate system; constructing a fitness function reflecting an error between an actual parameter output value and a theoretical output value of the motor; performing parameter identification on the permanent magnet synchronous motor by using an improved eel-grouper optimization algorithm, and initializing a population by using an elite reverse learning mechanism; a Levy flight strategy is introduced in the algorithm development stage; introducing a reconnaissance alert strategy of a sparrow search algorithm; a chaotic Tent search strategy is introduced, a fitness function is calculated, parameter optimization is carried out through algorithm iteration, iteration is stopped after the maximum number of iterations is reached, and optimal identification parameters are output. By improving a search strategy and a parameter adjustment mechanism of the algorithm, the precision and robustness of parameter identification are further improved, and more reliable parameter support is provided for high-performance control of the permanent magnet synchronous motor.

This prevents the system from inferring that the setting has been changed. [Solution] The performance control means executes a first performance related to a specific benefit when a specific benefit is granted, does not execute the first performance when a specific benefit is not granted in response to being operated in a second operation mode, does not execute the first performance when the stop switch is operated in a second operation mode in a non-advantageous section and a specific benefit is granted in the next game, does not execute the first performance, may execute a second performance when the stop switch is operated in a second operation mode in a non-advantageous section, may execute a second performance when the stop switch is operated in a second operation mode in an advantage section, and performs performances through multiple layers including a first layer and a second layer different from the first layer, the first performance and the second performance are different performances and are executed on layers different from the first performance and the second performance.

The invention provides a serdes chip performance control parameter optimization method and device, and the method comprises the steps: setting the value ranges of all configuration parameters of a preset configuration type in a serdes chip, and generating an initial particle swarm according to each configuration parameter and the corresponding value range; inputting the initial particle swarm as an input particle swarm into a first round of iteration; each round of iteration comprises the steps of inputting each particle in the input particle swarm into a corresponding serdes chip, obtaining an eye diagram corresponding to each particle, and obtaining a target value corresponding to each particle according to the eye diagram corresponding to each particle; obtaining the maximum target value in all particles in the input particle swarm as a local optimal value, and obtaining the local optimal value with the maximum target value in all current iteration rounds as a global optimal value; and after the termination condition is met, the optimal configuration parameter of the serdes chip is obtained, so that the optimization efficiency and the channel compensation performance are improved.

This prevents the system from inferring that the setting has been changed. [Solution] The performance control means executes a first performance related to a specific benefit when a specific benefit is granted, does not execute the first performance when a specific benefit is not granted as a result of the operation in the second operation mode, does not execute the first performance when the stop switch is operated in the second operation mode during a non-advantageous section and a specific benefit is granted in the next game, performs performances through multiple layers including a first layer and a second layer which is a higher layer than the first layer, executes the first performance in the first layer and executes a second performance which is different from the first performance in the second layer, and makes the execution timing of the first performance and the execution timing of the second performance different.

The invention relates to a sensorless high-performance control method for an oil pump motor in a low-speed domain. The sensorless high-performance control method comprises the following steps: step 1, building a high-frequency signal injection model; based on a traditional permanent magnet synchronous motor model, a high-frequency mathematical model of the oil pump under a d-q axis system is derived, and the relation between q-axis high-frequency response current and the angle error is obtained; step 2, random amplitude and frequency signal injection; obtaining q-axis high-frequency response current based on a high-frequency response current equation and the injected voltage signal with random amplitude and frequency; 3, performing signal demodulation based on an adaptive filtering algorithm to obtain an angle error signal; and step 4, after the rotor position error signal is extracted in the step 3, realizing rotor position observation through a PI observer. The noise caused by fixed frequency injection can be greatly reduced in the low-speed domain state of the oil pump motor; and secondly, a target signal can be accurately extracted to participate in closed-loop control or rotor position observation, so that the control performance is improved.

The invention relates to the technical field of vehicle supercharging control, in particular to a supercharger performance control method and device of a hybrid power system and a vehicle. The method comprises the steps that a plateau ignition angle MAP table and a plateau air inlet VVT angle MAP table of the vehicle in a high altitude mode are obtained; a plateau air inlet VVT angle MAP table is corrected, meanwhile, the knocking thrust angle condition of the hybrid power system is checked, and the maximum performance of a current supercharger is determined so as to correct the exhaust gas recirculation rate; calibration limits are generated based on at least part of detonation, preignition, the highest rotating speed of turbine hardware, the combustion center of gravity, the combustion boundary and the HCU series-parallel economic line, and comprehensive test check is conducted based on the calibration limits so that performance optimization can be conducted on the engine. Therefore, the problems that in the related technology, due to the fact that the performance and the response speed of the supercharger in the plateau area are reduced, the actual torque of an engine cannot meet the requirement of a hybrid power system, and then the series-parallel connection switching and electricity protection capacity of the vehicle is affected are solved.

The invention relates to the technical field of research and development of low-temperature bolt steel, and discloses a low-temperature impact performance control process for low-temperature bolt steel. Comprising the steps that S1, in the steelmaking refining stage, purity and uniformity control is conducted, S2, casting blank homogenization treatment is conducted, stress relief and structure regulation are conducted, S3, a heat treatment core process is conducted, structure and toughness balance regulation is conducted, and S4, online detection and dynamic feedback are conducted, and performance stability is guaranteed. By accurately controlling the element proportion of carbon (C), silicon (Si), manganese (Mn), chromium (Cr) and molybdenum (Mo) in steel and combining with an optimized heat treatment process (such as 860 DEG C oil quenching and 640-650 DEG C high-temperature tempering, and the heat preservation time is prolonged to 120 minutes or more), the V-shaped notch impact energy of the material in the environment of-101 DEG C stably reaches 35 J or more, the impact energy of part of samples can reach 50 J or more, and the impact energy of the part of samples can reach 50 J or more. The problem that the low-temperature impact performance is insufficient after wire hardening and tempering is thoroughly solved, and it is ensured that the brittle failure resistance of the bolt is remarkably improved in the ultralow-temperature environment.

To improve interest in a performance.SOLUTION: This game machine is provided with a performance control board 300 capable of executing a picture scroll mode performance for changing the display contents of a background image displayed on the back surface side from performance symbols for each variable display of the performance symbols (special symbol 1 one digit symbol a2, special symbol 2 one digit symbol a3 and picture scroll mode exclusive mini symbol). Then, with regard to the display contents of the background image which is displayed during the picture scroll mode performance, the same display contents do not overlap. That is, in the Pachinko machine 1, when executing the picture scroll mode performance in which the display content of the background image displayed on the back side of the performance symbol is changed for each variable display of the performance symbol, since the same display content is not overlapped for the display content of the background image displayed during the picture scroll mode performance, the interest of the performance can be improved.SELECTED DRAWING: Figure 51

The utility model relates to a high-performance controller device for an electric bicycle, which comprises a hollow outer wrapping body, a control module, a conductive column module and a power module are assembled in the outer wrapping body, and the bottom end surface of the power module is attached to the inner bottom wall surface of the outer wrapping body; the conductive column module structurally comprises a mounting support, a plurality of first binding posts, a plurality of second binding posts and a plurality of supporting rings are fixed to the end face of the mounting support at intervals, the first binding posts are used for being connected with a driving power source, and the second binding posts are used for being connected with a motor. The support ring is arranged between the control module and the power module so as to separate the control module from the power module. By arranging the conductive column module, the control module and the power module can be separated, so that the power module can be mounted in a manner of being attached to the inner bottom wall surface of the outer wrapping body, the layout is compact, meanwhile, the heat dissipation efficiency is improved, and the performance of the controller device is improved.