CN110091876B - Multi-fault detection and isolation method for wire-controlled four-wheel steering electric forklift - Google Patents

Multi-fault detection and isolation method for wire-controlled four-wheel steering electric forklift Download PDF

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CN110091876B
CN110091876B CN201910397391.8A CN201910397391A CN110091876B CN 110091876 B CN110091876 B CN 110091876B CN 201910397391 A CN201910397391 A CN 201910397391A CN 110091876 B CN110091876 B CN 110091876B
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CN110091876A (en
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肖本贤
孙铮
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Hefei University of Technology
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/0098—Details of control systems ensuring comfort, safety or stability not otherwise provided for
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/02—Ensuring safety in case of control system failures, e.g. by diagnosing, circumventing or fixing failures
    • B60W50/0205—Diagnosing or detecting failures; Failure detection models
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/02—Ensuring safety in case of control system failures, e.g. by diagnosing, circumventing or fixing failures
    • B60W50/029—Adapting to failures or work around with other constraints, e.g. circumvention by avoiding use of failed parts

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Abstract

The invention relates to a multi-fault detection and isolation method for a line-controlled four-wheel steering electric forklift, which comprises the following steps: establishing a three-degree-of-freedom dynamic model of the electric forklift; constructing a fault model; designing a self-adaptive sliding mode variable structure observer; setting a self-adaptive sliding mode variable structure observer for each possible fault part, and setting different fault threshold values; accurately judging which specific sensor or actuator has a fault according to the residual error, and judging specific fault time; if the fault occurs, isolating the fault in time and reminding a driver of the occurrence of the fault; and (3) if no fault occurs, circularly executing the step (1) to the step (6) at set time intervals, and realizing fault detection and isolation of the wire-controlled four-wheel steering electric fork truck. The invention can quickly and accurately position and reasonably isolate the faults of the actuator and the observer, so that the wire-controlled four-wheel steering electric fork truck has good safety and stability under various complex working conditions.

Description

Multi-fault detection and isolation method for wire-controlled four-wheel steering electric forklift
Technical Field
The invention relates to the technical field of safe auxiliary driving and intelligent fault detection, in particular to a multi-fault detection and isolation method of a wire-controlled four-wheel steering electric forklift.
Background
In recent years, with the development of industrialization and science, engineering vehicles are increasingly frequently used. Meanwhile, with the development of automobile science and technology, more advanced technology is applied to engineering vehicles, and operability, safety and driving stability of the engineering vehicles are improved. Among them, a forklift is widely used in ports, logistics warehouses, factory workshops, and the like as a main cargo handling vehicle. However, the conventional fuel forklift has the problems of high energy consumption, environmental pollution and the like, and is widely applied to an unpowered forklift.
The four driving wheels of the four-wheel independent driving electric forklift can be randomly distributed in torque, and the four driving wheels are flexibly controlled, so that the four-wheel independent driving electric forklift becomes a research hotspot in the field of pure electric vehicles at home and abroad at present. Meanwhile, the steer-by-wire system has the characteristics of improving the safety performance of the automobile, improving the driving characteristics, enhancing the maneuverability and improving the road feel of the driver.
Fork truck work in these places often meets the operating environment that the space is narrow and small, turn to frequently for fork truck compares than other engineering vehicle, and operating environment is abominable, more need pay attention to turn to operation and safety problem. If a fault occurs, the traditional fault detection and isolation method cannot be used for timely detection and isolation, so that potential safety hazards, even out of control, or other serious safety accidents of the forklift can be caused.
Disclosure of Invention
The invention aims to provide a multi-fault detection and isolation method of a wire-controlled four-wheel steering electric fork-lift truck, which can effectively ensure the operability, stability and safety of the wire-controlled four-wheel steering electric fork-lift truck in a complex working environment.
In order to achieve the purpose, the invention adopts the following technical scheme: a multi-fault detection and isolation method for a steer-by-wire four-wheel steering electric fork-lift truck, the method comprising the following sequential steps:
(1) establishing an electric forklift three-degree-of-freedom dynamic model according to an electric forklift real vehicle;
(2) constructing a fault model according to a fault item and an unknown disturbance item of the forklift in the operation process and by combining with the established electric forklift dynamic model;
(3) determining the actual yaw rate w from the current driving state of the fork-lift truckrActual slip angular velocity prAnd the actual steering wheel angle value deltar；
(4) Designing an adaptive sliding mode variable structure observer, wherein a discontinuous switch item and an adaptive item determined according to a residual error are added;
(5) setting a self-adaptive sliding mode variable structure observer for each possible fault part to carry out fault monitoring, and setting different fault threshold values;
(6) the number of the set adaptive sliding mode variable structure observers is the same as that of the sensors or actuators, and the specific sensor or actuator is accurately judged to have a fault according to the residual error, and the specific fault time is judged;
(7) if the fault occurs, isolating the fault in time and reminding a driver of the occurrence of the fault;
(8) and (3) if no fault occurs, circularly executing the step (1) to the step (6) at set time intervals, and realizing fault detection and isolation of the wire-controlled four-wheel steering electric fork truck.
In the step (1), a three-degree-of-freedom dynamic model of the electric forklift of the steer-by-wire four-wheel electric forklift is established as follows:
according to the dynamic principle of the forklift, the following three equations are obtained:
determining the roll motion equation about the X-axis as given in equation (1):
Figure GDA0002497502070000021
determining the lateral motion equation about the Y axis as given in equation (2):
Figure GDA0002497502070000022
determining the yaw motion equation about the Z axis as given in equation (3):
Figure GDA0002497502070000023
Ixrotational inertia about the X axis for the suspended mass;
Figure GDA0002497502070000024
yaw angular acceleration;
Figure GDA0002497502070000025
is the roll angular acceleration; mxiThe component moment of each moment in the X-axis direction; i isxzThe inertia product of the finished automobile around the X axis and the Z axis; fYiThe component moment of each moment in the Y-axis direction; l isxAn external moment acting on the suspended mass in the X-axis direction; m is the vehicle mass;
Figure GDA0002497502070000026
is the lateral acceleration; u is the longitudinal forward speed; omega is yaw angular velocity; m issIs a sprung mass; h issThe vertical distance from the center of mass of the sprung mass to the central axis of the roll; fYIs the total external force along the Y-axis direction; i iszIs the moment of inertia about the Z axis; mziThe component moment of each moment in the Z-axis direction; mzIs the total external moment to the Z axis; p is the roll angular velocity;
determining a torque balance equation of the steer-by-wire four-wheel electric forklift, as shown in the formulas (4) to (6):
Figure GDA0002497502070000027
FY＝FY1+FY2+FY3+FY4(5)
Mz＝a(FY1+FY2)-b(FY3+FY4) (6)
since the fork truck phi value is small, sin phi is approximately equal to phi, cos phi is equal to 1, and the following equations can be obtained by combining (1) to (6):
Figure GDA0002497502070000031
FY1is the vertical load of the left wheel of the front axle; fY2Is the vertical load of the right wheel of the front axle; fY3Is the vertical load of the left wheel of the rear axle; fY4Is the vertical load of the right wheel of the rear axle; a. b is the distance from the center of mass of the forklift to the front axle and the rear axle respectively; g is the acceleration of gravity;
Figure GDA0002497502070000032
is the centroid slip angular velocity; k is a radical ofφSuspension roll stiffness; rfThe front axle side tilting rotation coefficient; c. CφDamping for suspension roll angle; phi is the vehicle body side inclination angle; deltafIs the corner of the front wheel of the forklift; deltarIs the corner of the rear wheel of the forklift; rrThe tilting direction coefficient of the rear shaft side is obtained; k is a radical offEquivalent cornering stiffness of front axle tires; k is a radical ofrEquivalent cornering stiffness of rear axle tires;
Figure GDA0002497502070000033
yaw angular acceleration;
taking the yaw angular velocity omega, the centroid slip angle β, the vehicle body roll angle phi and the roll angle velocity p as state variables, and writing the above equation into the following state space equation form:
Figure GDA0002497502070000034
in the formula:
Figure GDA0002497502070000035
Figure GDA0002497502070000036
Figure GDA0002497502070000037
M3＝[k1k1a 0 0]T
x(t)＝[ω β φ p]T；U＝δf；
wherein: u is an input item, and the input quantity is a front wheel steering angle; A. b, C, M1、M2、M3The matrix contains real truck data of the forklift.
In the step (2), the fault terms include an input interference term, a sensor fault term and an actuator fault term, and adding the input interference term, the sensor fault term and the actuator fault term can obtain a fault equation:
Figure GDA0002497502070000041
in the formula (I), the compound is shown in the specification,
Figure GDA0002497502070000042
xp(t) derivative of; x is the number ofp(t)∈Rn：xp(t)＝[ω β φ p]TNon-measurable state quantity u (t) ∈ Rl: inputting a vector; y isp(t)∈Rm: outputting the vector; dp: uncertain vectors such as unknown disturbances; d (t) is unknown perturbation; f. ofs∈Rm: a sensor fault vector; f. ofa∈Rm: an actuator fault vector; esp: a known sensor fault distribution matrix; eap: a known actuator fault distribution matrix; a. thep，Bp，Cp: a matrix of known constants;
for designing output items to be only in accordance with state quantities xp(T) related, presence of a non-singular transformation matrix T0Is transformed, among them
Figure GDA0002497502070000043
The system state equation can be expressed as:
Figure GDA0002497502070000044
wherein: a. the1、A2、A3、A4、B1、B2、C2、D2、E1、E2All given dimensions, from the relation
Figure GDA0002497502070000045
CpT0＝[0 C2]Determining a specific matrix by LMI tool box, wherein T0For setting matrices, x, artificially1∈R(n+h)×(n+h),x2∈Rp，A1∈R(n+h-p)×(n+h-p)，A2∈R(n+h-p)×p，A3∈Rp×(n+h-p)，A4∈Rp×p，B1∈R(n+h)-p，B2∈Rp，D2∈Rp×(q+h)，E1∈R(n+h)-p，E2∈Rp，C2∈Rp；
Base equation (9) on T0The transformation is to equation (10),
Figure GDA0002497502070000046
contains no fault term, only unknown disturbance term, A1、A2、B1、E1Is a parameter after mathematical transformation; in the same way, the method for preparing the composite material,
Figure GDA0002497502070000047
in which both fault terms and interference terms are contained, A3、A4、B2、D2、E2Is a parameter after mathematical transformation; y (t) ═ C2x2(t) C in2Are parameters after mathematical transformation.
In the step (3), the yaw rate w of the forklift in the current driving state is measured by using the yaw rate sensor, the side yaw rate sensor and the steering wheel angle sensor respectivelyrAngular yaw rate prSteering wheel angle value deltar(ii) a Voltage U of left front wheel driving motor measured by voltage sensorf1Voltage U of right front wheel driving motorf2Voltage U of driving motor of left rear wheelr1Voltage U of right rear wheel driving motorr2。
In the step (4), designing the adaptive sliding mode variable structure observer specifically includes:
Figure GDA0002497502070000051
wherein:
Figure GDA0002497502070000052
is a state quantity; u (t) is input quantity, and the input quantity is a rotation angle value; v is a discontinuous term; l is a matrix to be set;
Figure GDA0002497502070000053
disturbance observed by an observer;
Figure GDA0002497502070000054
is the output quantity;
defining a discontinuous term v, adding the discontinuous term v into an adaptive sliding mode variable structure observer,
Figure GDA0002497502070000055
where ζ is a suitable parameter; f is an adaptive matrix to be calculated; e.g. of the typeyGenerating a residual for the observer;
meanwhile, only fault information is included by utilizing residual errors, a fault estimation algorithm is designed, the algorithm comprises self-adaptive rate, and the algorithm expression is obtained as follows:
Figure GDA0002497502070000056
Figure GDA0002497502070000057
a fault estimation algorithm based on residual errors, E0To design the dimensional matrix, eyFor state observation error, β is the variable structure parameter, and F is the adaptive matrix.
In the step (5), setting a threshold value of each sensor and each actuator, wherein the threshold value is the maximum value in a normal working state; yaw rate sensor threshold value μw(ii) a Yaw rate sensor threshold μp(ii) a Steering wheel angle sensor threshold value of muδ(ii) a The output voltage threshold value of the left front wheel driving motor is muf1(ii) a The output voltage threshold value of the right front wheel driving motor is mul2(ii) a The output voltage threshold of the left rear wheel driving motor is mur1(ii) a The output voltage threshold value of the right rear wheel drive motor is mur2；
When the yaw rate sensor fails, the output amount is we(ii) a When the yaw rate sensor fails, the output quantity is pe(ii) a When the steering wheel angle sensor fails, the output quantity is δe(ii) a The actuator is a direct current drive motor, the output torque of the motor is controlled by voltage, and the wheel rotation angle is further controlled, so when the actuator fails, the output quantity is the output voltage U of the left front wheel drive motorfe1Output voltage U of right front wheel driving motorfe2Output voltage U of left rear wheel driving motorre1Output voltage U of right rear wheel driving motorre2。
And (7) if the fault is judged to occur, isolating the fault, and prompting the fault to occur to a driver on a display screen of the cab and giving an alarm by a buzzer.
According to the technical scheme, the invention has the advantages that: firstly, according to the structure and the working environment of the wire-controlled four-wheel steering electric fork truck, a three-degree-of-freedom whole truck model of the wire-controlled four-wheel steering electric fork truck is established; establishing a fault model according to the interference item and the fault item and by combining a whole vehicle model, and laying a foundation for the use of an observer; the adaptive sliding mode observer is arranged, variable structure parameters are added, unknown input interference can be effectively known, the adaptive rate is designed by utilizing residual signals, and the track can be better tracked; meanwhile, a multi-observer thought is utilized, and an observer is arranged for each part, so that the states of each sensor and each actuator can be observed by using a sliding-mode observer, and fault detection and state reconstruction can be performed; different residual error threshold values are designed for different types of sensors and actuators, so that faults can be effectively judged according to different conditions, and the characteristics that the residual error generated by an observer (actuator) is not influenced by the fault signal of the sensor (actuator) and unknown input of a system, but is only influenced by the fault signals generated by other sensors (actuators) are utilized, so that the specific sensor (actuator) is accurately judged according to the residual error, and the specific fault time is determined; finally, the display screen in the cab reminds the driver of when and which part of the forklift breaks down, so that the safety of the driver in a complex working environment is effectively ensured. Secondly, the adaptive sliding mode variable structure observer has higher sensitivity and rapidity, can effectively avoid the occurrence of false alarm and false alarm by using a residual error threshold value method, can quickly and accurately position by adopting the thought of a plurality of observers, and reasonably isolates the faults of the actuator and the observers, so that the wire-controlled four-wheel steering electric forklift has good safety and stability under various complex working conditions.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
fig. 2 is a schematic diagram of a three-degree-of-freedom model of the steer-by-wire four-wheel electric forklift according to the present invention.
Detailed Description
As shown in fig. 1 and 2, a method for detecting and isolating multiple faults of a steer-by-wire four-wheel electric forklift comprises the following steps in sequence:
(1) establishing an electric forklift three-degree-of-freedom dynamic model according to an electric forklift real vehicle;
(2) constructing a fault model according to a fault item and an unknown disturbance item of the forklift in the operation process and by combining with the established electric forklift dynamic model; various unknown interferences, such as environmental interference and input interference in the signal input process, can be encountered in the operation process of the forklift, and meanwhile, system components can also be in failure;
(3) determining the actual yaw rate w from the current driving state of the fork-lift truckrActual slip angular velocity prAnd the actual steering wheel angle value deltar；
(4) Designing an adaptive sliding mode variable structure observer, wherein a discontinuous switch item and an adaptive item determined according to a residual error are added;
(5) setting a self-adaptive sliding mode variable structure observer for each possible fault part to carry out fault monitoring, and setting different fault threshold values;
(6) the number of the set adaptive sliding mode variable structure observers is the same as that of the sensors or actuators, and the specific sensor or actuator is accurately judged to have a fault according to the residual error, and the specific fault time is judged;
(7) if the fault occurs, isolating the fault in time and reminding a driver of the occurrence of the fault;
(8) and (3) if no fault occurs, circularly executing the step (1) to the step (6) at set time intervals, and realizing fault detection and isolation of the wire-controlled four-wheel steering electric fork truck.
In the step (1), a three-degree-of-freedom dynamic model of the electric forklift of the steer-by-wire four-wheel electric forklift is established as follows:
according to the dynamic principle of the forklift, the following three equations are obtained:
determining the roll motion equation about the X-axis as given in equation (1):
Figure GDA0002497502070000071
determining the lateral motion equation about the Y axis as given in equation (2):
Figure GDA0002497502070000072
determining the yaw motion equation about the Z axis as given in equation (3):
Figure GDA0002497502070000073
Ixrotational inertia about the X axis for the suspended mass;
Figure GDA0002497502070000074
yaw angular acceleration;
Figure GDA0002497502070000075
is the roll angular acceleration; mxiThe component moment of each moment in the X-axis direction; i isxzThe inertia product of the finished automobile around the X axis and the Z axis; fYiThe component moment of each moment in the Y-axis direction; l isxAn external moment acting on the suspended mass in the X-axis direction; m is the vehicle mass;
Figure GDA0002497502070000076
is the lateral acceleration; u is the longitudinal forward speed; omega is yaw angular velocity; m issIs a sprung mass; h issThe vertical distance from the center of mass of the sprung mass to the central axis of the roll; fYIs the total external force along the Y-axis direction; i iszIs the moment of inertia about the Z axis; mziThe component moment of each moment in the Z-axis direction; mzIs the total external moment to the Z axis; p is the roll angular velocity;
determining a torque balance equation of the steer-by-wire four-wheel electric forklift, as shown in the formulas (4) to (6):
Figure GDA0002497502070000081
FY＝FY1+FY2+FY3+FY4(5)
Mz＝a(FY1+FY2)-b(FY3+FY4) (6)
since the fork truck phi value is small, sin phi is approximately equal to phi, cos phi is equal to 1, and the following equations can be obtained by combining (1) to (6):
Figure GDA0002497502070000082
FY1is the vertical load of the left wheel of the front axle; fY2Is the vertical load of the right wheel of the front axle; fY3Is the vertical load of the left wheel of the rear axle; fY4Is the vertical load of the right wheel of the rear axle; a. b is the distance from the center of mass of the forklift to the front axle and the rear axle respectively; g is the acceleration of gravity;
Figure GDA0002497502070000083
is the centroid slip angular velocity; k is a radical ofφSuspension roll stiffness; rfThe front axle side tilting rotation coefficient; c. CφDamping for suspension roll angle; phi is the vehicle body side inclination angle; deltafIs the corner of the front wheel of the forklift; deltarIs the corner of the rear wheel of the forklift; rrThe tilting direction coefficient of the rear shaft side is obtained; k is a radical offEquivalent cornering stiffness of front axle tires; k is a radical ofrEquivalent cornering stiffness of rear axle tires;
Figure GDA0002497502070000084
yaw angular acceleration;
taking the yaw angular velocity omega, the centroid slip angle β, the vehicle body roll angle phi and the roll angle velocity p as state variables, and writing the above equation into the following state space equation form:
Figure GDA0002497502070000085
in the formula:
Figure GDA0002497502070000086
Figure GDA0002497502070000087
Figure GDA0002497502070000091
M3＝[k1k1a 0 0]T
x(t)＝[ω β φ p]T；U＝δf；
wherein: u is an input item, and the input quantity is a front wheel steering angle; A. b, C, M1、M2、M3The matrix contains real truck data of the forklift.
In the step (2), the fault terms include an input interference term, a sensor fault term and an actuator fault term, and adding the input interference term, the sensor fault term and the actuator fault term can obtain a fault equation:
Figure GDA0002497502070000092
in the formula (I), the compound is shown in the specification,
Figure GDA0002497502070000093
xp(t) derivative of; x is the number ofp(t)∈Rn：xp(t)＝[ω β φ p]TNon-measurable state quantity u (t) ∈ Rl: inputting a vector; y isp(t)∈Rm: outputting the vector; dp: uncertain vectors such as unknown disturbances; d (t) is unknown perturbation; f. ofs∈Rm: a sensor fault vector; f. ofa∈Rm: an actuator fault vector; esp: a known sensor fault distribution matrix; eap: a known actuator fault distribution matrix; a. thep，Bp，Cp: a matrix of known constants;
for designing output items to be only in accordance with state quantities xp(T) related, presence of a non-singular transformation matrix T0Is transformed, among them
Figure GDA0002497502070000094
The system state equation can be expressed as:
Figure GDA0002497502070000095
wherein: a. the1、A2、A3、A4、B1、B2、C2、D2、E1、E2All given dimensions, from the relation
Figure GDA0002497502070000096
CpT0＝[0 C2]Determining a specific matrix by LMI tool box, wherein T0For setting matrices, x, artificially1∈R(n+h)×(n+h),x2∈Rp，A1∈R(n+h-p)×(n+h-p)，A2∈R(n+h-p)×p，A3∈Rp×(n+h-p)，A4∈Rp×p，B1∈R(n+h)-p，B2∈Rp，D2∈Rp×(q+h)，E1∈R(n+h)-p，E2∈Rp，C2∈Rp；
Base equation (9) on T0The transformation is to equation (10),
Figure GDA0002497502070000101
contains no fault term, only unknown disturbance term, A1、A2、B1、E1Is a parameter after mathematical transformation; in the same way, the method for preparing the composite material,
Figure GDA0002497502070000102
in which both fault terms and interference terms are contained, A3、A4、B2、D2、E2Is a parameter after mathematical transformation; y (t) ═ C2x2(t) C in2Are parameters after mathematical transformation.
In the step (3), the yaw rate w of the forklift in the current driving state is measured by using the yaw rate sensor, the side yaw rate sensor and the steering wheel angle sensor respectivelyrAngular yaw rate prSteering wheel angle value deltar(ii) a Voltage U of left front wheel driving motor measured by voltage sensorf1Voltage U of right front wheel driving motorf2Voltage U of driving motor of left rear wheelr1Voltage U of right rear wheel driving motorr2。
In the step (4), designing the adaptive sliding mode variable structure observer specifically includes:
Figure GDA0002497502070000103
wherein:
Figure GDA0002497502070000104
is a state quantity; u (t) is input quantity, and the input quantity is a rotation angle value; v is a discontinuous term; l is a matrix to be set;
Figure GDA0002497502070000105
disturbance observed by an observer;
Figure GDA0002497502070000106
is the output quantity;
defining a discontinuous term v, adding the discontinuous term v into an adaptive sliding mode variable structure observer,
Figure GDA0002497502070000107
where ζ is a suitable parameter; f is an adaptive matrix to be calculated; e.g. of the typeyGenerating a residual for the observer;
meanwhile, only fault information is included by utilizing residual errors, a fault estimation algorithm is designed, the algorithm comprises self-adaptive rate, and the algorithm expression is obtained as follows:
Figure GDA0002497502070000108
Figure GDA0002497502070000109
a fault estimation algorithm based on residual error，E0To design the dimensional matrix, eyFor state observation error, β is the variable structure parameter, and F is the adaptive matrix.
In the step (5), setting a threshold value of each sensor and each actuator, wherein the threshold value is the maximum value in a normal working state; yaw rate sensor threshold value μw(ii) a Yaw rate sensor threshold μp(ii) a Steering wheel angle sensor threshold value of muδ(ii) a The output voltage threshold value of the left front wheel driving motor is muf1(ii) a The output voltage threshold value of the right front wheel driving motor is mul2(ii) a The output voltage threshold of the left rear wheel driving motor is mur1(ii) a The output voltage threshold value of the right rear wheel drive motor is mur2；
When the yaw rate sensor fails, the output amount is we(ii) a When the yaw rate sensor fails, the output quantity is pe(ii) a When the steering wheel angle sensor fails, the output quantity is δe(ii) a The actuator is a direct current drive motor, the output torque of the motor is controlled by voltage, and the wheel rotation angle is further controlled, so when the actuator fails, the output quantity is the output voltage U of the left front wheel drive motorfe1Output voltage U of right front wheel driving motorfe2Output voltage U of left rear wheel driving motorre1Output voltage U of right rear wheel driving motorre2。
And (7) if the fault is judged to occur, isolating the fault, and prompting the fault to occur to a driver on a display screen of the cab and giving an alarm by a buzzer.
In the step (5), because the types of the actuators and the sensors are not used, the operating characteristics are different, different residual threshold values are required to be designed to judge whether each part in the system has a fault or not.
Setting a fault residual error threshold value of a yaw rate sensor to wmThe fault residual error threshold value of the yaw rate sensor is pmThe fault residual error threshold value of the steering wheel angle sensor is deltam. The output voltage threshold value of the left front wheel driving motor is mufm1(ii) a The output voltage threshold value of the right front wheel driving motor is mulm2(ii) a Left rear wheel driving motor transmissionThe output voltage threshold is murm1(ii) a The output voltage threshold value of the right rear wheel drive motor is murm2；
Take yaw rate sensor as an example, if | | | eyw||2≤wmThen the yaw rate sensor is not malfunctioning, otherwise if eyw||2＞wmThe yaw rate sensor fails. By analogy, the yaw rate sensor, the steering wheel angle sensor and the direct current driving motors of the wheels can detect whether faults occur by the method.
In step (6), if only the observer is set for the system component, only whether the system component is faulty or not can be found, and a specific fault point cannot be established. For the purpose of fault isolation, the specific location and time of occurrence of the fault needs to be determined. Therefore, by using the multi-observer fault isolation technology, observers with the same number as the sensors and actuators are designed, namely 11 sliding mode observers are designed, so that the residual error generated by the (j + 1) (j is 0,1, …,10) th observer (actuator) is not influenced by the fault signal of the sensor (actuator) and unknown input of the system, but only influenced by the fault signals generated by other sensors (actuators), and the specific sensor is in fault and the specific fault time can be accurately judged according to the residual error.
Assuming that a failure occurs for the (j + 1) th component, the following observer is constructed
Figure GDA0002497502070000111
Defining the following discrete terms simultaneously
Figure GDA0002497502070000121
Figure GDA0002497502070000122
Table 1 clearly expresses the form of the sensor fault discrimination rule, in which: "1" means that under the corresponding observer, the residual norm is not 0, i.e. no failure has occurred; "0" indicates that the residual norm is 0 under the corresponding observer, i.e., a failure occurs.
TABLE 1 rules for sensor fault discrimination
Figure GDA0002497502070000123
Table 2 clearly expresses the form of the actuator fault discrimination rule, in which: "1" means that under the corresponding observer, the residual norm is not 0, i.e. no failure has occurred; "0" indicates that the residual norm is 0 under the corresponding observer, i.e., a failure occurs.
Wherein yaw rate sensor malfunction fs1Yaw rate sensor failure fs2Steering wheel angle sensor failure fs3Left front wheel drive motor sensor fault fsa1Right front wheel drive motor sensor failure fsa2Left rear wheel drive motor sensor failure fsa3And the sensor fault f of the right rear wheel drive motorsa4。
TABLE 2 actuator Fault discrimination rules
Figure GDA0002497502070000131
Wherein, the sensor fault f of the left front wheel driving motora1Right front wheel drive motor sensor failure fa2Left rear wheel drive motor sensor failure fa3And the sensor fault f of the right rear wheel drive motora4。
In step 7, if a fault is judged to have occurred, fault isolation is actively performed, a sliding mode observer is used for state reconstruction, and the corresponding fault position '1' is displayed on a display screen in a cab to show the fault occurrence time and the specific position, so that the function of reminding a driver is achieved, accidents are prevented, and the safety and the stability of the forklift are ensured.
In conclusion, according to the structure and the working environment of the wire-controlled four-wheel steering electric fork truck, a three-degree-of-freedom whole truck model of the wire-controlled four-wheel steering electric fork truck is established; establishing a fault model according to the interference item and the fault item and by combining a whole vehicle model, and laying a foundation for the use of an observer; the adaptive sliding mode observer is arranged, variable structure parameters are added, unknown input interference can be effectively known, the adaptive rate is designed by utilizing residual signals, and the track can be better tracked; meanwhile, a multi-observer thought is utilized, and an observer is arranged for each part, so that the states of each sensor and each actuator can be observed by using a sliding-mode observer, and fault detection and state reconstruction can be performed; different residual error threshold values are designed for different types of sensors and actuators, so that faults can be effectively judged according to different conditions, and the characteristics that the residual error generated by an observer (actuator) is not influenced by the fault signal of the sensor (actuator) and unknown input of a system, but is only influenced by the fault signals generated by other sensors (actuators) are utilized, so that the specific sensor (actuator) is accurately judged according to the residual error, and the specific fault time is determined; finally, the display screen in the cab reminds the driver of when and which part of the forklift breaks down, so that the safety of the driver in a complex working environment is effectively ensured.

Claims (7)

1. A multi-fault detection and isolation method for a line-controlled four-wheel steering electric forklift is characterized by comprising the following steps: the method comprises the following steps in sequence:
(1) establishing an electric forklift three-degree-of-freedom dynamic model according to an electric forklift real vehicle;
(2) constructing a fault model according to a fault item and an unknown disturbance item of the forklift in the operation process and by combining with the established electric forklift dynamic model;
(3) determining the actual yaw rate w from the current driving state of the fork-lift truckrActual slip angular velocity prAnd the actual steering wheel angle value deltar；
(4) Designing an adaptive sliding mode variable structure observer, wherein a discontinuous switch item and an adaptive item determined according to a residual error are added;
(5) setting a self-adaptive sliding mode variable structure observer for each possible fault part to carry out fault monitoring, and setting different fault threshold values;
(6) the number of the set adaptive sliding mode variable structure observers is the same as that of the sensors or actuators, and the specific sensor or actuator is accurately judged to have a fault according to the residual error, and the specific fault time is judged;
(7) if the fault occurs, isolating the fault in time and reminding a driver of the occurrence of the fault;
(8) and (3) if no fault occurs, circularly executing the step (1) to the step (6) at set time intervals, and realizing fault detection and isolation of the wire-controlled four-wheel steering electric fork truck.
2. The method of multiple fault detection and isolation for a four-wheel-steering-by-wire electric fork lift of claim 1, wherein: in the step (1), a three-degree-of-freedom dynamic model of the electric forklift of the steer-by-wire four-wheel electric forklift is established as follows:
according to the dynamic principle of the forklift, the following three equations are obtained:
determining the roll motion equation about the X-axis as given in equation (1):
Figure FDA0002417854080000011
determining the lateral motion equation about the Y axis as given in equation (2):
Figure FDA0002417854080000012
determining the yaw motion equation about the Z axis as given in equation (3):
Figure FDA0002417854080000013
Ixrotational inertia about the X axis for the suspended mass;
Figure FDA0002417854080000014
yaw angular acceleration;
Figure FDA0002417854080000015
is the roll angular acceleration; mxiThe component moment of each moment in the X-axis direction; i isxzThe inertia product of the finished automobile around the X axis and the Z axis; fYiThe component moment of each moment in the Y-axis direction; l isxAn external moment acting on the suspended mass in the X-axis direction; m is the vehicle mass;
Figure FDA0002417854080000026
is the lateral acceleration; u is the longitudinal forward speed; omega is yaw angular velocity; m issIs a sprung mass; h issThe vertical distance from the center of mass of the sprung mass to the central axis of the roll; fYIs the total external force along the Y-axis direction; i iszIs the moment of inertia about the Z axis; mziThe component moment of each moment in the Z-axis direction; mzIs the total external moment to the Z axis; p is the roll angular velocity;
determining a torque balance equation of the steer-by-wire four-wheel electric forklift, as shown in the formulas (4) to (6):
Figure FDA0002417854080000021
FY＝FY1+FY2+FY3+FY4(5)
Mz＝a(FY1+FY2)-b(FY3+FY4) (6)
since the fork truck phi value is small, sin phi is approximately equal to phi, cos phi is equal to 1, and the following equations can be obtained by combining (1) to (6):
Figure FDA0002417854080000022
FY1is the vertical load of the left wheel of the front axle; fY2Is the vertical load of the right wheel of the front axle; fY3Is the vertical load of the left wheel of the rear axle; fY4Is the vertical load of the right wheel of the rear axle; a. b is the distance from the center of mass of the forklift to the front axle and the rear axle respectively; g is the acceleration of gravity;
Figure FDA0002417854080000023
is the centroid slip angular velocity; k is a radical ofφSuspension roll stiffness; rfThe front axle side tilting rotation coefficient; c. CφDamping for suspension roll angle; phi is the vehicle body side inclination angle; deltafIs the corner of the front wheel of the forklift; deltarIs the corner of the rear wheel of the forklift; rrThe tilting direction coefficient of the rear shaft side is obtained; k is a radical offEquivalent cornering stiffness of front axle tires; k is a radical ofrEquivalent cornering stiffness of rear axle tires;
Figure FDA0002417854080000024
yaw angular acceleration;
taking the yaw angular velocity omega, the centroid slip angle β, the vehicle body roll angle phi and the roll angle velocity p as state variables, and writing the above equation into the following state space equation form:
Figure FDA0002417854080000025
in the formula:
Figure FDA0002417854080000031
Figure FDA0002417854080000032
Figure FDA0002417854080000033
M3＝[k1k1a 0 0]T
x(t)＝[ω β φ p]T；U＝δf；
wherein: u is an input item, and the input quantity is a front wheel steering angle; A. b, C, M1、M2、M3The matrix contains real truck data of the forklift.
3. The method of multiple fault detection and isolation for a four-wheel-steering-by-wire electric fork lift of claim 1, wherein: in the step (2), the fault terms include an input interference term, a sensor fault term and an actuator fault term, and adding the input interference term, the sensor fault term and the actuator fault term can obtain a fault equation:
Figure FDA0002417854080000034
in the formula (I), the compound is shown in the specification,
Figure FDA0002417854080000035
xp(t) derivative of; x is the number ofp(t)∈Rn：xp(t)＝[ω β φ p]TNon-measurable state quantity u (t) ∈ Rl: inputting a vector; y isp(t)∈Rm: outputting the vector; dp: uncertain vectors such as unknown disturbances; d (t) is unknown perturbation; f. ofs∈Rm: a sensor fault vector; f. ofa∈Rm: an actuator fault vector; esp: a known sensor fault distribution matrix; eap: a known actuator fault distribution matrix; a. thep，Bp，Cp: a matrix of known constants;
for designing output items to be only in accordance with state quantities xp(T) related, presence of a non-singular transformation matrix T0Is transformed, among them
Figure FDA0002417854080000036
The system state equation can be expressed as:
Figure FDA0002417854080000041
wherein: a. the1、A2、A3、A4、B1、B2、C2、D2、E1、E2All given dimensions, from the relation
Figure FDA0002417854080000042
CpT0＝[0 C2]Determining a specific matrix by LMI tool box, wherein T0For setting matrices, x, artificially1∈R(n+h)×(n+h),x2∈Rp，A1∈R(n +h-p)×(n+h-p)，A2∈R(n+h-p)×p，A3∈Rp×(n+h-p)，A4∈Rp×p，B1∈R(n+h)-p，B2∈Rp，D2∈Rp×(q+h)，E1∈R(n +h)-p，E2∈Rp，C2∈Rp；
Base equation (9) on T0The transformation is to equation (10),
Figure FDA0002417854080000043
contains no fault term, only unknown disturbance term, A1、A2、B1、E1Is a parameter after mathematical transformation; in the same way, the method for preparing the composite material,
Figure FDA0002417854080000044
in which both fault terms and interference terms are contained, A3、A4、B2、D2、E2Is a parameter after mathematical transformation; y (t) ═ C2x2(t) C in2Are parameters after mathematical transformation.
4. The method of multiple fault detection and isolation for a four-wheel-steering-by-wire electric fork lift of claim 1, wherein: in the step (3), the yaw rate w of the forklift in the current driving state is measured by using the yaw rate sensor, the side yaw rate sensor and the steering wheel angle sensor respectivelyrAngular yaw rate prSteering wheel angle value deltar(ii) a Voltage U of left front wheel driving motor measured by voltage sensorf1Voltage U of right front wheel driving motorf2Voltage U of driving motor of left rear wheelr1Right rear wheelVoltage U of driving motorr2。
5. The method of multiple fault detection and isolation for a four-wheel-steering-by-wire electric fork lift of claim 1, wherein: in the step (4), designing the adaptive sliding mode variable structure observer specifically includes:
Figure FDA0002417854080000045
wherein:
Figure FDA0002417854080000046
is a state quantity; u (t) is input quantity, and the input quantity is a rotation angle value; v is a discontinuous term; l is a matrix to be set;
Figure FDA0002417854080000047
disturbance observed by an observer;
Figure FDA0002417854080000048
is the output quantity;
defining a discontinuous term v, adding the discontinuous term v into an adaptive sliding mode variable structure observer,
Figure FDA0002417854080000051
where ζ is a suitable parameter; f is an adaptive matrix to be calculated; e.g. of the typeyGenerating a residual for the observer;
meanwhile, only fault information is included by utilizing residual errors, a fault estimation algorithm is designed, the algorithm comprises self-adaptive rate, and the algorithm expression is obtained as follows:
Figure FDA0002417854080000052
Figure FDA0002417854080000053
a fault estimation algorithm based on residual errors, E0To design the dimensional matrix, eyFor state observation error, β is the variable structure parameter, and F is the adaptive matrix.
6. The method of multiple fault detection and isolation for a four-wheel-steering-by-wire electric fork lift of claim 1, wherein: in the step (5), setting a threshold value of each sensor and each actuator, wherein the threshold value is the maximum value in a normal working state; yaw rate sensor threshold value μw(ii) a Yaw rate sensor threshold μp(ii) a Steering wheel angle sensor threshold value of muδ(ii) a The output voltage threshold value of the left front wheel driving motor is muf1(ii) a The output voltage threshold value of the right front wheel driving motor is mul2(ii) a The output voltage threshold of the left rear wheel driving motor is mur1(ii) a The output voltage threshold value of the right rear wheel drive motor is mur2；
When the yaw rate sensor fails, the output amount is we(ii) a When the yaw rate sensor fails, the output quantity is pe(ii) a When the steering wheel angle sensor fails, the output quantity is δe(ii) a The actuator is a direct current drive motor, the output torque of the motor is controlled by voltage, and the wheel rotation angle is further controlled, so when the actuator fails, the output quantity is the output voltage U of the left front wheel drive motorfe1Output voltage U of right front wheel driving motorfe2Output voltage U of left rear wheel driving motorre1Output voltage U of right rear wheel driving motorre2。
7. The method of multiple fault detection and isolation for a four-wheel-steering-by-wire electric fork lift of claim 1, wherein: and (7) if the fault is judged to occur, isolating the fault, and prompting the fault to occur to a driver on a display screen of the cab and giving an alarm by a buzzer.
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