Balanced and steady control method and system based on sensor

Abstract

The invention discloses a sensor-based equilibrium and stability control method and system, and relates to the technical field of control, and the method comprises the steps: obtaining data through a sensor; a PID control algorithm is adopted, and an execution mechanism is adjusted according to the attitude and acceleration information; according to a movement control algorithm, the movement distance is calculated through feedback data, and an instruction is sent to an execution mechanism; and controlling the execution mechanism according to the output of the movement control algorithm. Through a multi-sensor fusion technology and an optimized control algorithm, balanced and stable control, an anti-shake function, target object distance measurement and movement control, and system integration and optimization of the system are realized, the balance and stability of the system in dynamic motion are effectively improved, the influence of vibration and shake on precision is reduced, and the stability of the system is improved. The control precision in the interaction process with the target object is ensured, and the real-time performance and the response speed of the system are optimized, so that the safety, the reliability and the adaptability of the system are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of control technology, and in particular to a sensor-based balanced and stable control method and system. Background Art

[0002] In the prior art, the posture and acceleration are accurately collected and measured, and information between the measurement system and the target object is obtained, and detailed calculations are performed. In the anti-shake function, a closed-loop control algorithm is used to adjust the actuator, and a corresponding mobile control algorithm is designed according to the feedback information. By analyzing the feedback data of the distance sensor, the required moving distance is calculated, and the instruction is sent to the actuator to accurately control the actuator. However, the system's balance adjustment, anti-shake, close object scanning and moving distance control are still imperfect and have the above-mentioned shortcomings. Summary of the invention

[0003] In view of the above-mentioned problems, the present invention is proposed.

[0004] Therefore, the technical problem solved by the present invention is: the present invention proposes a sensor-based balanced and stable control method to address the deficiencies of existing control systems in real-time processing of multi-sensor fusion data, precise control of actuators, and optimization of system stability. This method solves the problem that the system cannot be balanced and run stably in real time due to the inability to efficiently fuse attitude, acceleration, and distance data, the slow response speed of the control algorithm, and the low adjustment accuracy of the actuator. By fusing the data collected by the inertial measurement unit, proximity sensor, and depth sensor, and combining the PID control algorithm with the mobile control algorithm, the response speed and control accuracy of the actuator are effectively improved, ensuring the dynamic balance and stability of the system.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: a sensor-based balanced stable control method, which comprises the following steps:

[0006] Acquire data through sensors; use PID control algorithm to adjust the actuator according to posture and acceleration information; calculate the moving distance through feedback data according to the mobile control algorithm, and send instructions to the actuator; control the actuator according to the output of the mobile control algorithm.

[0007] As a preferred solution of the sensor-based balanced and stable control method described in the present invention, the sensor includes an inertial measurement unit, a proximity sensor and a depth sensor.

[0008] The data includes posture data, acceleration data and distance data.

[0009] As a preferred solution of the sensor-based balanced and stable control method described in the present invention, the inertial measurement unit is used to measure posture data and acceleration data.

[0010] The proximity sensor and the depth sensor are used to measure the distance between the system and the target object.

[0011] As a preferred solution of the sensor-based balanced stable control method described in the present invention, the PID control algorithm is expressed as:

[0012] output = k p *error+k i *integral(error)+k d *derivative(error)

[0013] Among them, output represents the output of the controller, k p , k i and k d are the proportional, integral and differential coefficients respectively, error represents the gap between the expected and actual values, integral(error) represents the accumulation of errors, and derivative(error) represents the rate of change of errors.

[0014] As a preferred solution of the sensor-based balanced stable control method described in the present invention, the mobile control algorithm is expressed as:

[0015] desired_distance=target_distance

[0016] error=desired_distance-current_distance

[0017] output=K*error

[0018] Where desired_distance represents the desired target distance, current_distance is the current measured distance, and K is the control gain.

[0019] As a preferred solution of the sensor-based balanced and stable control method described in the present invention, the instructions include motor control instructions and valve control instructions.

[0020] The motor control instruction is used for the speed, torque or position information of the motor, and is used to control the movement of the actuator.

[0021] The valve control instruction is used for the valve opening or flow information, and is used to control the hydraulic system of the actuator.

[0022] Another object of the present invention is to provide a sensor-based balanced and stable control system, which can integrate the data collection of inertial measurement units, proximity sensors and depth sensors, and combine PID control algorithms and mobile control algorithms to adjust the movement of actuators in real time, thereby achieving accurate dynamic balance and stable control of the system. The system solves the shortcomings of existing control systems in terms of multi-sensor data fusion, actuator control accuracy and response speed, and fills the gap in the existing technology that is difficult to achieve efficient and stable control in complex environments.

[0023] In order to solve the above technical problems, the present invention provides the following technical solutions: a sensor-based balanced and stable control system, including an integration module, a data acquisition module, a control algorithm module, a distance measurement module and an actuator module.

[0024] As a preferred solution of the sensor-based balanced and stable control system described in the present invention, the data acquisition module is connected with the control algorithm module, the distance measurement module, and the integration module, and is used to measure the posture and acceleration information, and the distance between the measurement system and the target object.

[0025] The control algorithm module is connected with the data acquisition module, the actuator module and the integration module, and is used to adjust the actuator according to the information of the data acquisition module and adopt the PID algorithm.

[0026] The distance measurement module is connected with the data acquisition module and the actuator module, and is used for calculating and analyzing the specific movement control according to the information of the data acquisition module.

[0027] The actuator module is connected with the control algorithm module, the distance measurement module and the integration module, and is used for executing the calculation and adjustment output of the control algorithm module and the distance measurement module.

[0028] The integrated module is connected with the data acquisition module, the control algorithm module and the actuator module, and is used for optimizing the sensor data acquisition frequency, the real-time performance of the control algorithm and the response speed of the actuator.

[0029] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned sensor-based balanced and stable control method when executing the computer program.

[0030] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the sensor-based balanced and stable control method as described above.

[0031] The beneficial effects of the present invention are as follows: balanced and smooth control is achieved by using sensors to measure posture and acceleration information, and adjusting the actuator according to the PID control algorithm, thereby achieving balanced and smooth control of the system, ensuring that the system maintains balance and stability during movement, and improving the safety and reliability of the system.

[0032] The anti-shake function uses the attitude and acceleration information measured by the sensor to adjust the actuator through the PID control algorithm, thereby reducing the vibration and jitter of the system. This helps to improve the accuracy and stability of the system, which is particularly important in applications that require precise control.

[0033] Target object distance measurement and movement control use proximity sensors or depth sensors to measure the distance between the target object and the system, and control the proximity and movement of the target object based on the movement control algorithm of the feedback information. It is suitable for various application scenarios that require interaction with the target object.

[0034] System integration and optimization integrates the data acquisition module, control algorithm module and actuator module, and performs system-level optimization, including optimization of sensor data acquisition frequency, real-time control algorithm and actuator response speed. This helps to improve the overall performance and stability of the system, so that the system can better adapt to different working environments and application requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0036] Figure 1 An overall flow chart of a sensor-based balanced and stable control method provided for the first embodiment of the present invention.

[0037] Figure 2 An overall framework diagram of a sensor-based balanced and stable control system provided for the second embodiment of the present invention. DETAILED DESCRIPTION

[0038] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0039] Example 1, reference Figure 1 , is an embodiment of the present invention, and provides a sensor-based balanced and stable control method, characterized in that:

[0040] S1: Get data through sensors.

[0041] Sensors include an inertial measurement unit, a proximity sensor, and a depth sensor.

[0042] The data includes attitude data, acceleration data and distance data.

[0043] The inertial measurement unit is used to measure attitude data and acceleration data.

[0044] Proximity sensors and depth sensors are used to measure the distance between the system and the target object.

[0045] The specific data acquisition formula is as follows:

[0046] Attitude data: attitude = IMU.getAttitude()

[0047] Acceleration data (acceleration): acceleration = IMU.getAcceleration()

[0048] Distance data (distance): distance = min (ProximitySensor.getDistance(), DepthSensor.getDistance())

[0049] Among them, attitude: attitude data, which represents the attitude information of the system, including pitch angle, roll angle and yaw angle.

[0050] acceleration: acceleration data, which represents the acceleration information of the system, that is, the acceleration value of the system in each direction.

[0051] distance: distance data, indicating the distance between the system and the target object.

[0052] In addition, IMU, ProximitySensor, and DepthSensor are the names or objects of sensors, and getAttitude(), getAcceleration(), and getDistance() are methods of the corresponding sensor objects, which are used to obtain attitude, acceleration, and distance data.

[0053] By calling these methods, the actual attitude data, acceleration data, and distance data are obtained, and then assigned to the corresponding variables (attitude, acceleration, and distance) for use.

[0054] S2: Use PID control algorithm to adjust the actuator according to the attitude and acceleration information;

[0055] The balance control and anti-shake functions use the PID control algorithm in the closed-loop control algorithm to adjust the actuator according to the attitude and acceleration information measured by the sensor. The PID control algorithm is expressed as:

[0056] output = k p *error+k i *integral(error)+k d *derivative(error)

[0057] Among them, output represents the output of the controller, k p , k i and k d are the proportional, integral and differential coefficients respectively, error represents the gap between the expected and actual values, integral(error) represents the accumulation of errors, and derivative(error) represents the rate of change of errors.

[0058] Furthermore, this calculation formula is applied in the design of the balance control algorithm (S2) and the target object distance measurement and movement control algorithm (S3). In the balance control algorithm, the error is calculated according to the posture and acceleration information measured by the sensor and the output is obtained through the PID control algorithm to adjust the actuator. In the target object distance measurement and movement control algorithm, the error is calculated according to the target distance and the current measured distance, and the output is obtained through the PID control algorithm, and the instruction is sent to the actuator to achieve precise movement control.

[0059] It is also used in System Integration and Optimization (S5) to optimize controller parameters, such as adjusting the values ​​of Kp, Ki, and Kd.

[0060] Furthermore, in step S2, the actuator is adjusted according to the attitude and acceleration information measured by the sensor, and preset data is added. Specifically, the following adjustments are made:

[0061] First, obtain the attitude data (attitude) and acceleration data (acceleration) measured by the sensor.

[0062] Calculate the attitude error (attitude_error) and acceleration error (acceleration_error). The attitude error is calculated by the difference between the expected attitude value and the actual attitude value, while the acceleration error is calculated by the difference between the expected acceleration value and the actual acceleration value.

[0063] According to the PID control algorithm, the proportional term (k p *attitude_error), integral term (k i *integral(attitude_error)) and the differential term(k d *derivative(attitude_error)) to calculate the output value (output).

[0064] Among them, k p , k i and k d is the pre-set control gain.

[0065] The output value is applied to the actuator to adjust it. If it is a motor-driven mechanical system, the balance control and anti-shake function are achieved by adjusting the motor speed or torque.

[0066] Among them, the following preset data is used for adjustment:

[0067] Attitude data: attitude = 45°

[0068] Acceleration data: acceleration = 2m / s^2

[0069] Based on these preset data, make the following adjustments:

[0070] Calculate attitude error (attitude_error) and acceleration error (acceleration_error):

[0071] Attitude error (attitude_error) = expected attitude value - actual attitude value = 0° - 45° = -45°

[0072] Acceleration error (acceleration_error) = expected acceleration value - actual acceleration value = 0m / s^2 - 2m / s^2 = -2m / s^2

[0073] According to the PID control algorithm, the output value is calculated:

[0074] output = k p*attitude_error+k i *integral(attitude_error)+k d *derivative

[0075] (attitude_error) (The specific calculation of integral and differential terms is omitted here)

[0076] The calculated output value is applied to the actuator to adjust it.

[0077] S3: According to the movement control algorithm, the movement distance is calculated through feedback data, and the instruction is sent to the actuator.

[0078] The mobility control algorithm is expressed as,

[0079] desired_distance=target_distance

[0080] error=desired_distance-current_distance

[0081] output=K*error

[0082] Where desired_distance represents the desired target distance, current_distance is the current measured distance, and K is the control gain.

[0083] Furthermore, in step S3, the required moving distance is calculated by analyzing the feedback data of the distance sensor, and a command is sent to the actuator. The specific calculation and command sending steps are as follows:

[0084] Get the distance data (distance) between the target object and the system.

[0085] Determine the desired target distance (desired_distance), which is the distance the system wants to maintain from the target object.

[0086] Calculate the error: error = desired_distance - distance. This error represents the difference between the desired distance and the actual measured distance.

[0087] Select the adjustment range according to the control gain (K) and calculate the output value (output): output = K*error.

[0088] The calculated output value is converted into an instruction or control signal and sent to the actuator.

[0089] The instructions include motor control instructions and valve control instructions.

[0090] Motor control instructions are used for the speed, torque or position information of the motor to control the movement of the actuator.

[0091] Valve control instructions are used for valve opening or flow information to control the hydraulic system of the actuator.

[0092] Further, motor control instructions: the speed, torque or position information of the motor is used to control the movement of the actuator.

[0093] Valve control command: Valve opening or flow information, used to control the hydraulic system of the actuator.

[0094] Sending method:

[0095] Digital signal transmission: Send binary data through the digital interface (GPIO) to represent the command content, such as using PWM signals to adjust the motor speed or using digital pulse signals to control the valve opening.

[0096] Analog signal transmission: Send a continuously changing signal through an analog interface (DAC) to represent the command content, such as using a voltage signal to control the motor speed or valve opening.

[0097] Communication protocol sending: Use serial communication protocols (UART, SPI, I2C) or network communication protocols (such as TCP / IP, CAN) to send instruction content, and use these protocols to transmit numerical values, commands and parameter information.

[0098] Bus control transmission: Use a specific bus protocol (CAN bus, EtherCAT) to communicate and control multiple devices, and send command content through the bus.

[0099] S4: Control the actuator according to the output of the movement control algorithm.

[0100] According to the output of the control algorithm, the actuator is precisely controlled to achieve the system's balance adjustment, anti-shake, close object scanning and moving distance control functions.

[0101] Example 2, reference Figure 2 , which is an embodiment of the present invention, provides a system for a sensor-based balanced and stable control method, characterized in that it includes an integration module 100, a data acquisition module 200, a control algorithm module 300, a distance measurement module 400 and an actuator module 500.

[0102] The data acquisition module 200 is connected with the control algorithm module 300, the distance measurement module 400 and the integration module 100, and is used to measure the posture and acceleration information, and the distance between the measurement system and the target object.

[0103] The control algorithm module 300 is connected to the data acquisition module 200, the actuator module 500, and the integration module 100, and is used to adjust the actuator using the PID algorithm according to the information of the data acquisition module 200;

[0104] The distance measurement module 400 is connected to the data acquisition module 200 and the actuator module 500 , and is used to perform calculation and analysis on specific movement control according to the information of the data acquisition module 200 .

[0105] The actuator module 500 is connected to the control algorithm module 300 , the distance measurement module 400 , and the integration module 100 , and is used to execute the calculation and adjustment output of the control algorithm module 300 and the distance measurement module 400 .

[0106] The integrated module 100 is connected with the data acquisition module 200, the control algorithm module 300 and the actuator module 500, and is used for optimizing the sensor data acquisition frequency, the real-time performance of the control algorithm and the response speed of the actuator.

[0107] Furthermore, the data acquisition module, control algorithm module and actuator module are integrated to ensure the coordinated work among various parts and perform system-level optimization, including the optimization of sensor data acquisition frequency, real-time performance of the control algorithm, and response speed of the actuator, so as to improve the overall performance and stability of the system.

[0108] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program code.

[0109] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0110] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0111] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0112] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. 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 solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A sensor-based balanced and stable control method, characterized in that: include: Acquire data through sensors; Adopt PID control algorithm to adjust the actuator according to the attitude and acceleration information; According to the mobile control algorithm, the moving distance is calculated through feedback data, and the command is sent to the actuator; The actuators are controlled according to the output of the motion control algorithm.

2. A sensor-based balanced and stable control method as claimed in claim 1, characterized in that: The sensors include an inertial measurement unit, a proximity sensor, and a depth sensor; The data includes posture data, acceleration data and distance data.

3. A sensor-based balanced and stable control method as claimed in claim 2, characterized in that: The inertial measurement unit is used to measure attitude data and acceleration data; The proximity sensor and the depth sensor are used to measure the distance between the system and the target object.

4. A sensor-based balanced and stable control method as claimed in claim 3, characterized in that: The PID control algorithm is expressed as, output=k p *error+k i *integral(error)+k d *derivative(error) Among them, output represents the output of the controller, k p , k i and k d are the proportional, integral and differential coefficients respectively, error represents the gap between the expected and actual values, integral(error) represents the accumulation of errors, and derivative(error) represents the rate of change of errors.

5. A sensor-based balanced and stable control method as claimed in claim 4, characterized in that: The mobile control algorithm is expressed as, desired_distance=target_distance error=desired_distance-current_distance output=K*error Where desired_distance represents the desired target distance, current_distance is the current measured distance, and K is the control gain.

6. A sensor-based balanced and stable control method as claimed in claim 5, characterized in that: The instructions include motor control instructions and valve control instructions; The motor control instruction is used for the speed, torque or position information of the motor, and is used to control the movement of the actuator; The valve control instruction is used for the valve opening or flow information, and is used to control the hydraulic system of the actuator.

7. A system using a sensor-based balanced and stable control method as claimed in any one of claims 1 to 6, characterized in that: It comprises an integration module (100), a data acquisition module (200), a control algorithm module (300), a distance measurement module (400) and an actuator module (500).

8. A sensor-based balanced and stable control system as claimed in claim 7, characterized in that: The data acquisition module (200) is connected to the control algorithm module (300), the distance measurement module (400), and the integration module (100), and is used to measure posture and acceleration information, and the distance between the measurement system and the target object; The control algorithm module (300) is connected to the data acquisition module (200), the actuator module (500), and the integration module (100), and is used to adjust the actuator using a PID algorithm according to information from the data acquisition module (200); The distance measurement module (400) is connected to the data acquisition module (200) and the actuator module (500) and is used to perform calculation and analysis on specific movement control according to information from the data acquisition module (200); The actuator module (500) is connected to the control algorithm module (300), the distance measurement module (400), and the integration module (100), and is used to execute the calculation and adjustment output of the control algorithm module (300) and the distance measurement module (400); The integrated module (100) is connected to a data acquisition module (200), a control algorithm module (300), and an actuator module (500), and is used to optimize the sensor data acquisition frequency, the real-time performance of the control algorithm, and the response speed of the actuator.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of a sensor-based balanced and stable control method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a sensor-based balancing and stabilizing control method as described in any one of claims 1 to 7 are implemented.

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