High-efficiency and quick-response control method for brushless non-inductive direct current motor

Abstract

The invention discloses a high-efficiency and fast-response control method for a brushless non-inductive direct current motor, and the method employs a non-inductive vector control system which combines an improved rotating speed loop active-disturbance-rejection controller (ADRC) and an improved sliding-mode observer (SMO) to improve the anti-interference capability of a power system. The vector control of the brushless direct current motor at a high speed is realized by adopting an improved sliding-mode observer (SMO), and meanwhile, an active disturbance rejection controller (ADRC) is adopted by a rotating speed ring; according to the method, high-precision control is maintained, the parameter adjustment process is simplified, the implementation difficulty is reduced, the dependence on a high-precision sensor is reduced, the robustness and the anti-interference capability of the system are improved, and good stability and control precision can be maintained even under the condition that motor parameters change greatly or load fluctuation is large; the problems in the background technology are solved.

Description

Technical Field

[0001] The present invention relates to the field of brushless DC motors, and in particular to a high-efficiency, fast-response control method for brushless sensorless DC motors. Background Art

[0002] With the continuous advancement of drone technology, performance requirements for drone motors are becoming increasingly stringent. Traditional duty cycle control methods are no longer able to meet the demands of high-performance drone motors. Consequently, there is an urgent need for better motor control methods to enhance the operational performance of drone motors. These methods include increasing output torque, reducing torque ripple, and improving speed stability, enabling drone motors to maintain excellent performance even under harsh operating conditions such as high speeds and high loads. Consequently, there is an urgent need to develop superior control algorithms for drone motors to meet the diverse performance requirements of the rapidly developing drone industry.

[0003] Currently, drones on the market are generally controlled by electronic speed regulators, which generally use duty cycle control algorithms. The limitations of traditional duty cycle control algorithms are: 1. Insufficient control accuracy: Duty cycle control mainly adjusts the speed and power of the motor by adjusting the duty cycle of the switching device. However, this method cannot achieve precise control of the motor current and torque, resulting in limited motor operating efficiency and stability.

[0004] 2. Slow dynamic response: Duty cycle control responds slowly to dynamic situations such as sudden load changes and cannot adjust the motor's operating status in time, thus affecting the motor's performance and stability.

[0005] 3. Low energy efficiency: Since duty cycle control cannot achieve decoupling control of the motor magnetic field and torque, the energy efficiency of the motor often cannot reach the optimal state.

[0006] In pursuit of better powertrain performance, a small number of developers are currently developing FOC vector control algorithms. However, most of them use traditional FOC control algorithms, which have the following limitations: 1. Algorithm Complexity and Implementation Difficulty: The algorithm itself is complex, requiring precise modeling of the motor mathematical model and complex coordinate transformation and current decoupling control. Implementation requires fine-tuning of multiple parameters, such as PI controller parameters and coordinate transformation parameters, which increases implementation difficulty and debugging time.

[0007] 2. System robustness and stability: The system is sensitive to changes in motor parameters and load disturbances. Significant changes in motor parameters or large load fluctuations can lead to system performance degradation or instability. Regular calibration of sensor and controller parameters is required to ensure system stability and accuracy.

[0008] 3. Control Accuracy and Dynamic Response: Control accuracy is limited by factors such as sensor accuracy, controller performance, and algorithm implementation. In terms of dynamic response, while traditional FOC can achieve relatively fast response speeds, it can experience delays and errors when faced with complex operating conditions and rapid changes. Summary of the Invention

[0009] The object of the present invention is to provide a high-efficiency, fast-response control method for a brushless, sensorless DC motor, which simplifies the parameter adjustment process while maintaining high-precision control, reduces the difficulty of implementation, reduces the dependence on high-precision sensors, and improves the robustness and anti-interference ability of the system. Even when the motor parameters change significantly or the load fluctuates significantly, it can maintain good stability and control accuracy; so as to solve the problems raised in the above-mentioned background technology.

[0010] To achieve the above object, the present invention provides the following technical solutions: A high-efficiency, fast-response control method for a brushless, sensorless DC motor, comprising: A sensorless vector control system combining an improved speed loop active disturbance rejection controller (ADRC) and an improved sliding mode observer (SMO) is used to improve the anti-interference capability of the power system. The improved sliding mode observer (SMO) is used to implement vector control of the brushless DC motor at high speeds, while the speed loop uses an active disturbance rejection controller (ADRC). The entire sensorless vector control system operates as follows: Rotor position and speed estimation: Using the improved sliding mode observer (SMO) algorithm, the system estimates the motor's rotor position and speed based on real-time monitored current and voltage information; Control command generation: Based on the estimated rotor position and speed information and the desired motor operating state, the control algorithm module generates corresponding control commands; these commands are converted into voltage and current signals that the motor can understand through the PWM inverter; Motor drive: The PWM inverter converts control commands into voltage and current signals that the motor can understand, driving the motor to operate. During the motor's operation, the system monitors the motor's operating status in real time and transmits feedback information to the control algorithm module. Closed-loop control: By monitoring the motor's operating status in real time and passing feedback to the speed loop using the Active Disturbance Rejection Controller (ADRC) control algorithm module, the system achieves closed-loop control of the motor. This step ensures that the motor can operate stably according to the desired operating state. Furthermore, the improved sliding mode observer SMO: The mathematical model of the brushless DC motor in a two-phase stationary coordinate system can be expressed as: The constructed sliding mode switching surface is: in To observe the current, is the measured current; Since the traditional sign(x) function is not continuous at zero, which is also an important reason for system chattering, when improving the traditional sliding mode observer, the sign(x) function is improved first. Here, the sigmoid(x) function is used to replace the sign(x) function. The expression of the sigmoid(x) function is: To address the chattering of the sliding mode observer caused by inertia, a reaching law control method is used to reduce the speed of the system as it approaches the sliding surface. When the system reaches the sliding surface at a lower speed than before, the amplitude of the sliding surface will naturally decrease. An exponential reaching law is selected to achieve reaching law control. in and All are adjustable coefficients and are greater than zero. is an exponential approach term, which reduces the approach speed to zero quickly. is the constant speed approaching term, the purpose of which is to shorten the time for the system to reach the sliding surface and speed up the response speed; in order to better reduce the chattering of the sliding mode observer, the sigmoid(x) function and Functions are combined to obtain the reconstructed sliding mode observer: According to the above formula, the expression of back electromotive force is: The improved sliding mode observer is constructed as: The current observation deviation formula of the improved sliding mode observer is: At the same time, the Lyapunov stability theorem is applied to prove the stability of the sliding mode observer, and the following Lyapunov function is constructed. , and meet the conditions: From the above formula, we can see that only when and The stability condition can be met only when both are established, that is: in is the boundary thickness. According to the above formula, The following formula needs to be satisfied to ensure the stability of the improved sliding mode observer: In order to obtain the required motor speed information more accurately, a phase-locked loop algorithm is used to further obtain; Furthermore, the active disturbance rejection controller ADRC: The motor speed state equation: Assume that the state variables of the system are , then the total disturbance of the system can be expressed as: Assume that the input of the system is , then according to the analysis in the previous section, we have , then the state equation of the speed loop can be expressed as: The auto-disturbance rejection controller of the speed loop can be designed as follows: Tracking Differentiator (TD): in is the desired speed of the brushless DC motor, for tracking signal; Nonlinear state error feedback rate (NLSEF): Extended State Observer (ESO): The ESO above can be written in matrix form: Its characteristic equation is: To ensure the stability of the system, we have: ,in is the bandwidth of the observer; the transfer function in ESO can be expressed as: in It is the speed tracking, but the change of current will affect right In order to further improve the observation efficiency of the observer, a proportional gain channel of the observation error is added to the disturbance observation channel; therefore, the above ESO can be improved as follows: in is the differential gain coefficient of the observation error; the closed-loop transfer function in the above observer can be expressed as:

[0011] Compared with the prior art, the present invention has the following beneficial effects: 1. Improve control accuracy and stability Precise Control: SMO-ADRC combines the fast response of a sliding mode observer with the interference rejection capabilities of active disturbance rejection control (ADRC), enabling precise control of the UAV's power motors. The sliding mode observer accurately estimates the motor state in real time, providing reliable information for the controller. ADRC further improves control accuracy by accurately estimating and compensating for various system disturbances in real time.

[0012] Enhanced Stability: The improved SMO-ADRC vector control strategy enhances the stability of the UAV's power motor in complex environments. By optimizing control parameters and algorithms, the system's sensitivity to external disturbances is reduced, improving its robustness.

[0013] 2. Optimize motor performance: Fast Response: The SMO-ADRC vector control strategy is characterized by fast response and can quickly adjust the operating state of the UAV's power motor. This allows the UAV to adapt to environmental changes more quickly during flight, allowing the UAV to adjust its attitude and speed more quickly during flight, improving flight performance and safety.

[0014] Improved energy efficiency: Through precise control and interference compensation, SMO-ADRC can reduce motor energy consumption and improve energy efficiency, thereby extending the flight time of the drone.

[0015] 3. Enhance adaptability and robustness Adaptive Adjustment: Active Disturbance Rejection Control (SMO-ADRC) does not require a precise system model, but instead achieves control through real-time estimation and compensation of disturbances. This feature enables SMO-ADRC to adapt to changes in operating conditions and adaptively adjust control parameters, thereby improving the system's adaptability and robustness.

[0016] Coping with complex environments: UAVs may face various complex environments during flight, such as strong winds and electromagnetic interference. The improved SMO-ADRC vector control can more effectively cope with these challenges and maintain stable operation of the motor. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 Schematic diagram of the improved SMO-ADRC control structure of the brushless DC motor.

[0018] Figure 2 Schematic diagram of the improved sliding mode observer structure.

[0019] Figure 3 To improve the speed tracking response curve under the sliding mode observer.

[0020] Figure 4 This is the speed channel response curve.

[0021] Figure 5 is the torque channel response curve.

[0022] Figure 6 for i a Current channel response curve.

[0023] Figure 7 is the disturbance load torque of the brushless DC motor.

[0024] Figure 8 This is the speed channel response curve under disturbance.

[0025] Figure 9 is the disturbance torque channel response curve.

[0026] Figure 10 Under disturbance ia Current channel response curve. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0028] like Figure 1 As shown, a high-efficiency, fast-response control method for a brushless sensorless DC motor comprises: The sensorless vector control technology combines an improved speed loop active disturbance rejection controller (ADRC) with an improved sliding mode observer (SMO) to improve the anti-interference capability of the power system. Specifically, the improved sliding mode observer (SMO) is used to implement vector control of the brushless DC motor at high speeds. At the same time, the active disturbance rejection controller (ADRC) is used in the speed loop, which improves the dynamic response performance and anti-interference performance of the speed compared to traditional PI control. The entire system operates as follows: S1. Rotor position and speed estimation: Using an improved sliding mode observer (SMO) algorithm, the system estimates the motor's rotor position and speed based on real-time monitored current and voltage information; this step is key to achieving sensorless vector control.

[0029] S2. Control command generation: Based on the estimated rotor position and speed information, as well as the desired motor operating state (such as speed, torque, etc.), the control algorithm module generates corresponding control commands; these commands are converted into voltage and current signals that the motor can understand through the PWM inverter.

[0030] S3. Motor drive: The PWM inverter converts the control instructions into voltage and current signals that the motor can understand, driving the motor to operate. During the motor operation, the system monitors the motor's operating status in real time and passes feedback information to the control algorithm module.

[0031] S4. Closed-loop control: By monitoring the motor's operating status in real time and passing feedback information to the speed loop using the Active Disturbance Rejection Controller (ADRC) control algorithm module, the system achieves closed-loop control of the motor. This step ensures that the motor can operate stably according to the desired operating state.

[0032] Specifically, 1. Improve the design of sliding mode observer (SMO); The sliding mode observer is a common observer in sensorless motor control algorithms. Known for its easy convergence, insensitivity to motor parameters, simple parameter adjustment, and low computational complexity, it has found widespread practical application. The multivariable, nonlinear, and tightly coupled nature of brushless DC motors necessitates an observer with strong interference rejection capabilities to measure the system's internal state variables. Sliding mode variable structure control, with its excellent interference rejection and fast dynamic response, is used as an observer.

[0033] 1.1、Sliding variable structure control principle; Sliding variable structure (sliding mode) control enables the current state quantity in the control system to move in a small amplitude and high frequency according to a certain sliding mode trajectory until it reaches the desired point. It can be designed according to demand so that external disturbances and system parameters will not affect the system. Therefore, this control algorithm generally has the advantages of strong robustness and fast dynamic response speed.

[0034] Assume the control system is: in , control function Need to meet: In the formula are all continuous functions, and , The conditions for the existence of sliding mode are: According to Philipp's theory, we have: When switching function When the switching surface contains a stable equilibrium point of the control function , and the sliding mode motion equation and the switching surface are The sliding mode motion of the system is considered to be stable.

[0035] 1.2. Traditional sliding mode observers are widely used in motor control. However, in actual control, traditional sliding mode observers are prone to cause system chattering. To improve control accuracy, this invention improves the traditional sliding mode observer, thereby effectively suppressing chattering during system operation and improving control accuracy. The mathematical model of a brushless DC motor in a two-phase stationary coordinate system can be expressed as: The constructed sliding mode switching surface is: in To observe the current, is the measured current.

[0036] Because the traditional sign( x) function is not continuous at zero, which is also an important reason for the system chattering. Therefore, when improving the traditional sliding mode observer, we first perform sign( x ) function, here we use sigmoid( x ) function instead of sign( x ) function, sigmoid( x ) The expression of the function is: To address chattering in the sliding mode observer caused by inertia, a reaching law control method is employed to reduce the speed of the system as it approaches the sliding surface. When the system reaches the sliding surface at a lower speed than before, the magnitude of the movement across the sliding surface is naturally reduced. This invention employs an exponential reaching law to achieve reaching law control. in and All are adjustable coefficients and are greater than zero. is an exponential approach term, which reduces the approach speed to zero quickly. is the constant velocity approaching term, which aims to shorten the time for the system to reach the sliding surface and speed up the response. In order to better reduce the chattering of the sliding mode observer, the present invention uses sigmoid ( x ) function and Functions are combined to obtain the reconstructed sliding mode observer: According to the above formula, the expression of back electromotive force is: The improved sliding mode observer is constructed as: The current observation deviation formula of the improved sliding mode observer is: Here we apply the Lyapunov stability theorem to prove the stability of the sliding mode observer and construct the following Lyapunov function , and meet the conditions: From the above formula, we can see that only when and The stability condition can be met only when both are established, that is: in is the boundary thickness. According to the above formula, The following formula needs to be satisfied to ensure the stability of the improved sliding mode observer: In order to obtain the required motor speed information more accurately, a phase-locked loop algorithm can be used to further obtain it.

[0037] According to the algorithm proposed above, the structural diagram of the improved sliding mode observer can be obtained as follows: Figure 2 As shown; Since most aircraft model motors use sensorless control schemes, the improved sliding mode observer can more accurately observe the speed of the motor output, such as Figure 3The figure shows the speed response observed by the improved sliding mode observer. It can be seen from the figure that the designed observer can better follow the speed response curve of the motor's actual speed. Although there are some fluctuations, the overall fluctuation amplitude is small and within an acceptable range.

[0038] 2. Design of Active Disturbance Rejection Controller (ADRC) for Speed Loop When designing a brushless DC motor system controller, speed is a variable that requires real-time control. Depending on the atmospheric environment, it is crucial to ensure that the brushless DC motor system maintains stable operation under static conditions and can quickly adjust with minimal overshoot under dynamic conditions. Therefore, precise control of the motor's speed loop is necessary. Based on the mathematical equations for the brushless DC motor, the motor's speed state equation can be derived: Assume that the state variables of the system are , then the total disturbance of the system can be expressed as: Assume that the input of the system is , then according to the analysis in the previous section, we have , then the state equation of the speed loop can be expressed as: The auto-disturbance rejection controller of the speed loop can be designed as follows: Tracking Differentiator (TD): in is the desired speed of the brushless DC motor, for tracking signal.

[0039] Nonlinear state error feedback rate (NLSEF): Extended State Observer (ESO): The ESO above can be written in matrix form: Its characteristic equation is: To ensure the stability of the system, we have: ,in is the bandwidth of the observer. The transfer function in ESO can be expressed as: in It is the speed tracking, but the change of current will affect right To further improve the observation efficiency of the observer, the present invention adds a proportional gain channel of the observation error to the disturbance observation channel. Therefore, the above ESO can be improved as follows: in is the differential gain coefficient of the observation error. The closed-loop transfer function in the above observer can be expressed as: The designed control algorithm was simulated and analyzed. Figure 4-10The simulation results show that the improved sliding mode observer (SMO) has a better observation effect. Compared with the traditional PI vector control algorithm and the traditional duty cycle control algorithm, the improved SMO-ADRC vector control algorithm has a faster response speed and smaller torque fluctuation, and can reach a stable state in a shorter time. At the same time, in the case of sudden load, the improved SMO-ADRC vector control algorithm can track the reference instruction in a very short time, and can maintain better robustness and stability under external disturbances.

[0040] In the description of the present invention, it should be noted that the terms "upper," "lower," "inner," "outer," "left," "right," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, or are the orientations or positional relationships in which the inventive product is typically placed when in use, or are the orientations or positional relationships commonly understood by those skilled in the art. These terms are intended solely to facilitate the description of the present invention and simplify the description, and are not intended to indicate or imply that the devices or components referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. Furthermore, the terms "first," "second," etc., are used solely to distinguish descriptions and should not be construed as indicating or implying relative importance. In the description of the present invention, it should also be noted that, unless otherwise expressly specified or limited, terms such as "disposed" and "connected" should be understood broadly. For example, "connected" can mean a fixed connection, a detachable connection, or an integral connection; a mechanical connection or an electrical connection; a direct connection, an indirect connection through an intermediate medium, or internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

Claims

1. A high-efficiency, fast-response control method for a brushless, sensorless DC motor, characterized by: A sensorless vector control system combining an improved speed loop active disturbance rejection controller (ADRC) and an improved sliding mode observer (SMO) is used to improve the anti-interference capability of the power system. The improved sliding mode observer (SMO) is used to implement vector control of the brushless DC motor at high speeds, while the speed loop uses an active disturbance rejection controller (ADRC). The entire sensorless vector control system operates as follows: Rotor position and speed estimation: Using the improved sliding mode observer (SMO) algorithm, the system estimates the motor's rotor position and speed based on real-time monitored current and voltage information; Control command generation: Based on the estimated rotor position and speed information and the desired motor operating state, the control algorithm module generates corresponding control commands; these commands are converted into voltage and current signals understood by the motor through the PWM inverter; Motor drive: The PWM inverter converts control commands into voltage and current signals that the motor understands, driving the motor to operate. During motor operation, the system monitors the motor's operating status in real time and transmits feedback information to the control algorithm module. Closed-loop control: By monitoring the motor's operating status in real time and passing feedback to the speed loop using the Active Disturbance Rejection Controller (ADRC) control algorithm module, the system achieves closed-loop control of the motor; this step ensures that the motor can operate stably according to the desired operating state.

2. The high-efficiency, fast-response control method for a brushless sensorless DC motor according to claim 1, characterized in that: The improved sliding mode observer SMO includes: S1, construct the sliding mode switching surface as: S2, sign( x ) function, using sigmoid( x ) function instead of sign( x ) function, sigmoid( x ) The expression of the function is: S3. To address chattering in the sliding mode observer caused by inertia, a reaching law control method is used to reduce the speed of the system as it approaches the sliding surface. When the system reaches the sliding surface at a lower speed than before, the magnitude of the movement across the sliding surface will naturally decrease. An exponential reaching law is selected to achieve reaching law control. in and All are adjustable coefficients and are greater than zero. is an exponential approach term, which reduces the approach speed to zero quickly. It is a constant velocity approaching term, the purpose of which is to shorten the time it takes for the system to reach the sliding surface and speed up the response; S4, in order to better reduce the chattering of the sliding mode observer, the sigmoid ( x ) function and Functions are combined to obtain the reconstructed sliding mode observer: According to the above formula, the expression of back electromotive force is: The improved sliding mode observer is constructed as: Then the current observation deviation formula of the improved sliding mode observer is: S5. Use a phase-locked loop algorithm to further obtain more accurate motor speed information.

3. The high-efficiency, fast-response control method for a brushless, sensorless DC motor according to claim 2, characterized in that: The active disturbance rejection controller ADRC: The motor speed state equation is: Assume that the state variables of the system are , then the total disturbance of the system is expressed as: Assume that the input of the system is , then according to the analysis in the previous section, we have , then the state equation of the speed loop can be expressed as: The auto-disturbance rejection controller of the speed loop can be designed as follows: Tracking Differentiator (TD): in is the desired speed of the brushless DC motor, for tracking signal; Nonlinear state error feedback rate (NLSEF): Extended State Observer (ESO): The ESO above can be written in matrix form: Its characteristic equation is: To ensure the stability of the system, we have: ,in The bandwidth of the observer; the transfer function in ESO can be expressed as: in It is the speed tracking, but the change of current will affect right In order to further improve the observation efficiency of the observer, a proportional gain channel of the observation error is added to the disturbance observation channel; therefore, the above ESO is improved as follows: in is the differential gain coefficient of the observation error; the closed-loop transfer function in the above observer is expressed as: .

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