Marine robot control method, device, electronic equipment and storage medium

Abstract

The present disclosure provides a marine robot control method, device, electronic device and storage medium, which combines an extended state observer with dynamic linearization theory, and designs a data-driven extended state observer by using a dynamic linearization method to estimate the input gain coefficient that needs to be accurately known in the extended state observer in real time, which can realize the observation of system state information and lumped disturbance when only the system input and output information is used, and the data-driven extended state observer is applied to the marine robot control system. The data-driven extended state observer proposed in the present disclosure realizes the observation of the lumped disturbance of the marine robot and the adaptive estimation of the input gain coefficient of the system, solves the problem that the traditional extended state observer needs to know the system model information, and improves the universality of the marine robot control system.

Description

Technical Field

[0001] The present disclosure relates to the technical field of ship motion control, and in particular to a marine robot control method, device, electronic equipment and storage medium. Background Art

[0002] There are many types of marine robots, such as unmanned boats, wave gliders, underwater robots, etc. For the bow motion control problem of marine robots, most of the control actuators of the bow control process are driven by servos. For this type of bow control problem, there are already many control algorithms, such as classic proportional integral derivative (PID) control, anti-disturbance control, sliding mode control, model-free adaptive control, etc.

[0003] In recent years, with the development of control theory, the extended state observer in the ADRC has become the focus of research. It expands the system state and the lumped disturbance into a new state quantity according to the input and output of the controlled system, and compensates for the disturbance through the feedback mechanism to achieve the effect of anti-disturbance. However, the extended state observer still needs to know the input gain coefficient of the system to better resist disturbance. Therefore, it is of great significance to design a method that can adaptively estimate the input gain coefficient of the system and realize data-driven extended state observer. Summary of the invention

[0004] The present disclosure provides a marine robot control method, device, electronic device and storage medium to at least solve the above technical problems existing in the prior art.

[0005] According to a first aspect of the present disclosure, there is provided a method for controlling a marine robot, comprising:

[0006] Based on the actual status of marine robots , System Input and the estimated system input gain factor , determine the estimated value of the marine robot system state , estimated values ​​of the state derivatives of the marine robot system , and the estimated value of the lumped disturbance of the marine robot system ; Specifically include:

[0007] The actual status of the marine robot , System Input and the estimated system input gain factor Input to the extended state observer and obtain:

[0008]

[0009] in, , , is the coefficient of the extended state observer; are fixed design parameters; is the estimated value of the marine robot system state The derivative of is the estimated value of the state derivative of the marine robot system The derivative of is the estimated value of the total disturbance of the marine robot system The derivative of is the estimated error of the marine robot system state;

[0010] According to the estimated value of the state derivative of the marine robot system , Estimation of the lumped disturbance of the marine robot system , and system input , the system input gain coefficient is adjusted by dynamic linearization algorithm Estimate and obtain the estimated value of the system input gain coefficient ;

[0011] According to the expected state of the marine robot and estimates of the state of the marine robotic system , determine the first state error , the first state error Input to motion controller, get motion controller output ;

[0012] Based on the motion controller output , Estimation of the lumped disturbance of the marine robot system and the estimated system input gain factor , calculate the system input ;

[0013] Enter the system Input to the operation execution device to realize the control of the marine robot.

[0014] In the above scheme, the system is input After the input is sent to the operation execution device to realize the control of the marine robot, the method further includes:

[0015] Get the actual status of the marine robot ;

[0016] Based on the actual status of the marine robot , and the desired state of marine robots determining a second state error of the marine robot;

[0017] In response to the second state error being greater than or equal to a preset threshold, the motion controller outputs , Estimation of the lumped disturbance of the marine robot system and the estimated system input gain factor , determine the system input .

[0018] In the above scheme, the estimated value of the state derivative of the marine robot system is , Estimation of the lumped disturbance of the marine robot system , and system input , the system input gain coefficient is adjusted by dynamic linearization algorithm Estimate and obtain the estimated value of the system input gain coefficient ,include:

[0019] Based on system input , estimated values ​​of the state derivatives of the marine robot system , Estimation of the lumped disturbance of the marine robot system and the system input gain factor , determine the relationship between the system input and output information and the system input gain coefficient:

[0020]

[0021] make , then the relationship between the system input and output information and the system input gain coefficient is: .

[0022] In the above scheme, the estimated value of the state derivative of the marine robot system is , Estimation of the lumped disturbance of the marine robot system , and system input , the system input gain coefficient is adjusted by dynamic linearization algorithm Estimate and obtain the estimated value of the system input gain coefficient ,include:

[0023] Based on the estimation criterion function corresponding to the system input gain coefficient, the system input gain coefficient Find the extreme value and get the estimated value of the system input gain coefficient ;

[0024] The estimation criterion function corresponding to the system input gain coefficient includes:

[0025]

[0026] in, is the weight factor;

[0027] Get the estimated value of the system input gain coefficient include:

[0028]

[0029] Among them, if it satisfies , or One of them, ; is the step size factor, for The initial value of is a sufficiently small positive number.

[0030] In the above scheme, the desired state of the marine robot and estimates of the state of the marine robotic system , determine the first state error , the first state error Input to motion controller, get motion controller output ,include:

[0031] Determine the first state error According to the desired state of the marine robot and estimates of the state of the marine robotic system difference;

[0032] The first state error Input to the motion controller and get:

[0033]

[0034] in, , and are proportional, integral and differential coefficients respectively, is the simulation step length; the motion controller includes one of a PID controller, a sliding mode controller and a fuzzy controller.

[0035] In the above scheme, the motion controller outputs , Estimation of the lumped disturbance of the marine robot system and the estimated system input gain factor , calculate the system input ,include:

[0036] .

[0037] According to a second aspect of the present disclosure, a marine robot control system is provided, the control system comprising a main control computer, a state sensor, an operation execution device and a power supply system; the main control computer comprises a motion controller and a data-driven extended state observer, the data-driven extended state observer comprises an extended state observer; the control system is used for marine robot bow motion control and / or marine robot speed motion control;

[0038] The extended state observer is used to observe the actual state of the marine robot. , System Input and the estimated system input gain factor , determine the estimated value of the marine robot system state , estimated values ​​of the state derivatives of the marine robot system , and the estimated value of the lumped disturbance of the marine robot system ; Specifically used for:

[0039] The actual status of the marine robot , System Input and the estimated system input gain factor Input to the extended state observer and obtain:

[0040]

[0041] in, , , is the coefficient of the extended state observer; are fixed design parameters; is the estimated value of the marine robot system state The derivative of is the estimated value of the state derivative of the marine robot system The derivative of is the estimated value of the total disturbance of the marine robot system The derivative of is the estimated error of the marine robot system state;

[0042] The extended state observer is also used to estimate the state derivative of the marine robot system , Estimation of the lumped disturbance of the marine robot system , and system input , the system input gain coefficient is adjusted by dynamic linearization algorithm Estimate and obtain the estimated value of the system input gain coefficient ;

[0043] The motion controller is used to determine the desired state of the marine robot. and estimates of the state of the marine robotic system , determine the first state error , the first state error Input to motion controller, get motion controller output ;

[0044] The main control computer is used to output , Estimation of the lumped disturbance of the marine robot system and the estimated system input gain factor , calculate the system input ;

[0045] The main control computer is also used to input the system Input to the operation execution device to realize the control of the marine robot.

[0046] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0047] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method described in the present disclosure.

[0048] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause the computer to execute the method described in the present disclosure.

[0049] The marine robot control method disclosed in the present invention is based on the actual state of the marine robot. , System Input and the estimated system input gain factor , determine the estimated value of the marine robot system state , estimated values ​​of the state derivatives of the marine robot system , and the estimated value of the lumped disturbance of the marine robot system ; Based on the estimated value of the state derivative of the marine robot system , Estimation of the lumped disturbance of the marine robot system , and system input , the system input gain coefficient is adjusted by dynamic linearization algorithm Estimate and obtain the estimated value of the system input gain coefficient ; According to the desired state of the marine robot and estimates of the state of the marine robotic system , determine the first state error , the first state error Input to motion controller, get motion controller output Based on the motion controller output , Estimation of the lumped disturbance of the marine robot system and the estimated system input gain factor , calculate the system input ; Input the system The input is sent to the operation execution device to realize the control of the marine robot; in this way, the data driven extended state observer can be combined with the extended state observer to realize effective compensation for external environmental interference, solving the problem that the extended state observer needs a known system input gain coefficient. At the same time, the marine robot control method provided by the embodiment of the present disclosure has comprehensive technical advantages such as strong adaptive ability, simple control method, and easy engineering implementation.

[0050] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The above and other objects, features and advantages of the exemplary embodiments of the present disclosure will become readily understood by reading the detailed description below with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present disclosure are shown in an exemplary and non-limiting manner, in which:

[0052] In the drawings, the same or corresponding reference numerals represent the same or corresponding parts.

[0053] Figure 1 A first optional flow chart of the marine robot control method provided by the embodiment of the present disclosure is shown;

[0054] Figure 2 A data schematic diagram showing a method for controlling a marine robot provided by an embodiment of the present disclosure is shown;

[0055] Figure 3 A second optional flow chart of the marine robot control method provided by the embodiment of the present disclosure is shown;

[0056] Figure 4 A third optional flow chart of the marine robot control method provided by the embodiment of the present disclosure is shown;

[0057] Figure 5 An optional structural schematic diagram of a marine robot control system provided by an embodiment of the present disclosure is shown;

[0058] Figure 6A schematic diagram of the structure of an electronic device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0059] In order to make the purpose, features, and advantages of the present disclosure more obvious and easy to understand, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present disclosure.

[0060] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it can be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0061] In the following description, the terms "first\second" involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second" can be interchanged with a specific order or sequence where permitted, so that the embodiments of the present disclosure described herein can be implemented in an order other than that illustrated or described herein.

[0062] Unless otherwise defined, all technical and scientific terms used in this disclosure have the same meaning as those commonly understood by those skilled in the art to which this disclosure belongs. The terms used in this disclosure are only for the purpose of describing the embodiments of this disclosure and are not intended to limit this disclosure.

[0063] It should be understood that in the various embodiments of the present disclosure, the size of the serial number of each implementation process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.

[0064] In the control of marine robots, the estimation of the system input gain coefficient is crucial; in related technologies, the system input and output data are filtered and stored in a stack, and then the control gain estimate is calculated for all the recorded data; or, matrix calculation and estimation calculation are used to select the control input gain estimate through a time judgment module, and the adaptive extended state observer includes a control input gain calculation module and an adaptive rate of the control input gain estimate to estimate the control input gain; but the former requires a large amount of storage space, and as the control time increases, the computational complexity also increases further; the latter has a large amount of computation and is difficult to apply to actual engineering.

[0065] In response to the defects existing in the related art, the embodiments of the present disclosure provide a marine robot control method, which combines an extended state observer with dynamic linearization theory. By constructing a calculation relationship between the system input and output information and the system input gain coefficient, a dynamic linearization method is used to perform online estimation of the system input gain coefficient that needs to be accurately known in the extended state observer, observe the lumped disturbance of the marine robot and adaptively estimate the system input gain coefficient, realize data-driven extended state observation, and compensate the motion controller output to offset the impact of the lumped disturbance on the marine robot.

[0066] Figure 1 A first optional flow chart of the marine robot control method provided by the embodiment of the present disclosure is shown; Figure 2 A data schematic diagram showing a method for controlling a marine robot according to an embodiment of the present disclosure is shown. Figure 1 and Figure 2 Provide explanation.

[0067] Step S101, based on the actual state of the marine robot, the system input and the estimated value of the system input gain coefficient, determine the estimated value of the marine robot system state, the estimated value of the marine robot system state derivative, and the estimated value of the marine robot system lumped disturbance.

[0068] In some embodiments, a carrier (hereinafter referred to as carrier) implementing the marine robot control method converts the actual state of the marine robot into , System Input and the estimated system input gain factor Input to the extended state observer and obtain:

[0069] (1)

[0070] in, , , is the coefficient of the extended state observer; are fixed design parameters, which are design parameters known to those skilled in the art; Estimated value of the marine robot system state The derivative of is the estimated value of the state derivative of the marine robot system The derivative of is the estimated value of the total disturbance of the marine robot system The derivative of is the estimated error of the marine robot system state; One of the characterization instant, sampling instant, or step size.

[0071] In some embodiments, The initial value is , The initial value is , The initial value is , The initial value is , The initial value is , The initial value is The initial values ​​of each parameter are known, and the actual state of the marine robot can be combined with the initial values ​​of each parameter. And formula (1), the estimated value of the lumped disturbance of the marine robot system is calculated .

[0072] In some embodiments, the carrier can be a computer program, electronic circuit, database, mobile application, electronic device, cloud computing platform, distributed system, artificial intelligence framework, mathematical model, automation tool and microcontroller, etc., which can implement software or hardware of algorithm and method flow.

[0073] Step S102, according to the estimated value of the state derivative of the marine robot system, the estimated value of the lumped disturbance of the marine robot system, and the system input, the system input gain coefficient is estimated by a dynamic linearization algorithm to obtain an estimated value of the system input gain coefficient.

[0074] In some embodiments, the carrier is based on system input , estimated values ​​of the state derivatives of the marine robot system , Estimation of the lumped disturbance of the marine robot system and the system input gain factor , determine the relationship between the system input and output information and the system input gain coefficient:

[0075] (2)

[0076] make , then the relationship between the system input and output information and the system input gain coefficient is: .in, It has no specific physical meaning and is used only to simplify the calculation process. .

[0077] Furthermore, the carrier estimates the system input gain coefficient based on the estimation criterion function corresponding to the system input gain coefficient. Find the extreme value and get the estimated value of the system input gain coefficient .

[0078] In some embodiments, the estimation criterion function corresponding to the system input gain coefficient includes:

[0079] (3)

[0080] in, is the weight factor;

[0081] Get the estimated value of the system input gain coefficient include:

[0082]

[0083] Among them, if it satisfies , or ,but ; is the step size factor, for The initial value of is a sufficiently small positive number.

[0084] Step S103, determining a first state error according to the desired state of the marine robot and the estimated value of the system state of the marine robot, inputting the first state error into the motion controller, and obtaining the output of the motion controller.

[0085] In some embodiments, the first state error The carrier will first state error Input to the motion controller and get:

[0086]

[0087] in, , and are proportional, integral and differential coefficients respectively, is the simulation step length; the motion controller includes one of a PID controller, a sliding mode controller and a fuzzy controller.

[0088] Step S104, calculating the system input based on the motion controller output, the estimated value of the lumped disturbance of the marine robot system and the estimated value of the system input gain coefficient.

[0089] In some embodiments, the determination of the system input includes:

[0090]

[0091] The calculated value in step S101 , calculated in step S102 and the value calculated in step S103 The system input can be determined.

[0092] Step S105, inputting the system input to the operation execution device to realize the control of the marine robot.

[0093] In some embodiments, the control of the marine robot includes marine robot bow motion control and / or marine robot speed motion control.

[0094] Thus, the marine robot control method provided by the embodiment of the present disclosure can be combined with the data-driven extended state observer that can effectively compensate for external environmental interference, thereby solving the problem that the extended state observer requires a known system input gain coefficient. At the same time, the marine robot control method provided by the embodiment of the present disclosure has comprehensive technical advantages such as strong adaptive capability, simple control method, and easy engineering implementation.

[0095] Figure 3 A second optional flow chart of the marine robot control method provided in an embodiment of the present disclosure is shown.

[0096] Step S301, inputting the desired state of the marine robot into the motion controller.

[0097] In some embodiments, the desired state of the marine robot That is, the desired heading angle or speed of the marine robot.

[0098] Step S302: using an extended state observer to calculate an estimated value of the state of the marine robot system.

[0099] In some embodiments, the carrier transmits the actual state of the marine robot , System Input and the estimated system input gain factor Input into the extended state observer to obtain the system state of the marine robot. Specifically, it includes formula (1).

[0100] Wherein, the estimated value of the marine robot system state includes: Estimated value of the marine robot system state The derivative of is the estimated value of the state derivative of the marine robot system The derivative of is the estimated value of the total disturbance of the marine robot system The derivative of is the estimated error of the marine robot system state.

[0101] Step S303: determining the estimated value of the system input gain coefficient according to the estimated value of the system state and the system input.

[0102] In some embodiments, the carrier estimates the value based on the system state , And system input , construct the calculation relationship between the system input and output information and the input gain coefficient of the controlled system in equation (2); let , then formula (2) is .

[0103] The system input gain coefficient is estimated by dynamic linearization method to obtain equation (4).

[0104] Introduce a reset mechanism for the system input gain coefficient: If , or ,but .

[0105] Step S304, determining the output of the motion controller according to the expected state and the estimated value of the system state.

[0106] In some embodiments, the carrier will be the desired state of the marine robot and estimates of the state of the marine robotic system Input to the motion controller to determine the first state error :

[0107]

[0108] Furthermore, the PID control method (Equation (5)) is used based on the first state error Determine the output of the motion controller .

[0109] Step S305 , calculating the system input based on the motion controller output, the estimated value of the lumped disturbance of the marine robot system and the estimated value of the system input gain coefficient.

[0110] In some embodiments, the carrier calculates the system input based on equation (7): .

[0111] In some embodiments, the It is the compensation output by the motion controller and also the input of the operation execution device, which is used to control the marine robot to perform corresponding operations.

[0112] Step S306: Send the system input to the operation execution device through the main control computer to execute the corresponding operation.

[0113] Step S307, determining whether the second state error meets the requirement.

[0114] In some embodiments, the carrier obtains the actual state of the marine robot through a state sensor ; Based on the actual state of the marine robot , and the desired state of marine robots Determine a second state error of the marine robot; in response to the second state error being greater than or equal to a preset threshold, re-based on the motion controller output , Estimation of the lumped disturbance of the marine robot system and the estimated system input gain factor , determine the system input , that is, re-execute steps S302 to S306 until the second state error is less than the preset threshold.

[0115] Thus, the marine robot control method provided by the embodiment of the present disclosure constructs the relationship between the system input-output information and the system input gain coefficient, adopts the dynamic linearization method to realize the adaptive estimation of the input gain coefficient of the extended state observer, and combines the extended state observer to realize the compensation of the lumped disturbance suffered by the marine robot motion control system. The problem that the extended state observer needs to know the system input gain coefficient accurately is solved, and the adaptability of the extended state observer is expanded. At the same time, the calculation principle of the method provided by the embodiment of the present disclosure is simple, which is convenient for practical engineering application in the marine robot motion control system.

[0116] Figure 4 A third optional flow chart of the marine robot control method provided in the embodiment of the present disclosure is shown, and will be explained according to each step.

[0117] In some embodiments, the unmanned boat is a common marine robot, and its heading control system is composed of a main control computer, a heading sensor, a control actuator, a power supply system, etc. The main control computer calculates the heading control system input of the marine robot from the heading sensor. Then it is sent to the steering gear to perform steering.

[0118] Step S401, inputting the desired heading angle of the marine robot into a heading controller.

[0119] Step S402: using an extended state observer to calculate an estimated value of the heading angle of the marine robot system.

[0120] In some embodiments, the carrier converts the actual heading angle of the marine robot into , System Input and the estimated system input gain factor Input to the extended state observer to obtain the system state of the marine robot. Specifically include:

[0121] (8)

[0122] In this embodiment, is the actual heading angle of the marine robot; , , is the coefficient of the extended state observer; is a fixed design parameter; Estimation of heading angle of marine robotic systems; is the estimated value of the bow angular velocity of the marine robot system; is the estimated value of the lumped disturbance of the marine robot system.

[0123] Step S403: determining a system input gain coefficient estimate value according to the system state estimate value and the system input.

[0124] In some embodiments, the carrier estimates the value based on the system state , And system input , construct the calculation relationship between the system input and output information and the input gain coefficient of the controlled system in equation (2); let , then formula (2) is .

[0125] The system input gain coefficient is estimated by dynamic linearization method to obtain equation (4).

[0126] Introduce a reset mechanism for the system input gain coefficient: If , or ,but .

[0127] Step S404: determining the output of the heading controller according to the expected heading angle and the estimated value of the system heading angle.

[0128] In some embodiments, the carrier sets the desired heading angle of the marine robot and the estimated heading angle of the marine robotic system Input to the heading controller to determine the first state error :

[0129]

[0130] Furthermore, the PID control method is adopted, based on the first state error Determine the output of the heading controller :

[0131]

[0132] Wherein, step S403 and step S404 are implemented by a data-driven extended state observer; the data-driven extended state observer includes an extended state observer for implementing step S404; and a module for implementing a dynamic linearization method for implementing step S405.

[0133] Step S405, calculating the system input based on the bow controller output, the estimated value of the lumped disturbance of the marine robot system and the estimated value of the system input gain coefficient.

[0134] In some embodiments, the carrier calculates the system input based on equation (7): .

[0135] In some embodiments, the It is the compensation output of the bow controller and also the input of the operation execution device, which is used to control the marine robot to perform corresponding operations.

[0136] Step S406, sending the system input to the steering gear through the main control computer to perform corresponding operations.

[0137] Step S407, determining whether the first heading error meets the requirement.

[0138] In some embodiments, the carrier obtains the actual heading angle of the marine robot through a state sensor. ; Based on the actual heading angle of the marine robot , and the desired heading angle of the marine robot Determine a first heading error of the marine robot; in response to the first heading error being greater than or equal to a preset threshold, re-based on the heading controller output , Estimation of the lumped disturbance of the marine robot system and the estimated system input gain factor , determine the system input , that is, re-execute step S402 to step S406 until the first heading error is less than the preset threshold.

[0139] In this way, the disclosed embodiment combines the extended state observer with the dynamic linearization theory, and designs a data-driven extended state observer by using the dynamic linearization method to estimate the input gain coefficient that needs to be accurately known in the extended state observer in real time. The system state information and lumped disturbance observation can be realized when only the system input and output information is used, and the data-driven extended state observer is applied to the marine robot control system. The data-driven extended state observer proposed in the disclosed embodiment realizes the observation of the lumped disturbance of the marine robot and the adaptive estimation of the input gain coefficient of the system, solves the problem that the traditional extended state observer needs to know the system model information, and improves the universality of the marine robot control system.

[0140] Figure 5 An optional structural schematic diagram of the marine robot control system provided by an embodiment of the present disclosure is shown, and will be explained according to each part.

[0141] In some embodiments, a marine robot control system 500 is characterized in that the control system includes a main control computer 501, a state sensor 502, an operation execution device 503 and a power supply system 504; the main control computer 501 includes a motion controller 5011 and a data-driven extended state observer 5012, and the data-driven extended state observer 5012 includes an extended state observer 50121 and a module 50122 for implementing a dynamic linearization method; the marine robot control system 500 is used for marine robot bow motion control and / or marine robot speed motion control; the motion controller 5011 includes existing controllers such as PID controller, sliding mode controller, fuzzy controller, etc.

[0142] In some embodiments, the motion controller 5011 in the main control computer 501 calculates the controller output The system input of the marine robot motion control is obtained by compensating the lumped disturbance obtained by the data-driven extended state observer 5012. , and sends it to the operation execution device 503 to execute the corresponding operation, the state sensor 502 collects the state information of the marine robot in real time and sends it to the main control computer 501 for calculation, specifically:

[0143] The extended state observer 50121 is used to observe the actual state of the marine robot. , System Input and the estimated system input gain factor , determine the estimated value of the marine robot system state , Marine Robot System Status Estimate of the derivative , and the estimated value of the lumped disturbance of the marine robot system ;

[0144] The extended state observer 50121 is also used to estimate the state derivative of the marine robot system , Estimation of the lumped disturbance of the marine robot system , and system input , the system input gain coefficient is adjusted by dynamic linearization algorithm Estimate and obtain the estimated value of the system input gain coefficient ;

[0145] The motion controller 5011 is used to control the desired state of the marine robot. and estimates of the state of the marine robotic system , determine the first state error , based on the first state error , get the output of motion controller 5011 ;

[0146] The main control computer 501 is used to output based on the motion controller 5011 , Estimation of the lumped disturbance of the marine robot system and the estimated system input gain factor , calculate the system input ;

[0147] The main control computer 501 is also used to input the system The information is input to the operation execution device 503 to realize the control of the marine robot.

[0148] In some embodiments, when the system is input After the input is sent to the operation execution device to realize the control of the marine robot, the state sensor 502 is used to obtain the actual state of the marine robot. ; Based on the actual state of the marine robot , and the desired state of marine robots determining a second state error of the marine robot;

[0149] In response to the second state error being greater than or equal to a preset threshold, the marine robot control system 500 re-outputs the motion controller 5011 based on the , Estimation of the lumped disturbance of the marine robot system and the estimated system input gain factor , determine the system input .

[0150] The extended state observer 50121 is specifically used for:

[0151] The actual status of the marine robot , System Input and the estimated system input gain factor Input to the extended state observer and obtain:

[0152]

[0153] in, , , is the coefficient of the extended state observer; are fixed design parameters; Marine robot system status The derivative of Marine robot system status Estimate of the derivative The derivative of is the estimated value of the total disturbance of the marine robot system The derivative of is the estimated error of the marine robot system state.

[0154] The motion controller 5011 is specifically used to: , estimated values ​​of the state derivatives of the marine robot system , Estimation of the lumped disturbance of the marine robot system and the system input gain factor , determine the relationship between the system input and output information and the system input gain coefficient:

[0155]

[0156] make , then the relationship between the system input and output information and the system input gain coefficient is: .

[0157] The motion controller 5011 is specifically used to: based on the estimation criterion function corresponding to the system input gain coefficient, Find the extreme value and get the estimated value of the system input gain coefficient ;

[0158] The estimation criterion function corresponding to the system input gain coefficient includes:

[0159]

[0160] in, is the weight factor;

[0161] Get the estimated value of the system input gain coefficient include:

[0162]

[0163] Among them, if it satisfies , or ,but ; is the step size factor, for The initial value of is a sufficiently small positive number.

[0164] The motion controller 5011 is specifically used to: determine the first state error According to the desired state of the marine robot and estimates of the state of the marine robotic system difference;

[0165] The first state error Input to the motion controller 5011 and get:

[0166]

[0167] in, , and are proportional, integral and differential coefficients respectively, is the simulation step length; the motion controller 5011 includes one of a PID controller, a sliding mode controller and a fuzzy controller.

[0168] The main control computer 501 is specifically used to output the motion controller 5011 , Estimation of the lumped disturbance of the marine robot system and the estimated system input gain factor , calculate the system input ,include: .

[0169] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device and a readable storage medium.

[0170] Figure 6 A schematic block diagram of an example electronic device 800 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0171] like Figure 6As shown, the electronic device 800 includes a computing unit 801, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 to a random access memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the electronic device 800 can also be stored. The computing unit 801, the ROM 802, and the RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0172] Multiple components in the electronic device 800 are connected to the I / O interface 805, including: an input unit 806, such as a keyboard, a mouse, etc.; an output unit 807, such as various types of displays, speakers, etc.; a storage unit 808, such as a disk, an optical disk, etc.; and a communication unit 809, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 809 allows the electronic device 800 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0173] The computing unit 801 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 801 performs the various methods and processes described above, such as the marine robot control method. For example, in some embodiments, the marine robot control method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 808. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 800 via the ROM 802 and / or the communication unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the marine robot control method described above may be performed. Alternatively, in other embodiments, the computing unit 801 may be configured to perform the marine robot control method in any other appropriate manner (e.g., by means of firmware).

[0174] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0175] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0176] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0177] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0178] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0179] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0180] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0181] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of the present disclosure, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0182] The above is only a specific embodiment of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present disclosure, which should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A method for controlling a marine robot, characterized in that: The method comprises: Based on the actual status of marine robots , System Input and the estimated system input gain factor , determine the estimated value of the marine robot system state , estimated values ​​of the state derivatives of the marine robot system , and the estimated value of the lumped disturbance of the marine robot system ; Specifically include: The actual status of the marine robot , System Input and the estimated system input gain factor Input to the extended state observer and obtain: in, , , is the coefficient of the extended state observer; are fixed design parameters; is the estimated value of the marine robot system state The derivative of is the estimated value of the state derivative of the marine robot system The derivative of is the estimated value of the total disturbance of the marine robot system The derivative of is the estimated error of the marine robot system state; According to the estimated value of the state derivative of the marine robot system , Estimation of the lumped disturbance of the marine robot system , and system input , the system input gain coefficient is adjusted by dynamic linearization algorithm Estimate and obtain the estimated value of the system input gain coefficient , including: Based on system input , estimated values ​​of the state derivatives of the marine robot system , Estimation of the lumped disturbance of the marine robot system and the system input gain factor , determine the relationship between the system input and output information and the system input gain coefficient: make , then the relationship between the system input and output information and the system input gain coefficient is: ; Based on the estimation criterion function corresponding to the system input gain coefficient, the system input gain coefficient Find the extreme value and get the estimated value of the system input gain coefficient ; The estimation criterion function corresponding to the system input gain coefficient includes: in, is the weight factor; Get the estimated value of the system input gain coefficient include: Among them, if it satisfies , or One of them, ; is the step size factor, for The initial value of is a sufficiently small positive number; According to the expected state of the marine robot and estimates of the state of the marine robotic system , determine the first state error , the first state error Input to motion controller, get motion controller output ; Based on the motion controller output , Estimation of the lumped disturbance of the marine robot system and the estimated system input gain factor , calculate the system input ; Enter the system Input to the operation execution device to realize the control of the marine robot.

2. The method according to claim 1, characterized in that The system is input After the input is sent to the operation execution device to realize the control of the marine robot, the method further includes: Get the actual status of the marine robot ; Based on the actual status of the marine robot , and the desired state of marine robots determining a second state error of the marine robot; In response to the second state error being greater than or equal to a preset threshold, the motion controller outputs , Estimation of the lumped disturbance of the marine robot system and the estimated system input gain factor , determine the system input .

3. The method according to claim 1, characterized in that: The desired state of the marine robot and estimates of the state of the marine robotic system , determine the first state error , the first state error Input to motion controller, get motion controller output ,include: Determine the first state error According to the desired state of the marine robot and estimates of the state of the marine robotic system difference; The first state error Input to the motion controller and get: in, , and are proportional, integral and differential coefficients respectively, is the simulation step length; the motion controller includes one of a PID controller, a sliding mode controller and a fuzzy controller.

4. The method according to claim 1, characterized in that The motion controller output , Estimation of the lumped disturbance of the marine robot system and the estimated system input gain factor , calculate the system input ,include: 。 5. A marine robot control system, characterized in that: The control system includes a main control computer, a state sensor, an operation execution device and a power supply system; the main control computer includes a motion controller and a data-driven extended state observer, and the data-driven extended state observer includes an extended state observer; the control system is used for the bow motion control of the marine robot and / or the speed motion control of the marine robot; The extended state observer is used to observe the actual state of the marine robot. , System Input and the estimated system input gain factor , determine the estimated value of the marine robot system state , estimated values ​​of the state derivatives of the marine robot system , and the estimated value of the lumped disturbance of the marine robot system ; Specifically used for: The actual status of the marine robot , System Input and the estimated system input gain factor Input to the extended state observer and obtain: in, , , is the coefficient of the extended state observer; are fixed design parameters; is the estimated value of the marine robot system state The derivative of is the estimated value of the state derivative of the marine robot system The derivative of is the estimated value of the total disturbance of the marine robot system The derivative of is the estimated error of the marine robot system state; The extended state observer is also used to estimate the state derivative of the marine robot system , Estimation of the lumped disturbance of the marine robot system , and system input , the system input gain coefficient is adjusted by dynamic linearization algorithm Estimate and obtain the estimated value of the system input gain coefficient , specifically used for: Based on system input , estimated values ​​of the state derivatives of the marine robot system , Estimation of the lumped disturbance of the marine robot system and the system input gain factor , determine the relationship between the system input and output information and the system input gain coefficient: make , then the relationship between the system input and output information and the system input gain coefficient is: ; Based on the estimation criterion function corresponding to the system input gain coefficient, the system input gain coefficient Find the extreme value and get the estimated value of the system input gain coefficient ; The estimation criterion function corresponding to the system input gain coefficient includes: in, is the weight factor; Get the estimated value of the system input gain coefficient include: Among them, if it satisfies , or One of them ; is the step size factor, for The initial value of is a sufficiently small positive number; The motion controller is used to determine the desired state of the marine robot. and estimates of the state of the marine robotic system , determine the first state error , the first state error Input to motion controller, get motion controller output ; The main control computer is used to output , Estimation of the lumped disturbance of the marine robot system and the estimated system input gain factor , calculate the system input ; The main control computer is also used to input the system Input to the operation execution device to realize the control of the marine robot.

6. The system according to claim 5, characterized in that The device also includes a state sensor; The state sensor, when inputting the system Input to the operation execution device to realize the control of the marine robot and then obtain the actual status of the marine robot ; Based on the actual status of the marine robot , and the desired state of marine robots determining a second state error of the marine robot; In response to the second state error being greater than or equal to a preset threshold, the marine robot control system re-actuates based on the motion controller output , Estimation of the lumped disturbance of the marine robot system and the estimated system input gain factor , determine the system input .

7. An electronic device, characterized in that: include: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1 to 4.

8. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to make a computer execute the method according to any one of claims 1-4.

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