A method and system for optimizing control of boom amplitude and telescopic speed of off-road forklift

Abstract

The present invention provides a method and system for optimizing the control of the boom amplitude and telescopic speed of an off-road forklift, which relates to the field of speed control technology, including: formulating an adaptive identification strategy for accessories and selecting a corresponding accessory type; collecting working posture and pressure data; constructing a load torque dynamic solution algorithm based on the working posture, pressure data and accessory type to obtain real-time load torque; constructing safety boundary constraints based on the real-time load torque to obtain a safety constraint speed instruction; obtaining an optimal speed instruction based on the safety constraint speed instruction and the accessory type; constructing a motor speed closed-loop control algorithm based on an adaptive anti-interference algorithm and based on the optimal speed instruction to obtain a motor drive voltage; obtaining a solenoid valve opening instruction based on a neural network inverse model and based on the optimal speed instruction; and controlling the speed of the off-road forklift arm of the corresponding accessory type based on the motor drive voltage and the solenoid valve opening instruction.

Description

Technical Field

[0001] The present invention relates to the technical field of speed control, and in particular to a method and system for optimizing control of boom amplitude and telescopic speed of an off-road forklift. Background Art

[0002] With the continuous expansion of industrial production scale and the increasingly complex working environment, higher requirements are placed on the performance and safety of off-road forklifts.

[0003] In actual operations, off-road forklifts need to frequently adjust and extend the boom, and their speed control directly affects operational efficiency and safety. Traditional forklift speed control systems have many limitations: on the one hand, they have poor adaptability to different attachments and are unable to automatically adjust the control strategy according to the type of attachment. For example, when replacing different attachments such as spreaders and fork tines, it is difficult to accurately match the corresponding operational requirements, resulting in low operational efficiency and even possible safety accidents. On the other hand, the ability to respond to load changes is insufficient. When the load torque changes dynamically, the speed cannot be adjusted in a timely and accurate manner, which can easily cause problems such as boom shaking and cargo falling.

[0004] Therefore, a method and system for optimizing the control of boom amplitude and telescopic speed of an off-road forklift is provided. Summary of the Invention

[0005] In order to solve the above technical problems, the purpose of the present invention is to provide a method and system for optimizing the control of the boom amplitude and telescopic speed of an off-road forklift.

[0006] In order to achieve the above-mentioned object, the present invention provides the following technical solution: a method for optimizing the control of the boom amplitude and telescopic speed of an off-road forklift, comprising the following steps:

[0007] Formulate an adaptive identification strategy for attachments, and select a corresponding attachment type based on the adaptive identification strategy; collect working posture data of the boom of a rough-terrain forklift of the corresponding attachment type and pressure data of the oil cylinder of the rough-terrain forklift;

[0008] According to the working posture, pressure data and attachment type, a load torque dynamic solution algorithm is constructed, and the real-time load torque of the off-road forklift boom corresponding to the attachment type is obtained according to the load torque dynamic solution algorithm;

[0009] Constructing a safety boundary constraint condition based on the real-time load torque; obtaining a safety constraint speed instruction for the boom of an off-road forklift corresponding to the attachment type based on the safety boundary constraint condition;

[0010] According to the safety constraint speed command and the attachment type, the optimal speed command of the off-road forklift boom with the corresponding attachment type is obtained;

[0011] Based on the adaptive anti-interference algorithm and the optimal speed command, a closed-loop control algorithm for the motor speed is constructed to obtain the motor drive voltage for the corresponding off-road forklift with the corresponding attachment type;

[0012] Based on the neural network inverse model and according to the optimal speed instruction, the solenoid valve opening instruction of the corresponding attachment type off-road forklift is obtained; according to the motor drive voltage and the solenoid valve opening instruction, the speed of the arm frame of the corresponding attachment type off-road forklift is controlled.

[0013] According to one preferred embodiment of the present invention, an attachment adaptive recognition strategy is formulated. The process of selecting a corresponding attachment type according to the attachment adaptive recognition strategy includes:

[0014] Through the hard-wire signal of the off-road forklift, an attachment feature database is established, which includes: , attachment type name, attachment initial lever arm length and safety threshold;

[0015] According to the accessory feature database, an accessory adaptive recognition strategy is formulated, and the accessory adaptive recognition strategy is:

[0016] ;in, It is a database of attribute characteristics; For accessories .

[0017] According to one preferred embodiment of the present invention, the process of collecting the working posture data of the boom of an off-road forklift corresponding to the attachment type and the pressure data of the oil cylinder of the off-road forklift includes:

[0018] According to the wire sensor, angle sensor, and pressure sensor installed in the off-road forklift, a collection cycle is set, and the boom telescopic displacement, boom amplitude adjustment angle, and pressure data of the off-road forklift boom corresponding to the accessory type are collected according to the collection cycle; the boom telescopic displacement and boom amplitude adjustment angle are uniformly recorded as the working posture.

[0019] According to one preferred embodiment of the present invention, a load moment dynamic solution algorithm is constructed. According to the load moment dynamic solution algorithm, the process of obtaining the real-time load moment of the off-road forklift boom includes:

[0020] The collected boom telescopic displacement, boom amplitude angle and pressure data are recorded as 、 as well as ;

[0021] According to the telescopic displacement of the boom , boom luffing angle , pressure data and attachment types , construct a load moment dynamic solution algorithm; the load moment dynamic solution algorithm is:

[0022] ;in, is the real-time load torque; is the real-time cross-sectional area of ​​the rough terrain forklift cylinder; is the efficiency coefficient of the hydraulic system, which is obtained by relevant technical personnel looking up the table; is the lever arm function of the off-road forklift; the lever arm function for:

[0023] ;in, For the corresponding attachment type The initial lever arm length.

[0024] According to one preferred embodiment of the present invention, a process of constructing a safety boundary constraint condition and obtaining a safety constraint speed instruction corresponding to an off-road forklift boom of an attachment type according to the safety boundary constraint condition includes:

[0025] Get real-time load torque And the boom angle ;

[0026] Preset safe load torque threshold and the safety boom angle threshold ;

[0027] According to the real-time load torque , boom luffing angle , safe load torque threshold and the safety boom angle threshold , construct safety boundary constraints; the safety boundary constraints are:

[0028] ;in, To constrain speed instructions for safety; is the original speed command.

[0029] According to one preferred embodiment of the present invention, the process of obtaining the optimal speed instruction for a rough terrain forklift boom corresponding to the attachment type according to the safety constraint speed instruction and the attachment type includes:

[0030] Get safety constraint speed command ;

[0031] According to the safety-constrained speed command , construct a multi-objective optimization control algorithm; the multi-objective optimization control algorithm is:

[0032] ;in, is the optimal speed instruction; It is a multi-objective particle swarm optimization algorithm; To minimize the boom action time; To minimize the standard deviation of speed fluctuation; It is the mechanical limit speed of the preset boom movement.

[0033] According to one preferred embodiment of the present invention, a process for constructing a motor speed closed-loop control algorithm based on an adaptive anti-interference algorithm and an optimal speed command to obtain a motor drive voltage for an off-road forklift with corresponding attachment type includes:

[0034] Get the optimal speed instruction ;

[0035] Based on the adaptive anti-interference algorithm, a motor speed closed-loop control algorithm is constructed; the motor speed closed-loop control algorithm is:

[0036] ;in, is the motor driving voltage; is the power magnification factor; Dynamic correction of the proportional coefficient; is the speed error; is the integration coefficient; is the differential coefficient.

[0037] According to one preferred embodiment of the present invention, based on a neural network inverse model and according to an optimal speed command, a solenoid valve opening command corresponding to an off-road forklift with an attachment type is obtained; and according to the motor drive voltage and the solenoid valve opening command, a process of controlling the speed of the boom of the off-road forklift with an attachment type includes:

[0038] Based on the neural network inverse model and according to the optimal speed instruction , construct a solenoid valve decoupling control model: the solenoid valve decoupling control model is:

[0039] ;in, 、 is the solenoid valve opening instruction; is the amplitude variation speed; is the telescopic speed; It is the inverse model obtained by neural network training.

[0040] An off-road forklift boom luffing and telescopic speed optimization control system includes: a forklift data acquisition module, an attachment identification module, a load torque calculation module, a torque control module, a main control module, and an execution control module;

[0041] An attachment recognition module is used to formulate an attachment adaptive recognition strategy and select a corresponding attachment type according to the attachment adaptive recognition strategy;

[0042] Forklift data acquisition module, used to collect the working posture of the off-road forklift boom and the pressure data of the off-road forklift cylinder corresponding to the attachment type;

[0043] The load torque calculation module constructs a load torque dynamic calculation algorithm based on the working posture, pressure data, and attachment type, and obtains the real-time load torque of the off-road forklift boom according to the load torque dynamic calculation algorithm;

[0044] The torque control module constructs a safety boundary constraint condition based on the real-time load torque; and obtains a safety constraint speed instruction for the off-road forklift boom based on the safety boundary constraint condition;

[0045] The main control module builds a multi-objective optimization control algorithm based on the safety constraint speed command and the attachment type to obtain the optimal speed command for the off-road forklift boom;

[0046] The execution control module constructs a motor speed closed-loop control algorithm based on an adaptive anti-interference algorithm and according to an optimal speed instruction, thereby obtaining the motor drive voltage of the off-road forklift; obtains the solenoid valve opening instruction of the off-road forklift based on an inverse neural network model and according to the optimal speed instruction; and controls the speed of the off-road forklift boom according to the motor drive voltage and the solenoid valve opening instruction.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] The collaborative work of multiple modules, including the attachment recognition module and the load torque calculation module, significantly improves the safety of off-road forklift operations. The attachment recognition module adaptively identifies attachment types, providing the basis for subsequent precise control. The load torque calculation module calculates load torque in real time based on working posture, pressure data, and attachment type. The torque control module uses this information to establish safety boundary constraints and derive safe speed instructions. This effectively avoids safety accidents caused by overloading or improper speed, ensures stable and safe operation of the forklift in complex working conditions, and reduces the risk of equipment damage and operator safety hazards.

[0049] The main control module combines the safety constraint speed command and the attachment type to construct a multi-objective optimization control algorithm to obtain the optimal speed command. The execution control module constructs the motor speed closed-loop control algorithm and the solenoid valve opening control algorithm based on the adaptive anti-interference algorithm and the neural network inverse model, respectively, to accurately control the motor drive voltage and the solenoid valve opening, to achieve precise control of the boom amplitude and extension speed, reduce the action response time, improve the accuracy and smoothness of cargo handling, meet the efficient and precise operation requirements of different operation scenarios, and help enterprises improve production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction to the drawings required for use in the embodiments will be given below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0051] Figure 1 The figure is a schematic diagram of the steps of an optimization control method for the boom amplitude and telescopic speed of an off-road forklift.

[0052] Figure 2 The diagram shows a module diagram of an optimized control system for boom luffing and telescopic speed of an off-road forklift. DETAILED DESCRIPTION

[0053] To make the objectives, technical solutions, and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other implementations obtained by those of ordinary skill in the art without inventive effort are within the scope of protection of the present invention.

[0054] like Figure 1 As shown, a method for optimizing the control of boom amplitude and telescopic speed of an off-road forklift includes the following steps:

[0055] Formulate an adaptive identification strategy for attachments, and select a corresponding attachment type based on the adaptive identification strategy; collect working posture data of the boom of a rough-terrain forklift of the corresponding attachment type and pressure data of the oil cylinder of the rough-terrain forklift;

[0056] According to the working posture, pressure data and attachment type, a load torque dynamic solution algorithm is constructed, and the real-time load torque of the off-road forklift boom corresponding to the attachment type is obtained according to the load torque dynamic solution algorithm;

[0057] Constructing a safety boundary constraint condition based on the real-time load torque; obtaining a safety constraint speed instruction for the boom of an off-road forklift corresponding to the attachment type based on the safety boundary constraint condition;

[0058] According to the safety constraint speed command and the attachment type, the optimal speed command of the off-road forklift boom with the corresponding attachment type is obtained;

[0059] Based on the adaptive anti-interference algorithm and the optimal speed command, a closed-loop control algorithm for the motor speed is constructed to obtain the motor drive voltage for the corresponding off-road forklift with the corresponding attachment type;

[0060] Based on the neural network inverse model and according to the optimal speed instruction, the solenoid valve opening instruction of the corresponding attachment type off-road forklift is obtained; according to the motor drive voltage and the solenoid valve opening instruction, the speed of the arm frame of the corresponding attachment type off-road forklift is controlled.

[0061] It should be further explained that, in the specific implementation process, the attachment adaptive recognition strategy is formulated. The specific process of selecting the corresponding attachment type according to the attachment adaptive recognition strategy includes:

[0062] Through the hard-wire signal of the off-road forklift, an attachment feature database is established, which includes: , accessory type name, accessory initial lever arm length and safety threshold; it should be further explained that the initial lever arm length and safety threshold of different accessories are different; the safety threshold includes: the safety load torque threshold of the corresponding accessory and the safety arm range angle threshold.

[0063] According to the accessory feature database, an accessory adaptive recognition strategy is formulated, and the accessory adaptive recognition strategy is:

[0064] ;in, It is a database of attribute characteristics; For accessories .

[0065] For example, the attachment type names are: Rotary Fork, Wood Fork, and Bale Clamp; define the corresponding attachments for Rotary Fork, Wood Fork, and Bale Clamp. , respectively as well as , by traversing the attribute feature database In the corresponding accessories ,like If you do not attach : , in the accessory feature database If defined in Corresponding accessories are not included.

[0066] It should be further explained that, in the specific implementation process, the specific process of collecting the working posture of the boom of the off-road forklift corresponding to the attachment type and the pressure data of the off-road forklift cylinder includes:

[0067] According to the wire sensor, angle sensor, and pressure sensor installed in the off-road forklift, a collection cycle is set, and the boom telescopic displacement, boom amplitude adjustment angle, and pressure data of the off-road forklift boom corresponding to the accessory type are collected according to the collection cycle; it should be further explained that the boom telescopic displacement and boom amplitude adjustment angle are uniformly recorded as working posture.

[0068] It should be further explained that, in the specific implementation process, a load moment dynamic solution algorithm is constructed. According to the load moment dynamic solution algorithm, the specific process of obtaining the real-time load moment of the off-road forklift boom includes:

[0069] The collected boom telescopic displacement, boom amplitude angle and pressure data are recorded as 、 as well as It should be further explained that the telescopic displacement of the arm , boom luffing angle , pressure data It is based on data collected in a real-time collection cycle to facilitate real-time optimization control of the off-road forklift boom.

[0070] According to the telescopic displacement of the boom , boom luffing angle , pressure data and attachment types , construct a load moment dynamic solution algorithm; the load moment dynamic solution algorithm is:

[0071] ;in, is the real-time load torque; is the real-time cross-sectional area of ​​the rough terrain forklift cylinder; is the efficiency coefficient of the hydraulic system, which is obtained by relevant technical personnel looking up the table; is the lever arm function of the off-road forklift; it should be further explained that the lever arm function for:

[0072] ;in, For the corresponding attachment type The initial lever arm length.

[0073] For example, if the attachment type is a rotary fork, the corresponding initial arm length of the attachment is Meters; boom telescopic displacement is Meters; boom angle is ;The pressure data of the oil cylinder is ;The real-time cross-sectional area of ​​the cylinder is ; The efficiency coefficient of the hydraulic system is ; The force arm function is ;The real-time load torque is .

[0074] It should be further explained that, in the specific implementation process, the safety boundary constraint condition is constructed; and according to the safety boundary constraint condition, the specific process of obtaining the safety constraint speed instruction of the boom of the off-road forklift corresponding to the attachment type includes:

[0075] Get real-time load torque And the boom angle ;

[0076] Preset safe load torque threshold and the safety boom angle threshold ;

[0077] According to the real-time load torque , boom luffing angle , safe load torque threshold and the safety boom angle threshold , construct safety boundary constraints; the safety boundary constraints are:

[0078] ;in, To constrain speed instructions for safety; is the original speed instruction; it should be further explained that the original speed instruction This is the target speed that has not been verified by the safety threshold and is the original boom speed command generated based on the actual operation requirements of the off-road forklift.

[0079] For example, if the attachment type is a rotary fork, the real-time load torque is ; The corresponding safe load torque threshold is ; If the original speed command is ;Safety constraint speed command decelerates to .

[0080] It should be further explained that, in the specific implementation process, according to the safety constraint speed command and the attachment type, the specific process of obtaining the optimal speed command for the off-road forklift boom corresponding to the attachment type includes:

[0081] Get safety constraint speed command ;

[0082] According to the safety-constrained speed command , construct a multi-objective optimization control algorithm; the multi-objective optimization control algorithm is:

[0083] ;in, is the optimal speed instruction; It is a multi-objective particle swarm optimization algorithm; To minimize the boom action time; To minimize the standard deviation of speed fluctuation; It is the mechanical limit speed of the preset boom movement.

[0084] For example, if the attachment type is a rotary fork, the safety constraint speed command for , preset the mechanical limit speed of the boom movement for ; Real-time load torque for ; The target displacement is ;Weight distribution: , ; The number of particles in the particle swarm parameters based on the multi-objective particle swarm optimization algorithm is set to The number of iterations is set to Second, the inertia weight is given by Decrease to , learning factor , baseline value setting: ; ; Randomly generated Initial speed values, such as: 45, 38, 50, 42, 30, 48, 41, 35, 46, 43, 39, 47, 37, 44, 36, 49, 34, 40, 50, 45 , and generates The initial speeds are all less than or equal to the safety constraint speed command ; Boom action time ; Speed ​​fluctuation standard deviation ; Fitness ; Update particle velocity ;in, The best particle speed in history; is the optimal particle speed;

[0085] Iteration Times: Inertia weight is , random number , ;

[0086] Particle 1 speed , , speed fluctuation standard deviation , fitness ;

[0087] Particle 2 Speed , , speed fluctuation standard deviation , fitness ; Particle 2 speed Optimal fitness Optimal;

[0088] Introduce in sequence and calculate all 's adaptability.

[0089] Update particle 1 velocity ;

[0090] Push inward in sequence and update the corresponding .

[0091] Iteration Times: Inertia weight is , random number , ; Introduce in sequence and calculate all The fitness and update corresponding .

[0092] Iteration Times: Inertia weight is , random number , ; Introduce in sequence and calculate all The fitness and update corresponding After 50 iterations, the optimal speed instruction for .

[0093] It should be further explained that, in the specific implementation process, based on the adaptive anti-interference algorithm and according to the optimal speed command, a motor speed closed-loop control algorithm is constructed to obtain the motor drive voltage of the off-road forklift with the corresponding attachment type. The specific process includes:

[0094] Get the optimal speed instruction ;

[0095] Based on the adaptive anti-interference algorithm, a motor speed closed-loop control algorithm is constructed; the motor speed closed-loop control algorithm is:

[0096] ;in, is the motor driving voltage; is the power magnification factor; Dynamic correction of the proportional coefficient; is the speed error; is the integration coefficient; is the differential coefficient; it should be further explained that the speed error for: ;in, The actual speed fed back by the motor encoder; the proportional coefficient is dynamically corrected for: ;in, Basic scale factor; disturbance amplitude; is the disturbance frequency; is the disturbance phase.

[0097] For example, if the attachment type is a rotary fork, the collection cycle for ; Current time for ;Optimal speed instruction ;Actual speed fed back by the motor encoder ; Based on the adaptive anti-interference algorithm parameters: the basic proportional coefficient is , the disturbance amplitude is , the disturbance frequency is 50 , the perturbation phase is , , ; The power amplification factor is ; Before preset The speed errors of each cycle are ; Speed ​​error ; Dynamic correction of proportional coefficient ;

[0098] is the motor drive voltage .

[0099] It should be further explained that, in a specific implementation process, based on the neural network inverse model and according to the optimal speed command, the solenoid valve opening command of the corresponding off-road forklift with an attachment type is obtained; and according to the motor drive voltage and the solenoid valve opening command, the specific process of controlling the speed of the boom of the corresponding off-road forklift with an attachment type includes:

[0100] Based on the neural network inverse model and according to the optimal speed instruction , construct a solenoid valve decoupling control model: the solenoid valve decoupling control model is:

[0101] ;in, 、 is the solenoid valve opening instruction; is the amplitude variation speed; is the telescopic speed; is the inverse model obtained by neural network training; it needs to be further explained that, It is the solenoid valve opening instruction for the amplitude variation operation; Solenoid valve opening instruction for telescopic operation; amplitude change speed for: ; Extension speed for: ;in, is the adaptive weight factor.

[0102] For example, if the attachment type is a rotary fork, the amplitude adjustment angle is ; The current angle is ; The telescopic distance is ; The current distance is ; The action time constraint is ; The effective radius of the luffing cylinder is ;Optimal speed instruction ; Luffing speed ; Extension speed ; Neural network inverse model output decoupling matrix ; Solenoid valve opening instruction ;Converted into the solenoid valve opening instruction of percentage amplitude operation ; Solenoid valve opening instruction for percentage telescopic operation ; But the solenoid valve opening cannot be negative. Solenoid valve opening instruction for telescopic operation Minimum .

[0103] According to the motor drive voltage , solenoid valve opening instruction 、 , to control the boom speed and telescopic speed of the off-road forklift boom with corresponding attachment type.

[0104] like Figure 2 As shown, an off-road forklift boom amplitude and extension speed optimization control system includes: a forklift data acquisition module, an attachment identification module, a load torque calculation module, a torque control module, a main control module and an execution control module;

[0105] An attachment recognition module is used to formulate an attachment adaptive recognition strategy and select a corresponding attachment type according to the attachment adaptive recognition strategy;

[0106] Forklift data acquisition module, used to collect the working posture of the off-road forklift boom and the pressure data of the off-road forklift cylinder corresponding to the attachment type;

[0107] The load torque calculation module constructs a load torque dynamic calculation algorithm based on the working posture, pressure data, and attachment type, and obtains the real-time load torque of the off-road forklift boom according to the load torque dynamic calculation algorithm;

[0108] The torque control module constructs a safety boundary constraint condition based on the real-time load torque; and obtains a safety constraint speed instruction for the off-road forklift boom based on the safety boundary constraint condition;

[0109] The main control module builds a multi-objective optimization control algorithm based on the safety constraint speed command and the attachment type to obtain the optimal speed command for the off-road forklift boom;

[0110] The execution control module constructs a motor speed closed-loop control algorithm based on an adaptive anti-interference algorithm and according to an optimal speed instruction, thereby obtaining the motor drive voltage of the off-road forklift; obtains the solenoid valve opening instruction of the off-road forklift based on an inverse neural network model and according to the optimal speed instruction; and controls the speed of the off-road forklift boom according to the motor drive voltage and the solenoid valve opening instruction.

[0111] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for optimizing the control of boom length and telescopic speed of an off-road forklift, characterized in that: The following steps are involved: Develop an adaptive identification strategy for attachments, including: Through the hard-wire signal of the off-road forklift, an attachment feature database is established, which includes: , attachment type name, attachment initial lever arm length and safety threshold; According to the accessory feature database, an accessory adaptive recognition strategy is formulated, and the accessory adaptive recognition strategy is: ;in, It is a database of attribute characteristics; For accessories ; According to the attachment adaptive identification strategy, a corresponding attachment type is selected; and working posture data of the boom of the off-road forklift of the corresponding attachment type and pressure data of the oil cylinder of the off-road forklift are collected, including: According to the pull wire sensor, angle sensor, and pressure sensor provided in the off-road forklift, a collection period is set, and the telescopic displacement of the boom of the off-road forklift corresponding to the attachment type, the boom amplitude angle, and the pressure data of the off-road forklift cylinder are respectively collected according to the collection period; the telescopic displacement of the boom and the boom amplitude angle are uniformly recorded as the working posture; Based on the working posture, pressure data, and attachment type, a load torque dynamic calculation algorithm is constructed. According to the load torque dynamic calculation algorithm, the real-time load torque of the off-road forklift boom corresponding to the attachment type is obtained, including: The collected boom telescopic displacement, boom amplitude angle and pressure data are recorded as 、 as well as ; According to the telescopic displacement of the boom , boom luffing angle , pressure data and attachment types , construct a load moment dynamic solution algorithm; the load moment dynamic solution algorithm is: ;in, is the real-time load torque; is the real-time cross-sectional area of ​​the rough terrain forklift cylinder; is the efficiency coefficient of the hydraulic system, which is obtained by relevant technical personnel looking up the table; is the lever arm function of the off-road forklift; the lever arm function for: ;in, For the corresponding attachment type The initial lever arm length; Constructing a safety boundary constraint condition based on the real-time load torque; obtaining a safety constraint speed instruction for the boom of an off-road forklift corresponding to the attachment type based on the safety boundary constraint condition; According to the safety constraint speed command and the attachment type, the optimal speed command of the off-road forklift boom with the corresponding attachment type is obtained; Based on the adaptive anti-interference algorithm and the optimal speed command, a closed-loop control algorithm for the motor speed is constructed to obtain the motor drive voltage for the corresponding off-road forklift with the corresponding attachment type; Based on the neural network inverse model and according to the optimal speed instruction, the solenoid valve opening instruction of the corresponding attachment type off-road forklift is obtained; according to the motor drive voltage and the solenoid valve opening instruction, the speed of the arm frame of the corresponding attachment type off-road forklift is controlled.

2. The method for optimizing control of boom luffing and telescopic speed of an off-road forklift according to claim 1, characterized in that: Constructing safety boundary constraints; According to the safety boundary constraint condition, the process of obtaining the safety constraint speed instruction corresponding to the off-road forklift boom of the attachment type includes: Get real-time load torque And the boom angle ; Preset safe load torque threshold and the safety boom angle threshold ; According to the real-time load torque , boom luffing angle , safe load torque threshold and the safety boom angle threshold , construct safety boundary constraints; the safety boundary constraints are: ;in, To constrain speed instructions for safety; is the original speed command.

3. The method for optimizing control of boom length and telescopic speed of an off-road forklift according to claim 2, characterized in that: The process of obtaining the optimal speed command for the boom of a rough terrain forklift with the corresponding attachment type according to the safety constraint speed command and the attachment type includes: Get safety constraint speed command ; According to the safety-constrained speed command , construct a multi-objective optimization control algorithm; the multi-objective optimization control algorithm is: ;in, is the optimal speed instruction; It is a multi-objective particle swarm optimization algorithm; To minimize the boom action time; To minimize the standard deviation of speed fluctuation; It is the mechanical limit speed of the preset boom movement.

4. The method for optimizing control of boom amplitude and telescopic speed of an off-road forklift according to claim 3, characterized in that: Based on the adaptive anti-interference algorithm and the optimal speed command, a closed-loop motor speed control algorithm is constructed to obtain the motor drive voltage for the corresponding off-road forklift with the corresponding attachment type. The process includes: Get the optimal speed instruction ; Based on the adaptive anti-interference algorithm, a motor speed closed-loop control algorithm is constructed; the motor speed closed-loop control algorithm is: ;in, is the motor driving voltage; is the power magnification factor; Dynamic correction of the proportional coefficient; is the speed error; is the integration coefficient; is the differential coefficient.

5. The method for optimizing control of boom amplitude and telescopic speed of an off-road forklift according to claim 4, characterized in that: Based on the neural network inverse model and the optimal speed command, the solenoid valve opening command corresponding to the off-road forklift with the corresponding attachment type is obtained; The process of controlling the speed of the boom of an off-road forklift truck with a corresponding attachment type according to the motor drive voltage and the solenoid valve opening instruction includes: Based on the neural network inverse model and according to the optimal speed instruction , construct a solenoid valve decoupling control model: the solenoid valve decoupling control model is: ;in, 、 is the solenoid valve opening instruction; is the amplitude variation speed; is the telescopic speed; is the inverse model obtained by neural network training.

6. An off-road forklift boom luffing and telescopic speed optimization control system, which implements the off-road forklift boom luffing and telescopic speed optimization control method according to claim 1, characterized in that: include: Forklift data acquisition module, attachment identification module, load torque calculation module, force limit control module, main control module and execution control module; The attachment recognition module is used to formulate an attachment adaptive recognition strategy, including: establishing an attachment feature database through the hard-wired signal of the off-road forklift, the attachment feature database includes: attachments , attachment type name, attachment initial lever arm length and safety threshold; According to the accessory feature database, an accessory adaptive recognition strategy is formulated, and the accessory adaptive recognition strategy is: ;in, It is a database of attribute characteristics; For accessories ; According to the attachment adaptive recognition strategy, select the corresponding attachment type; A forklift data acquisition module is used to collect working posture data of the boom of an off-road forklift with a corresponding attachment type and pressure data of the off-road forklift's oil cylinder, including: according to the pull wire sensor, angle sensor, and pressure sensor provided in the off-road forklift, and setting an acquisition cycle, respectively collecting boom telescopic displacement, boom amplitude angle, and pressure data of the off-road forklift boom with a corresponding attachment type according to the acquisition cycle; the boom telescopic displacement and boom amplitude angle are uniformly recorded as the working posture; The load moment calculation module constructs a load moment dynamic solution algorithm based on the working posture, pressure data and attachment type. According to the load moment dynamic solution algorithm, the real-time load moment of the off-road forklift boom is obtained, including: recording the collected boom telescopic displacement, boom amplitude angle and pressure data as 、 as well as ; According to the telescopic displacement of the boom , boom luffing angle , pressure data and attachment types , construct a load moment dynamic solution algorithm; the load moment dynamic solution algorithm is: ;in, is the real-time load torque; is the real-time cross-sectional area of ​​the rough terrain forklift cylinder; is the efficiency coefficient of the hydraulic system, which is obtained by relevant technical personnel looking up the table; is the lever arm function of the off-road forklift; the lever arm function for: ;in, For the corresponding attachment type The initial lever arm length; The force limit control module constructs a safety boundary constraint condition based on the real-time load torque; and obtains a safety constraint speed instruction for the off-road forklift boom based on the safety boundary constraint condition; The main control module builds a multi-objective optimization control algorithm based on the safety constraint speed command and the attachment type to obtain the optimal speed command for the off-road forklift boom; The execution control module constructs a motor speed closed-loop control algorithm based on an adaptive anti-interference algorithm and according to an optimal speed instruction, thereby obtaining the motor drive voltage of the off-road forklift; obtains the solenoid valve opening instruction of the off-road forklift based on an inverse neural network model and according to the optimal speed instruction; and controls the speed of the off-road forklift boom according to the motor drive voltage and the solenoid valve opening instruction.

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