98 results about "Backstepping controller" patented technology

The invention relates to a command filtering backstepping control method based on an interference observer. An anti-interference non-linear controller is designed according to a multi-source interference non-linear system. The command filtering backstepping control method comprises the following steps of firstly building a non-linear mathematical model of a multi-source interference system; secondly designing equivalence interference in an estimation system of the non-linear system interference observer; then substituting equivalence interference estimated values obtained from the non-linear system interference observer into a command filtering backstepping controller, building the command filtering backstepping controller; and finally using a pole allocation method to design command filtering backstepping controller gain and non-linear interference observer gain for guaranteeing a closed loop composite error system to asymptotically be stable. The command filtering backstepping control method is strong in anti-interference capability, and can be applied to anti-interference control for systems such as aircrafts, mechanical arms, biochemical processes and ships.

A spacecraft attitude-track integrated backstepping tracking control method is provided, and aims to solve the problems that an existing method respectively uses separate control modes to track the spacecraft track and attitude, so the tracking effect is poor; the method comprises the following steps: 1, building a spacecraft attitude-track integrated relative kinematics and dynamics model according to dual quaternions; 2, designing a controller according to a backstepping method and the spacecraft attitude-track integrated relative kinematics and dynamics model built in step 1; 3, designing an anti-saturation method based input bounded controller according to the controller designed in step 2. The method considers the input bound problems on the backstepping controller base, and designs the anti-saturation node based input bounded backstepping controller; the method can track the spacecraft and realize the 6-degree of freedom attitude-track cooperation tracking of the target spacecraft, is suitable for practical in orbit conditions, and applied to the spaceflight field.

The invention provides a steering engine saturation resistant self-adaptive control method for ship courses. The method comprises performing a mathematical description on ship course motion, and constructing a dynamic saturation-resistant compensator, a first state vector z1 of a self-adaptive backstepping controller and a Lyapunov function of the z1 to obtain virtual control; calculating a second state vector z2 of the self-adaptive backstepping controller through subtraction through combining ship course angle information, the course angular speed and the compensation state which is output by a dynamic saturation-resistant compensator module, constructing an overall Lyapunov function in the control method, and obtaining a ship course non-linear self-adaptive controller provided with the saturation-resistant compensator through combining ship course stability conditions to complete the ship course non-linear self-adaptive control method provided with the saturation-resistant compensator. The self-adaptive control method is explicit in thinking, clear and reasonable in structure and prone to engineering implementation.

The invention discloses a backstepping control method of a pneumatic position servo system, which is specifically implemented according to the following steps: step 1, establishing a model of a controlled pneumatic position servo system, obtaining each variable parameter through real-time detection by respective detecting instrument, ignoring the friction force, and obtaining a third-order linear model of the pneumatic system, wherein the control target is to enable model output to track required desired output; step 2, establishing a backstepping controller model of the pneumatic position servo system; step 3, estimating unknown parameter values of the pneumatic position servo system, inputting the number values obtained through estimation into a computer so as to update parameters of the backstepping controller model in real time, controlling the signal output of an amplifier by the computer to regulate the displacement of a piston in real time. The backstepping control method of the pneumatic position servo system can obtain better tracking effect and higher control precision without adding pressure detection hardware or algorithm.

The invention discloses a displacement control method for a piezoelectric ceramics actuator. The control precision of a high-precision servo positioning platform can be improved by adopting the method provided by the invention. According to the invention, a traditional PI hysteresis model is improved and two new parameters are introduced. The improved PI hysteresis model can have compensation on symmetry and residue displacement in an easily-implementing manner. Then, the sum of uncertain disturbance including errors of PI hysteresis compensation, model establishing errors and unknown interference is estimated online in real time and is fed to a backstepping controller, so that numerical values of constant parameters of the backstepping controller can be reduced; the control system robustness on external interference can be improved and the control effect of a control system can be enhanced. By adopting the method, good tracking precision and robustness can be maintained and the whole control system is simple in structure and convenient to implement.

The invention discloses a rapid tracking control method for horizontal plane trajectory of a benthic AUV, and belongs to the technical field of trajectory tracking control of autonomous underwater robots. According to the invention, problems of limited control precision and slow adjustment speed when the current control method is applied to the benthic AUV are solved. According to the method, ocean current disturbance and model uncertainty are combined into a disturbance lumped term, a finite time disturbance observer is used for approaching a disturbance lumped term value, and a neural network is introduced to estimate an observation error. Furthermore, an adaptive neural network backstepping controller based on a finite time disturbance observer is provided to realize finite time high-precision trajectory tracking control of the benthic AUV. The method can be applied to trajectory tracking control of the benthic AUV.

The invention discloses a rotary speed control system and method of a permanent magnet synchronous motor. A current sensor module is connected with the permanent magnet synchronous motor; the currentsensor module, a Clark coordinate conversion module and a Park coordinate conversion module are connected in sequence; the Park coordinate conversion module is connected with a nonlinear disturbance observator and a back-stepping controller separately; the nonlinear disturbance observator is connected with the back-stepping controller; the back-stepping controller, a Park coordinate inverse conversion module, a voltage space vector PWM module and an inverter are connected in sequence; the inverter is connected with the permanent magnet synchronous motor; and a rotary speed / position detection module is connected with the nonlinear disturbance observator, the back-stepping controller, the Park coordinate conversion module and the Park coordinate inverse conversion module separately. By adopting back-stepping control and the nonlinear disturbance observator method to replace the conventional PI controller, and by adopting a rotary speed-current single loop control mode to replace the conventional rotary speed loop and current loop cascading control structure, quick tracking control of rotary speed and current is realized.

The invention discloses an adaptive fuzzy backstepping tracking control method of an active power filter, relates to controllers of the active power filter and particularly provides an adaptive fuzzy backstepping tracking control method, combining adaptive control, fuzzy control and backstepping control and aiming at a three-phase active power filter. For shortcomings of a backstepping control law design, a fuzzy logic system is utilized to approach an unknown nonlinear function, and the fuzzy logic system is adjusted on line according to an adaptive law, so that harmful effects on the system due to parameter uncertainty are avoided. An adaptive fuzzy backstepping controller enables a compensating current to track an instruction current signal in real time, stabilizes the tracking deviation in neighborhoods of 0 and utilizes the Lyapunov method to analyze the stability and the convergence of the system so as to guarantee that all signals in a closed-loop system has global asymptotic stability.

The invention provides a self-adaptive integral backstepping control method for load disturbance resistance of a PMSM for an elevator. Motor speed w is compared with given motor speed w* to obtain a rotation speed error e; load torque [tau]L is estimated according to motor speed w that is fed back and electromagnetic torque Te; the estimated load torque [tau]L and a rotation speed error e are input to a self-adaptive integral backstepping controller to be adjusted, a steady-state error of speed is eliminated to obtain a virtual control quantity i<q><*> of a q axis of a stator current in a rotating coordinate system d-q, an exciting current component i<d><*> is used as a reference value to be input to a current loop, and subtraction operation is performed on the reference value and a statorcurrent i<d> after coordinate transformation to obtain a d axis stator current error e<d>; control voltages u<d> and u<q> are calculated according to a q axis stator current error e<q> and a d axis stator current error e<d>; and u<d> and u<q> are subjected to park inversion and are input to an SVPWM pulse width modulation module to generate a pulse signal required for driving an inverter, therebydriving the motor to run. The self-adaptive integral backstepping control method for load disturbance resistance of a PMSM for an elevator improves robustness of an elevator electric system, and enhances comfort and rapidness of the elevator.

The invention discloses an impedance control method for a multi-joint mechanical arm based on finite time command filter and belongs to the technical field of robot control. Based on a backstepping method, force / position control of the mechanical arm is achieved by means of an impedance control technique. An unknown friction quantity in a multi-joint mechanical arm system is approached by adoptinga fuzzy adaptive technique and a command filter technique is introduced to solve the computing complexity problem in a conventional backstepping controller design, and meanwhile, an error compensating mechanism is introduced to eliminate influence of filter errors. A force / position tracking signal of the mechanical arm is converged within a finite time by means of finite time control, so that itis ensured that the force / position tracking error of the mechanical arm can be converged in a small enough field of an origin within the finite time. In a word, according to the control method provided by the invention, a force / position track at the tail end of the mechanical arm can track an expected trajectory quickly and effectively.

The invention discloses a backstepping control method of a load simulator based on an expansion state observer, and belongs to the field of electro-hydraulic server control. According to the control method, nonlinearity including parameter nondeterminacy of a system and external interference are taken into consideration, a third-order model of the load simulator is established concretely, uncertain nonlinearity of the external interference and the like is estimated based on the expansion state observer, a continuous backstepping controller is designed, and a bounded stable theoretical result is obtained. The method has the advantage of accurate parameter estimation, a rapid dynamic compensation method is used to overcome the defect of relatively low output tracking performance in adaption,and a better simulation result can be obtained in the aspects of parameter estimation and error tracking; and a designed nonlinear controller is continuous in the control voltage and can be applied in engineering practicality.

The invention relates to a passive backstepping control method for suppressing circulation of a modular multilevel converter. The passive backstepping control method comprises the steps of S1, obtaining an MMC circulation PCHD model by a single-phase equivalent circuit of an MMC according to a positive definite quadratic form energy function; S2, building a PCHD model-based MMC circulation suppression passive backstepping controller; S3, inputting a circulation double-frequency actual value and a reference value into the MMC circulation suppression passive backstepping controller so as to output circulation voltage compensation quantity; and S4, performing carrier phase-shift modulation on the circulation voltage compensation quantity, and controlling a switch tube in an MMC sub-module tobe switched on and switched off by a modulation wave so as to achieve the purpose of circulation suppression. Compared with the prior art, PCHD model-based passive control and a backstepping method are organically combined, global stability can be ensured, rapid and dynamic response also can be achieved, and moreover, the method has the obvious effects of simple control law algorithm, no singularpoint, high robustness and circulation suppression.

The invention discloses a micro-gyroscope backstepping control method based on a neural network state observer. A micro-gyroscope, the neural network state observer and a backstepping controller are included. Displacement in a Z-axis micro-gyroscope XY-axis direction acts as input of the state observer, and uncertain part of the micro-gyroscope is estimated via a neural network so that estimation of micro-gyroscope position and speed signals is completed. The estimated signal of the state observer is adopted by the backstepping controller to act as input so that vibration amplitude and frequency in the micro-gyroscope XY-axis direction are controlled. According to the micro-gyroscope backstepping control method based on the neural network state observer, backstepping control based on the neural network state observer is applied to the micro-gyroscope so that system stability and reliability are enhanced, error is effectively reduced and the control effect is great.

Disclosed is a control method for a permanent magnet synchronous generator for mechanical elastic energy storage. According to the control method, a full-system mathematical model of a permanent magnet synchronous generation apparatus which is formed by a coil spring box, a speed-changing gear box and a permanent magnet synchronous generator which are connected in sequence is established firstly; then a state equation of the permanent magnet synchronous generator is established according to internal and external interferences, and a high-gain interference observer is designed; the comprehensive interference is evaluated by the high-gain interference observer; the control voltages of a d axis and a q axis are solved by designing a robust back-stepping controller L2; and finally, the control voltages are input into the full-system mathematical model of the permanent magnet synchronous generator to realize control on the permanent magnet synchronous generator. According to the control method provided by the invention, the high-gain algorithm based interference observer is designed based on the internal and external non-linear interferences; the robust back-stepping control law is designed based on the L2 interference suppression algorithm; test results prove that the control method can fully restrain internal and external non-linear interferences; and consequently, the high-precision control of the generator is realized, and high-quality electric energy output by the motor is ensured.

The invention relates to a parameter-identification-based PMSG control method for mechanical elastic energy storage. The method comprises: a full-system mathematical model of a permanent-magnet synchronous power generation device consisting of a vortex spring box, a transmission gearbox and a permanent-magnet synchronous generator is established; according to an MRAS and a Popov hyperstable theory, two kinds of identification algorithm capable of identifying generator parameters including an inductance value and a flux linkage and energy storage box parameters including a torque and a rotary inertia are designed for parameter changing observation; modeling is carried out by using identification values to eliminate a modeling error caused by internal and external parameter changes to the greatest extent; an adaptive backstepping controller is designed to calculate and obtain an adaptive law for describing resistor interference and control input signals of a d axis and a q axis; and then the control signals are inputted into the full-system mathematical model of the permanent-magnet synchronous power generation device, so that controlling of the permanent-magnet synchronous power generation device can be realized. Experiment results demonstrate that internal and external parameter changing interference of the system can be eliminated to the greatest extent; high-precision controlling of the generator can be realized; and the motor can output high-quality electric energy.

The invention discloses a direct power control method of a three-phase PWM rectifier. According to the three-phase current and three-phase voltage of the network side of the three-phase PWM rectifier,the instantaneous active power and the instantaneous reactive power of the three-phase PWM rectifier are calculated to construct the average state space model of the three-phase PWM rectifier. A decoupling control signal is introduced into the average state space model of the three-phase PWM rectifier. Uncertain terms in the system are taken into account. A reactive power neural network adaptiveBackstepping controller and a neural network adaptive Backstepping controller of direct current output voltage are designed. Related parameters are input into the reactive power neural network adaptive Backstepping controller and the neural network adaptive Backstepping controller of direct current output voltage to acquire the corresponding output control rate. Coupling transformation is carriedout on the output control rate. The switching control signal of the three-phase PWM rectifier is acquired according to the SVPWM model. The control method provided by the invention has the advantagesof small calculation amount, simple parameter adjustment and good robustness.

The invention relates to a designing method of a self-adaption backstepping controller of a full vehicle active suspension system. The method comprises the following steps of 1, building a full vehicle active suspension non-linear model; 2, determining the self-adaption backstepping controller, wherein the self-adaption backstepping controller comprises a front right suspension controller, a front left suspension controller, a rear right suspension controller and a rear left suspension controller and all the controllers are connected to actuators corresponding to suspensions respectively; 3, determining a self-adaption control target; 4, determining a control law of the self-adaption backstepping controller by combining the full vehicle active suspension non-linear model and the self-adaption control target. Compared with the prior art, according to the designing method of the self-adaption backstepping controller of the full vehicle active suspension system, the driving comfort of vehicles is improved, meanwhile the vehicle driving safety, the suspension travel, the actuator saturation phenomenon and the like can all be satisfied, and the controllers of the design perform control more precisely and more reliably.

The invention discloses an adaptive control method of a vehicle active suspension system considering time lag interference, which comprises the following steps: establishing a nonlinear active suspension system model with input time lag, and obtaining a kinetic equation of an active suspension according to a Newton second law; designing a self-adaptive backstepping controller capable of resistingtime lag interference; analyzing the influence of the time lag on the system, calculating the critical time lag of the controlled suspension system, and obtaining the controllable time lag range of the self-adaptive backstepping controller; selecting proper gains k1 and k2 and feedback coefficients l1, l2, ls and lc, so that all constraints of the nonlinear system can be limited within a reasonable range under the influence of a certain time lag range, and control indexes are met; according to the method, the problems that an existing vehicle nonlinear suspension model is simple, a control target is single and the like are solved, and the problems of controller time lag interference, sprung mass uncertainty and model dynamic stability under the vehicle driving condition are also solved.

The invention discloses a fuzzy adaptive dynamic surface control method for an asynchronous motor stochastic system based on a reduced-dimensional observer. Aiming at the control precision requirements of asynchronous motor stochastic systems and the existing random disturbance and nonlinear problems, the method designs a fuzzy adaptive backstep controller to track a target position, and uses thefuzzy logic system to deal with the unknown stochastic nonlinearity in asynchronous motor system. The dynamic surface technology is introduced into a traditional backstep method to solve the problem of 'computation explosion' in the computing process, and a reduced-dimensional observer is constructed to estimate the rotor position and the rotor angular velocity of the asynchronous motor. The simulation results show that the method of the invention can quickly converge the tracking error to a sufficiently small neighborhood of the origin, and has the better anti-interference ability.

The invention discloses a longitudinal control method for a hypersonic flight vehicle based on online identification of an aerodynamic parameter. The method firstly employs an iteration extension Kalman filtering algorithm combining an extension Kalman filtering algorithm and an iteration filtering theory to perform the online identification on the aerodynamic parameter, and provides a more accurate model for subsequent control; and then, based on the identified aerodynamic parameter, a adaptive filtering back-step controller is designed to precisely controls a longitudinal equation of the hypersonic flight vehicle. Compared with a traditional extension Kalman filtering algorithm, the iteration extension Kalman filtering algorithm employed by the method is higher in precision, and can identify the aerodynamic parameter more accurately. A control strategy proposed by the invention can effectively overcome a phenomenon of "inconsistent parameters of heaven and earth", the accuracy of a model is improved through the online identification, and the pressure of a control system is alleviated.

The invention discloses a neural network control method for backlash compensation of a turntable servo system, and aims to obtain higher tracking precision, faster response time and more stable tracking performance in allusion to the problems of driving delay and response hysteresis caused by the existence of a backlash in the turntable servo system. The method comprises the following steps of: establishing a state-space equation of an industrial robot turntable servo system, and selecting a dead zone function to describe backlash nonlinearity; directed at the problem that the speed information loaded by an industrial robot servo system is difficult to measure, a speed observer is designed to estimate the speed information; meanwhile, applying a backstepping method, introducing a virtual control quantity, selecting a Lyapunov function for backstepping recursion, and meanwhile introducing a radial basis function neural network for approximating a nonlinear part in the system, designingan RBF neural network backstepping controller, and proving the stability of the system by using the Lyapunov stability principle, ensuring the progressive stability of the system, compensating the influence of backlash nonlinearity, and improving the tracking precision.

The invention relates to an aircraft guidance and control integrated method based on an observer technology, and the method comprises the steps: building a missile guidance and control integrated model, and converting the missile guidance and control integrated model into a strict feedback nonlinear mathematic model; and designing a multi-sliding-mode-surface backstepping controller by combining variable structure sliding mode control and backstepping control based on the generated strict feedback nonlinear mathematical model. According to the method, the design of a control algorithm is facilitated, and by designing a composite item D, the sliding mode surface is stable and reachable, and the differential explosion phenomenon is avoided; an initial value attenuation term is introduced tooptimize a sliding mode surface, so that the amplitude of a control signal is reduced, and saturation of an actuating mechanism is prevented; and the second-order disturbance observer is used for carrying out observation compensation on the composite item D, so that the anti-interference capability and robustness of the system are improved.

The invention discloses a BP neural network optimization chaotic control method based on a double-fed wind power system. The method comprises the steps of: establishing a standard mathematical model of the double-fed wind power system, wherein the mathematical model comprises a voltage same flux linkage equation of a double-fed induction generator and a motor motion equation, and on this basis, establishing a decoupling model of the double-fed wind power system; designing the backstepping controller for the d-axis current of the rotor by utilizing the backstepping method, and designing the backstepping controller for the q-axis current and the rotating speed v of the rotor; and employing the BP neural network to fit and optimize the decoupling backstepping control parameters to achieve optimization of the control effect of the double-fed wind power system. The global stability of the system is verified by the stability analysis theory and actual verification.

The invention relates to a finite time control method for a variable-load quadrotor unmanned aerial vehicle. Aiming at a variable-load quadrotor unmanned aerial vehicle model, a position loop performs real-time online estimation on load change parameters based on an adaptive control algorithm, and an adaptive backstepping controller is designed. An attitude loop carries out online estimation on interference through a disturbance observer, a sliding mode surface is further improved, a new finite time stability criterion is introduced, and a finite time sliding mode controller is designed. Therefore, the convergence speed of the system is higher, the anti-interference capability is stronger, the steady-state and transient-state performances are better, and the method is more suitable for practical application.

The invention relates to a Backstepping-based lower limb exoskeleton control method, which comprises the following steps of: 1, establishing a lower limb exoskeleton dynamical model, and converting the lower limb exoskeleton dynamical model into a control system state equation; 2, designing a Backstepping controller, and carrying out the control of the Backstepping controller; 3, improving an RBF disturbance observer, including designing the RBF disturbance observer and an RBF neural network adaptive law; and 4, performing control implementation, and enabling the lower limb exoskeleton to move according to the expected track. According to the method, for external random disturbance, the approximation characteristic of an RBF neural network is utilized, a disturbance observer is designed, and the external random disturbance is approximated; and aiming at the network approximation error existing in the RBF neural network, the disturbance observer is further improved, and the auxiliary variable is introduced to compensate the network approximation error, so that the external random disturbance is compensated, the approximation of the external random disturbance is closer to a real value, and the approximation error of the RBF neural network is reduced.

The invention provides a high-anti-interference fast-response control system and method for a high-frequency link matrix converter, and belongs to the technical field of advanced control of high-efficiency power conversion systems. An output current outer loop backstepping controller obtains a reference value of an input current on an active component d axis according to a received given output current reference value and an output current and an output voltage of the high-frequency link matrix converter; an input current inner loop backstepping controller obtains a modulation ratio of three-phase current active components according to the power grid voltage active component, the power grid current active component and the reactive component; and a bipolar current space vector modulation module obtains a control pulse signal of the high-frequency link matrix converter according to the modulation ratio of the three-phase current active components and the sector, and is used for drivinga bidirectional switch of the high-frequency link matrix converter. According to the invention, overshoot and overshoot time can be reduced, and internal and external disturbance of a high-frequency link matrix converter system can be effectively resisted, so that the converter system has good dynamic performance and anti-interference performance.

The invention discloses a Matlab based simulation control method for a nonlinear backstepping controller. The method includes steps of (1) constructing a mathematic model of a magnetic suspension ball system in a way of neglecting other interference that may act on the ball; (2) constructing a nonlinear backstepping controller model of the magnetic suspension system and obtaining a conclusion that all tracking errors level off to zero according to LaSalle invariant theory. System stability is improved and the control rate of the backstepping controller is given by a formula (8, 9, 10). According to the invention, the magnetic suspension ball system having highly nonlinear property has good stability and high-performance location tracking capability. The adopted method is effective, and is high in modeling precision and insusceptible to external interference.

A sensorless switch magnetic resistance motor-driven system belongs to the motor control field, and comprises a switch magnetic resistance motor, an asymmetric converter, a bus capacitor, a DC power supply, a driving circuit, a current regulator, a backstepping controller, a non-linear state observer, a current hall sensor, a current signal conditioning circuit, a voltage hall sensor, and a voltage signal conditioning circuit; the sensorless structure can increase the system stability; the non-linear state observer can monitor the stator-phase voltage and phase current so as to calculate therotor position, thus accurately determining the rotor position even the motor is under a high speed rotating state, reducing the system cost, and improving the driving precision.

The embodiments of the invention provide an autonomous underwater robot and path following control method and device and relate to the robot technology field. The method comprises the following stepsof obtaining a built autonomous underwater robot motion system; generating a nonlinear dynamic system of the autonomous underwater robot motion system according to a physics principle; receiving a real-time position acquired by the positioning module of the autonomous underwater robot, and rewriting the real-time position according to a dynamic model; and generating a nonlinear robust inverse stepcontroller based on a disturbance term of the autonomous underwater robot, the real-time position and a preset input-state stability theory, and controlling the autonomous underwater robot motion system so that the autonomous underwater robot autonomously and independently completes precise path following operation and achieves stable operation.

The invention discloses a composite control method for improving an anti-interference capability of a brushless direct current motor. The method comprises the steps: S1, building a brushless direct current motor state equation, concluding parameter perturbation and external load interference as total disturbance, and building a brushless direct current motor servo system state space model; S2, taking the total disturbance as an extended state variable, and reconstructing a system equivalent state space model by separating a measurable state and an unmeasurable state of the system; S3, constructing a reduced-order extended state observer, and estimating the total disturbance and the unmeasurable state of the system online; and S4, designing a backstepping controller based on disturbance dynamic compensation by using the estimated value of the reduced-order extended state observer and the measurable state of the system, suppressing the influence of disturbance on the output of the system, improving the dynamic performance and robustness of the system, and ensuring the accurate tracking of the output of the system on reference input. The method is easy to implement, high in control real-time performance, high in tracking precision and the like.