104 results about "Fuzzy sliding mode control" patented technology

The invention discloses a direct torque control system of a permanent magnet synchronous motor based on a terminal sliding mode, which belongs to the field of motor control. The system comprises a main circuit, a signal detection circuit, a rotational-speed outer-ring controller for the terminal sliding mode, a torque linkage inner-ring controller for an adaptive fuzzy sliding mode, a stator-linkage electromagnetic torque estimation module, an SVPWM module, a 3 / 2 coordinate transform module, and a rotor position / speed estimation module; the design on the rotational-speed outer-ring controller is realized by using a terminal sliding mode control method based on the adaptive estimation of load disturbance, and the rotational-speed outer-ring controller outputs direct-torque controlled demand signals; and the design on the torque linkage inner-ring controller is realized by using an adaptive fuzzy sliding mode control method, and the torque linkage inner-ring controller outputs two-phase alternating voltages in a two-phase stationary coordinate system; and through carrying out SVPWM transformation on the two-phase alternating voltages, a power switching element acted on an inverter of the main circuit implements the direct torque control of the permanent magnet synchronous motor. The direct torque control system in the invention has the advantages of quick torque response speed, good robustness, small tracking error, and capability of improving the reliability and static / dynamic characteristics of the system.

The invention relates to a modified fuzzy sliding mode controlling method of a monopole three-phase photovoltaic grid-connected system, belonging to the control technical application field of a photovoltaic grid-connected system; the method has the advantages of strong robustness, good stability and rapid dynamic response speed; the method comprises the following steps particularly: firstly, feedforward compensation is led in to rapidly compensate the coupling part of d, q shaft current id and iq which are output by an inverter, thereby realizing rapid dynamic decoupling between id and iq; secondly, by controlling reaching law of lead-in index of an integral sliding mode controller, the dynamic performance of a sliding mode controlling system is improved, the response speed of the system at the initial starting stage is accelerated, and a system state trajectory is ensured to rapidly and smoothly enter in a sliding mode surface to move, wherein the sliding mode surface has good robustness to system interference; finally, a fuzzy control is led in to weaken the buffeting of common sliding mode control in the sliding mode surface, the output of the sliding mode controller is softened, and the stability of the system is improved.

The invention relates to a multi-intelligent agent based unmanned electric car automatic overtaking system and method. The automatic overtaking system includes a vehicle-mounted sensor for acquiring front traffic information of an unmanned electric car. The automatic overtaking method includes: establishing a minimize safe distance model on the basis of feature information of a car and a surround environment thereof extracted by a vehicle-mounted sensing system and a V2X communication system; setting a sine function form as a base function of an automatic overtaking desired path, and dynamically planning an automatic overtaking desired track of the unmanned electric car in real time; adopting a self-adaption fuzzy slide mode control technique to solve the desired speed and the desired yaw velocity of overtaking of the unmanned electric car on the basis of a deviation between the desired overtaking path and an actual path; adopting a multi-intelligent agent genetic optimization algorithm to calculate out the required longitudinal and horizontal force of each wheel of the unmanned electric car; and establishing a mapping model from the longitudinal and horizontal forces of the wheels of the unmanned electric car to the desired slip angle and slip rate, and achieving execution control of the longitudinal and horizontal force of tires the unmanned electric car.

The invention discloses a micro-gyroscope tracking control method based on an adaptive fuzzy sliding mode. The method comprises the following steps of: designing a control law according to the linear feedback technology and a micro-gyroscope dynamic equation; adding the sliding mode control to the control law based on the method to obtain a sliding mode control law; approaching to a practical system with a fuzzy system to obtain a fuzzy sliding mode control law; and determining an adaptive law of parameters based on the method. As the fuzzy approaching error is greater than or equal to the least approaching error, a parameter in the control law is selected as the absolute value of the approaching error plus a constant greater than 0, thus the unconditional stability of the system is ensured, the system response is accelerated and the system buffeting is reduced. Through the invention, the problems that the control accuracy of a traditional micro-gyroscope control system is relatively low due to the influence of environment change as the parameter variation is not considered and the like are solved, the micro-gyroscope can be effectively and reliably controlled in the case of uncertain parameters caused by the manufacturing error or unknown and existing environmental interference, and the overall stability of the system is ensured.

The invention discloses a fuzzy sliding mode and neural network based composite control system of a permanent synchronous motor. The control system comprises a rotation speed control outer ring and a current control inner ring, wherein a control unit in the rotation speed control outer ring adopts a composite control module; the composite control module comprises a fuzzy sliding mode control module and a neural network control module; and the fuzzy sliding mode control module and the neural network control module are combined together through two weighing factors lambda n and lambda f. The control system has the advantages of both the fuzzy sliding mode control module and the neural network control module, so that the strong robustness and high stability of the control system of the permanent synchronous motor are realized, the steady state precision is improved, and moreover, the rapidness in control and the strong load disturbance resistance are achieved.

The invention provides an angular velocity estimation based self-adaptive fuzzy sliding mode control method, applies the self-adaptive fuzzy sliding mode control method to a micro three-axis gyroscope control system, and can realize the trajectory tracking control and parameter estimation of a micro gyroscope system. According to the self-adaptive fuzzy sliding mode control method, a controller is designed on the basis the state-space equation of a micro gyroscope. Firstly, on the basis of the sliding mode controller, a novel self-adaptive identification method is designed, and the angular velocity of the micro gyroscope and the estimated valves of other systematic parameters are updated on line and in real time; besides, a fixed gain in a sliding mode control toggle item is adjusted by virtue of a self-adaptive fuzzy system, and fuzzy approximation is performed to the upper bound of the fixed gain, so that a chattering phenomenon arising in sliding mode control can be reduced. Through the adoption of the self-adaptive fuzzy sliding mode control method, a favorable tracking performance can be obtained, and the self-adaptive fuzzy sliding mode control method has robustness in parameter variation and external disturbance.

The invention provides a fuzzy sliding mode control method for vehicle height adjustment and vehicle attitude of an electrically controlled air suspension. The method comprises the steps that vehiclebody height signals at four corners of the vehicle and signals at a pitch angle of the vehicle body and a side angle of the vehicle body reflecting the attitude of the whole vehicle are obtained by avehicle body height sensor and a gyroscope correspondingly; the signals at the pitch angle of the vehicle body and the side angle of the vehicle body and the vehicle body after a low-pass filter are transmitted to a fuzzy sliding mode controller of the vehicle; according to the difference between a actual value of a related signal and a target value and a predetermined fuzzy sliding mode control law, the controller outputs an air mass flow signal flowing through four high-speed switching solenoid valves; through the PWM pulse width modulation technology, the air mass flow signal is further transformed into a duty cycle signal of the four high-speed switching solenoid valves in an on-off state; and at last, the on-off states of an inflatable solenoid valve and a out-gassing solenoid valve is determined according to the on-off signal of the four high speed switching solenoid valves and the predetermined logical relationship. The effective adjustment towards the vehicle body height of theelectrically controlled air suspension is achieved, and the controller has strong adaptive ability, stable performance and remarkable advantage.

The invention discloses a rotating-speed-estimation-based self-adaptive fuzzy and sliding-mode control method of an ESC, and belongs to the field of automobile hydraulic power assisted steering systems. The control method includes the following steps: 1, an outer rotor of the ESC is connected with an engine, an inner rotor of the ESC is connected with a steering pump, and an ESC type electronic control hydraulic steering system is built; 2, a rotating speed signal of the steering pump in the ESC type electric control hydraulic steering system is collected through an ECU; 3, an ESC dynamic equation is built based on the rotating speed in the step 2, wherein a mathematical model of the ESC under the d-q axis is built; and 4, based on the mathematical model in the step 3, a rotating-speed-estimation-based self-adaptive fuzzy and sliding-mode controller is designed. According to the rotating-speed-estimation-based self-adaptive fuzzy and sliding-mode control method, the beneficial effects of self-adaptive fuzzy control and fuzzy sliding-mode control are adopted, satisfied system responses are generated through a dynamic self-adaptive law, interference is obviously eliminated, and buffeting is reduced.

The invention discloses a fractional-order adaptive inverse fuzzy sliding mode control method for a microgyroscope. The method comprises a step of establishing a dimensionless dynamic equation mathematical model and a reference trajectory model of a microgyroscope system, and a step of constructing an inversion adaption fuzzy sliding mode controller based on a fractional order. According to the method, the real-time tracing of a target by the microgyroscope can be achieved, the robustness of the system is increased, and good performance still can be maintained under the condition of external interference. A fractional order adaptive law is designed based on a fractional order sliding mode surface, a self-adaptive identification method is designed based on a Lyapunov stability criterion, various unknown system parameters of the microgyroscope is estimated in an online way in real time, compared with an integer order, adjustable items are added, and a control effect and a parameter estimation effect are improved. A fuzzy system approaches upper bound values of a parameter uncertainty and an external disturbance total number, through the fuzzy approximation of the upper bound values,switching terms in the sliding mode controller can be continuous, and buffeting can be greatly reduced.

The invention discloses a cantilever beam vibration control method based on back-stepping fuzzy sliding mode control. The method comprises the following steps of building a dynamic cantilever beam mathematical model, and performing cantilever beam mathematical model conversion; designing a back-stepping sliding mode controller on the basis of a Lyapunov stability theory, and obtaining a sliding mode control law; designing a fuzzy self-adaptation system on the basis of the Lyapunov stability theory, and obtaining a fuzzy self-adaptation law; simultaneously inputting the output of the back-stepping sliding mode controller and the output of the fuzzy self-adaptation system into the cantilever beam mathematical model; feeding back the output of the cantilever beam mathematical model to the fuzzy self-adaptation system in real time, and ensuring the global stability. The method has the beneficial effects that the relying of a control system on the cantilever beam mathematical model can be avoided; the manufacturing errors and the environment interference are compensated; the parameter study and regulation can be controlled in time, and the global progressive stability of the whole control system is ensured, so that the system reliability and the parameter change robustness can be improved.

The invention discloses a hardware real-time operation system. The hardware real-time operation system comprises an ARM (advanced RISC machines) processor and an FPGA (field programmable gate array) which are connected via an FSMC (fuzzy sliding mode control) bus, wherein the FPGA is used for realizing a preemptive scheduler, and managements on tasks, a signal quantity, an oil tank, a message queue, a mutual exclusion signal quantity and an event flag group based on the preemptive scheduler; and the ARM processor is used for executing the tasks and realizing task switchover. By implementing the technical scheme of the invention, the FPGA does not occupy the processing time of the ARM processor because of running independently from the ARM processor, and the saved time is used for executing task programs, thus successfully reducing the system expense of the ARM processor; in particular, the utilization rate of the ARM processor is effectively increased in applications needing rapid task switchover. Therefore, via the operation system realized by hardware, the schedulability and real-time performance of the task set are improved.

The invention discloses a fully-driven autonomous underwater vehicle structure and a recovery three-dimensional path tracking method, which provides a three-stage recovery three-dimensional path tracking method and an improved non-singular terminal fuzzy sliding mode control algorithm for a robot recovery straight-line homing stage and a straight-line tracking stage. The three-dimensional path tracking method divides the recovery path into three segments, and transforms each segment of the curve into a sequence of spatial discrete points to track and control it. In the sliding mode control, the improved fuzzy sliding mode algorithm of non-singular terminal is designed to realize multiple sliding modes, and the sliding mode gain is real-time optimized by the fuzzy algorithm, so that the target point can be tracked quickly and steadily, the 3D path tracking performance can be enhanced, and the recovery success rate can be improved.

The invention relates to a bridge crane anti-swing control method based on a two-type fuzzy sliding mode. The two-type fuzzy control theory is utilized in combination with the sliding mode variable structure control method, and a two-type fuzzy sliding mode controller is constructed; a sliding mode function is constructed according to a bridge crane model, a two-type fuzzy sliding mode function and a fuzzy rule database are established through utilizing the two-type fuzzy control theory, moreover, for a controller parameter configuration problem, the fuzzy adaptive DE algorithm is utilized tooptimize the controller. The method is advantaged in that a fuzzy adaptive scaling factor is introduced, global search performance of the algorithm is enhanced through introducing adaptive parameters,the algorithm is utilized to optimize the controller parameters, and lastly, the good anti-swing control effect is obtained.

The invention discloses a fuzzy sliding mode control method for a matrix rectifier. The method adopts sliding mode variable structure control and has the advantages of being high in robustness, not sensitive to intrinsic parameter change and external disturbance, and good in dynamic performance. To soften the buffeting phenomenon occurring after a state trajectory reaches the sliding mode surface during sliding mode control, fuzzy control is introduced to sliding mode control, and on the premise that the excellent characteristics of sliding mode control are reserved, a fuzzy controller is designed through the combination of fuzzy logic and knowledge and experience, the control process is optimized, the buffeting phenomenon is effectively restrained, and an excellent control effect is achieved.

The invention discloses an electric inspection robot operating posture control method and device. The control method comprises the steps that an electric inspection robot operating posture linearizedmodel is built, and a sliding mode surface equation is calculated based on the linearized model; a basic sliding mode control law is calculated on the basis of the sliding mode surface equation, a preset lyapunov function and a preset index reaching law, the sliding mode surface equation is processed through a generalized type two fuzzy sliding mode control model built in advance, and a preliminary processing result is output; and the preliminary processing result is substituted into an expression of the basic sliding mode control law, a final sliding mode control law is obtained, and accordingly, control over the electric inspection robot operating posture is completed based on the final sliding mode control law. In this way, through the electric inspection robot operating posture controlmethod and device, the anti-jamming capability of an electric inspection robot in the inspection moving process can be effectively improved, the slip resistance and the obstacle avoidance performanceare good, and accordingly, the safety performance of the electric inspection robot in the inspection moving process is effectively improved.

The invention provides an intelligent automobile transverse control system and method based on a piecewise affine fuzzy sliding mode. The system comprises an environment sensing module, a piecewise affine two-degree-of-freedom model module, an optimal driver model module, a fuzzy sliding mode control algorithm module and a lower computer execution module, wherein the environment sensing module isused for obtaining state parameters of a vehicle and fitting out a desired path; the piecewise affine two-degree-of-freedom model module is used for linearization of the nonlinear state of the vehicleand outputting transverse yaw acceleration of the vehicle; the optimal driver model module is used for calculating the ideal yaw velocity; the fuzzy sliding mode control algorithm module is used forcalculating the optimal steering wheel rotation angle and providing the optimal steering wheel rotation angle to the lower computer execution module for execution. By means of the method, the nonlinear characteristic of the vehicle can be effectively overcome, the control precision, stability and effectiveness are improved, the sliding mode switching frequency can be controlled through fuzzy control, and the phenomenon that sliding mode control easily causes buffeting is effectively reduced.

The invention discloses an indirect self-adaptive fuzzy sliding-mode control method of a micro gyroscope system. The method can achieve trajectory tracking control of the micro gyroscope system. The indirect self-adaptive fuzzy sliding-mode control method can approximate unknown terms in the micro gyroscope system in a fuzzy mode without an accurate mathematical model of the system and can approximate an upper bound value of parameter uncertainty and external interference amount in a fuzzy mode. Through the fuzzy approximation to the upper bound value, switching terms in a sliding-mode controller can be serialized, and buffeting is greatly reduced. By the adoption of the indirect self-adaptive fuzzy sliding-mode control method, satisfactory tracking performance can be acquired, and robustness to the parameter change and external interference is possessed.

The invention relates to a ZigBee intelligent gateway for large-scale networking and an implementing method thereof. The conventional ZigBee has small network coverage area. Two wireless ZigBee communication modules are respectively connected with a microprocessor module through signals; and a flash memory module is connected with the fuzzy sliding mode control (FSMC) port of the microprocessor module through signals. The implementing method for the intelligent gateway comprises that: the ZigBee intelligent gateway is connected with two adjacent ZigBee networks through a first ZigBee communication module and a second ZigBee communication module, and data information flow and command information flow passing through the intelligent gateway are processed in the intelligent gateway so as to determine the flowing direction of the information flow, namely forward or transmit the information flow. The ZigBee intelligent gateway realizes the information transmission process of a plurality ofZigBee subnetworks of different networks, so that different ZigBee subnetworks on the network layer are bridged through the gateway to form a logically large-scale network.

The invention discloses a method and apparatus for controlling the operation velocity of a linear servo system of a high-precision numerical control machine tool. The method includes the following steps: adopting a fuzzy sliding mode controller, adopting the exponential approach law at an approach motion stage, and adopting fuzzy control to realize switch control of a sliding mode at a sliding mode motion stage. The method enables a system to have excellent robustness and anti-interference capability, reduces buffeting of the operating velocity of the system, and accelerates responding velocity of the system. According to the invention, the apparatus includes a DSP digital signal processor unit, an A / D module, a rectification filtering module, a linear motor, an IPM intelligent power module, an encoder, a sensor, a current detecting module, a photoelectric isolation module and a fault detection module, etc.

The invention discloses a temperature control method of an electromagnetic induction heating system with uncertain stochastic delay, comprising: employing fuzzy sliding mode control, including an approach motion phase and a sliding mode motion phase; in early stage of approach motion, executing maximum power quick approach under power protection constraint and temperature rise speed limiting constraint; in later stage of approach motion, approaching a sliding mode surface in logarithmic curve manner so that the system has small vibration when approaching the sliding mode surface; in the sidingmode motion phase, using fuzzy control of dual sliding mode switching function and an adaptive adjusting mechanism of switching gain, so that vibration is effectively weakened and stable control is achieved. In the sliding mode control process, learning and prediction of a least squares support vector machine and electromagnetic induction heating thermal balance modeling and analysis are employedto provide prior information for sliding mode control, and speed and stability in electromagnetic induction heating temperature control are improved.

The invention discloses a high-frequency and high-voltage power supply controller for electrostatic dust collection and a control method. The high-frequency and high-voltage power supply controller for the electrostatic dust collection comprises a voltage conditioning circuit, a sliding mode controller, a fuzzy controller, a digital logic unit and a driving circuit, wherein voltage acquired by a voltage transformer of a high-frequency and high-voltage power supply main circuit is input into the voltage conditioning circuit, is conditioned and then is input into the sliding mode controller and the fuzzy controller; a sliding mode face parameter of the sliding mode controller is set and adjusted by the fuzzy controller; an output signal of the sliding mode controller passes through the digital logic unit to obtain a PWM signal of a driving switch; and the PWM signal drives an inverter circuit of the high-frequency and high-voltage power supply main circuit by the driving circuit. According to the high-frequency and high-voltage power supply controller for the electrostatic dust collection and the control method, fuzzy sliding mode control is applied to a high-frequency and high-voltage power supply for the electrostatic dust collection; and the sliding mode control has the characteristic of strong robustness on system parameter changes and outside disturbances, so that the system stability during reference voltage changes and load disturbances is improved.

The invention discloses a back-step self-adaptive fuzzy sliding-mode control method of an under-actuated aerial autonomous underwater vehicle (AUV) under composite disturbance. The back-step self-adaptive fuzzy sliding-mode control method comprises the steps of building a kinematics and kinetic model of the AUV, and building a Serret-Frenet coordinate system-based track tracing error model; and respectively designing track tracking back-step sliding-mode controllers of a horizontal plane and a vertical plane under the condition that no interference is considered according to the error model soas to achieve a track tracing function. On the basis, a working state of the system under a combined interference condition is considered, a self-adaptive fuzzy logic system is additionally arrangedat an original controller, the interference-resistance capability of the system is improved, and the track tracing control of the under-actuated AUV under the condition of external composite interference is achieved. By the back-step self-adaptive fuzzy sliding-mode control method, the composite interference of the under-actuated AUV can be identified, and a reference scheme having advantages of adaptability, high robustness and the like is provided for accurate control of track tracing of the AUV.

The invention discloses a control method of a vehicle-mounted flywheel battery radial suspension support system based on working conditions. The method includes: 1, taking a magnetic bearing system asa controlled object, and establishing a rotor dynamic model and a system state equation of the magnetic bearing system under different working conditions of the flywheel battery by using a dynamic test and a dynamic simulation; 2, subtracting the output x of the magnetic bear system from the target air gap x* to obtain the air gap error ex, and designing a sliding mode switch surface and a sliding mode controller including an equivalent control and a switching control based on the air gap error ex, a dynamic model and a state equation, and obtaining the sliding mode control law; 3, forming afuzzy RBF neural network by combining fuzzy control and an RBF neural network, and adjusting the constant velocity gain [epsilon] and exponential gain k of switching control by using the fuzzy RBF neural network; 4, adding a current controller, converting the output of the fuzzy sliding mode controller into the given current value of the current inner loop, and controlling the chopper to adjust the magnitude of the control current of the maglev bearing system. The control method improves the transient response rate of the current, and outputs the control current [delta] i of the maglev bearingsystem by the chopper.

The invention discloses a lower limb exoskeleton control method. The method comprises the following steps: collecting lower limb kinematics data of a subject; establishing a lower limb exoskeleton kinetic model; designing a nonlinear integral sliding mode surface; and designing a fuzzy sliding mode controller to obtain a fuzzy sliding mode control law. According to the method, the lower limb exoskeleton kinetic model is established by adopting an Euler-Lagrange method, and then in order to eliminate a buffeting phenomenon ubiquitous in sliding mode control and a Windup effect caused by an integral term, a nonlinear potential energy function is introduced to replace a traditional integral sliding mode surface on the basis of a sliding mode variable structure controller. And meanwhile, in order to overcome interference caused by factors such as modeling errors, signal noise and external disturbance in the lower limb exoskeleton modeling process, the fuzzy sliding mode controller is designed by utilizing the approximation characteristic of a fuzzy system, so that satisfactory lower limb exoskeleton control performance is obtained.

The invention discloses a micro gyroscope self-adaptive fuzzy sliding mode control method based on a dynamic surface. The micro gyroscope self-adaptive fuzzy sliding mode control method is characterized by comprising the steps of a first step, establishing a mathematical model of a micro gyroscope; a second step, approximating a summation of a dynamic characteristic of the micro gyroscope and an outer interference by means of a fuzzy control method; a third step, designing a self-adaptive fuzzy sliding mode controller based on the dynamic surface; and a fourth step, controlling the micro gyroscope based on the self-adaptive fuzzy sliding mode controller. A system can reach a stable state in a high speed. The dynamic characteristic of the micro gyroscope is an ideal mode. A manufacture error and an environment interference are compensated. The algorithm which is designed based on the dynamic surface method has advantages of reducing number of introduced parameters, simplifying calculation and reducing buffeting. The self-adaptive fuzzy sliding mode control can compensate the system designing parameter error and the outer interference and furthermore improves system validity.

The invention provides a spherical robot slope motion control method based on a fuzzy sliding mode controller. The method comprises the following steps that (1) posture and repeated swinging state information of a spherical robot on a slope is measured by an inertial measuring unit, position and speed information of the robot on the slope is measured through a speedometer and a coder, and motion target position information sent by an upper computer is received by the robot through wireless transmission; (2) the received information is transmitted to a central processing chip through a serial port; (3) driving moment required by the spherical robot under the current state is worked out by the central processing chip through the fuzzy sliding mode controller according to the received information, and the robot is controlled to move in real time. The spherical robot slope motion control method based on the fuzzy sliding mode controller has the advantages that (2) fuzzy control reduces requirements for system modeling accuracy; (2) the fuzzy sliding mode controller improves control robustness; (3) the introduction of fuzzy control greatly increases system convergence rate, and solves the problem that an existing fuzzy controller is insufficient in adjustment precision.

The invention discloses a UUV adaptive fuzzy sliding-mode control method under strong disturbance of load arranging to solve the research problem of absence of UUV control on account of strong disturbance of load arranging in a current UUV control method. The method is performed in accordance with the steps of firstly, performing load arranging through a UUV; secondly, obtaining the current state mu of the UUV, and building a dynamical model of the UUV under strong disturbance of load arranging; thirdly, designing a sliding-mode face s, and forming a sliding- mode controller; fourthly, designing a fuzzy controller; fifthly, optimizing delta K through an adaptive algorithm to obtain delta K; sixthly, obtaining a novel adaptive fuzzy sliding-mode controller tau; seventhly, controlling the UUV through tau to enable the state of the UUV to be changed; eighthly, executing the second step to the seventh step again till the UUV reaches the expected state mu d. The method is applied to the field of UUV control.

The invention provides a cascaded control method of an underwater ultrahigh-speed navigation body. The cascaded control method comprises the steps of setting a model parameter by building an underwater ultrahigh-speed supercavity navigation body motion model module, building a longitudinal motion error model module, calculating an error between actual motion of the underwater ultrahigh-speed navigation body and a set motion track, building a cascaded sub-system model, eliminating an interference and a system error through a standard sliding-mode control method by a sub-system 1, eliminating the system error through a fuzzy sliding-mode control method by a sub-system 2, building a control effect simulation module, and adjusting a parameter of a controller according to a real-time simulationresult so that the optical control effect of the system can be achieved. The cascaded control method is complete in step, and engineering implementation is easy; and when the cascaded control methodis applied to control of the underwater ultrahigh-speed navigation body, the design process of the navigation body controller can be simplified, and a guarantee can be provided for stable navigation of the underwater ultrahigh-speed navigation body.

The invention relates to a method for tracing the maximum power of a photovoltaic system based on finite time fuzzy sliding mode control. Firstly, the maximum power tracing problem of the photovoltaicsystem is re-interpreted in a model framework of a singular nonlinear system. Then, a T-S fuzzy modeling method is used for selecting six fuzzy sets to carry out fuzzification on the singular nonlinear system to obtain a singular T-S fuzzy system. A finite time fuzzy sliding mode controller is designed, and the time of reaching a sliding mode surface by the photovoltaic system is calculated. On the basis of a calculated time interval, an error limit of realizing maximum power tracing of the system when the photovoltaic control system reaches the sliding mode surface is further calculated. According to the method, the maximum power of the photovoltaic system can be traced in finite time under external disturbance, so that the photovoltaic power generation efficiency is improved; and the method has a wide market application prospect.

The invention provides a railway hump vehicle decelerator performance detection system. The system comprises an ARM processor module and the like; an Ethernet module, a power module and a serial port module are connected with the processor module; the power module, a photoelectric coding counting module, a DO (Digital Output) module, a DI (Digital Input) module, a PWM (Pulse Width Modulation) differential output module and an AD (Analog to Digital) acquisition module are connected with a processor module; and the processor modules are connected by an FSMC (Fuzzy Sliding Mode Control) bus. A brand-new detection scheme is provided for the problem that the braking performance becomes worse in the long-term use process of a decelerator in a railway traffic system. By combining a digital circuit design technology, an embedded system technology and a microcomputer control technology together, the system has the advantages of high efficiency, high precision, low cost and easiness in operation. By adopting the system, railway workers can detect and timely maintain failure decelerators, and researchers of a railway system can obtain abundant data from the uploaded mass data.