Speed Control Of Ultrasonic Motor Research Articles

Robust Speed Control of Ultrasonic Motors Based on Deep Reinforcement Learning of a Lyapunov Function

Speed control of ultrasonic motors (USM) needs to be precise, fast, and robust; however, this becomes a challenging task due to the nonlinear behavior of these motors including nonlinear response, pull-out phenomenon, and speed hysteresis. However, linear controllers would be suboptimal and unstable, and nonlinear controllers would require expert knowledge, expensive online calculations, or costly model estimation. In this paper, we propose a model-free nonlinear offline controller that can significantly mitigate these challenges. Using deep reinforcement learning (DRL) algorithms, a neural network speed controller was optimized. A soft actor-critic (SAC) DRL algorithm was chosen due to its sample efficiency, fast convergence, and stable learning. To ensure controller stability, a custom control Lyapunov reward function was proposed. The steady-state USM behavior was mathematically modeled for easing controller design under simulation. The SAC agent was designed and trained first in simulation and then further trained experimentally. The experimental results support that the trained controller can successfully expand speed operation range ([0, 300] rpm), plan optimal control trajectories, and stabilize performance under varying load torque and temperature drift.

Generalized Minimum Variance Iterative Learning Speed Control of Ultrasonic Motor

Generalized Minimum Variance Iterative Learning Speed Control of Ultrasonic Motor

Secant iterative learning control of ultrasonic motor

Aiming at the problem that the differential term of Newton iterative learning law is not easy to be determined and affects the control performance, the secant iterative learning law is proposed by using the secant method in numerical analysis technology. The proposed control strategy is applied to the speed control of ultrasonic motor to verify its effectiveness. Some practical improvements for the secant iterative learning control strategy are proposed to solve the problems in practical uses of the strategy. According to the nonlinear characteristics of ultrasonic motor, a simple method for determining the value of learning gain is obtained based on the experimental data. Furthermore, online adaptive adjustment method of learning gain is proposed to compensate the nonlinearity of ultrasonic motor. Experimental results show that the motor’s control performance progressively improves during the iterative learning process, featuring higher convergence speed and better performance, which indicates that the proposed control strategy is effective.

Model-free adaptive speed control on travelling wave ultrasonic motor

AbstractThis paper introduced a new data-driven control (DDC) method for the speed control of ultrasonic motor (USM). The model-free adaptive control (MFAC) strategy was presented in terms of its principles, algorithms, and parameter selection. To verify the efficiency of the proposed method, a speed-frequency-time model, which contained all the measurable nonlinearity and uncertainties based on experimental data was established for simulation to mimic the USM operation system. Furthermore, the model was identified using particle swarm optimization (PSO) method. Then, the control of the simulated system using MFAC was evaluated under different expectations in terms of overshoot, rise time and steady-state error. Finally, the MFAC results were compared with that of proportion iteration differentiation (PID) to demonstrate its advantages in controlling general random system.

Integration simulation method concerning speed control of ultrasonic motor

In this paper, the configuration of control system of the ultrasonic motor (USM) from finite element method (FEM) model by applying the nonlinear model order reduction (MOR) is proposed. First, the USM and the FEM model is introduced. Second, FEM model order reduction method is described. Third, the result of comparing the computing time and accuracy of the FEM model and reduced order model is shown. Finaly, nominal model for control is derived by system identification from reduced order model. Nonlinear model predictive control (NMPC) is applied to the nominal model, and speed is controlled. the controller effect is comfirmed by applying the proposed reduced order model.

Self-tuning speed control of ultrasonic motor combined with efficiency optimization

Aiming at the nonlinear characteristics of ultrasonic motor (USM) control system, a self-tuning pole assignment speed control strategy is proposed in this paper. The parameters of motor system are identified online, and then the controller is modified online according to the identified parameters of motor. In view of the short-time working characteristic of USM, a method for determining initial values of parameters with online identification algorithms is presented. Using this method, efficient self-tuning control can be realized using a small quantity of testing data. The proposed strategy is robust and relatively simple. Experimental results indicate that the speed control performance is good.

Characteristic model of travelling wave ultrasonic motor

In general, the design and analysis of ultrasonic motor and motor’s control strategy are based on mathematical model. The academic model is widely used in the analysis of traveling wave ultrasonic motor (TWUSM). But the dispersive characteristic of piezoelectric ceramics and other complicated process, such as the friction, make the model’s precision not so accurate. On the other hand, identification modeling method, which is built based on the tested data, has obtained increasing application in the study of ultrasonic motor’s control technology. Based on the identification model, many control strategies can be designed easily. But the identification model is an approximate model, so if a more accurate model of ultrasonic motor can be obtained, the analysis and design of motor control system will be more effective. Characteristic model is a kind of identification model which can accurately describe the characteristics of TWUSM. Based on the tested data, this paper proposes the modeling method of ultrasonic motor’s characteristic model. The paper also makes a comparison of the effectiveness of different identification algorithms. Aiming at the speed control of ultrasonic motor, the influence of the parameter’s initial values on the precision of model is discussed. The calculating results indicate the availability of this characteristic model.

A Novel Ultrasonic Motor Driver Based on Two Phase PWM Signals

An ultrasonic motor (USM) has been widely used in many applications since it has several advantages over the conventional electromagnetic motor, such as high torque at low speeds, no electromagnetic interference, and high holding torque without power supply. However, in order to achieve high efficiency, its electrical drive system presents unique challenges, especially in producing two-phase signal (high frequency, high voltage, phase difference of two-phase signal) input to a low impedance capacitive motor. In this paper, a novel drive system based on microcontroller (ATmega16) has been proposed for ultrasonic motor. Drive system includes power drive circuit and control system. Power drive circuit is combined from Push-Pull Inverter to provide high-frequency two-phase voltages. A microcontroller was used to control ultrasonic motor drive system. PWM signals were generated and then directly applied to the MOSFET drivers for speed control of ultrasonic motor. The frequency and phase difference of two phase PWM signals can be directly changed by microcontroller. Detailed experimental results are provided to demonstrate the successful of the proposed drive system.

A PWM Technique for DSP Controlled Ultrasonic Motor Drive System

In this study, a PWM technique is presented for digital signal processor controlled drive system of travelling-wave ultrasonic motor. The drive system is high-frequency two-phase serial-resonant inverter using mechanical resonant frequency of the ultrasonic motor. A TMS320F243 digital signal processor was used to control ultrasonic motor drive system. PWM signal was generated and then applied to the low pass filter to produce reference DC voltage level for speed control of ultrasonic motor. The driving frequency was selected as control input in the speed and position control loops. Experimental results show that the proposed drive and control system gives superior steady-state and transient performances in the speed and position control of ultrasonic motor.

Servo speed control of travelling-wave ultrasonic motor using digital signal processor

In this study a novel servo speed control system for travelling-wave ultrasonic motor (TWUSM) has been presented. A drive system has been built based on two-phase high-frequency inverter using mechanical resonant frequency of the ultrasonic motor. The TMS320F243 digital signal processor (DSP) is adapted to ultrasonic motor drive system. The speed control of ultrasonic motor has been implemented with driving frequency in the range of 41.3–43.3 kHz. The improved speed characteristics realised by the proposed drive and control system have been demonstrated and validated by experiments.

1P1-2F-G1 温度特性を考慮した自己調整ファジィ制御器による超音波モータの速度制御

1P1-2F-G1 温度特性を考慮した自己調整ファジィ制御器による超音波モータの速度制御

Identification and speed control of ultrasonic motors based on neural networks

An ultrasonic motor (USM) is a newly developed motor that has many excellent performances, useful features and extensive applications. The operational characteristics of the USM are affected by many factors. Strongly nonlinear characteristics could be caused by the increase of temperature, the changes of load, driving frequency and voltage and many other factors. Therefore, it is difficult to perform effective control on USMs using traditional control methods based on mathematical models of systems. Recently, artificial intelligent methods based on neural networks have become the main approaches to perform USM control. However, the existing neural-network-based methods for USM control have some shortcomings, such as complex network structures, slower convergent speeds and lower convergent precision, as well as no theoretical guarantee on the convergence of control. Furthermore, it is difficult to obtain accurate control input for the USM by using a speed controller with a single control variable. In this paper, a bimodal controller is designed where both the driving frequency and amplitude of the applied voltage are used as control inputs. A novel input–output recurrent neural network (IORNN) identifier is constructed to dynamically identify the input–output relation of the ultrasonic motors. To guarantee convergence and for faster learning, the adaptive learning rates are derived using discrete-type Lyapunov stability analysis. Numerical results show that the proposed IORNN identifier can approximate the nonlinear input–output mapping of ultrasonic motors quite well. Compared with the existing method, the control precision can be increased by about three times and the convergence time can be decreased by about two times when the proposed method is employed. Good effectiveness of the proposed control scheme is also obtained for various reference speeds.

Robust Speed Control of Ultrasonic Motor Based on H.INF. Control with Repetitive Compensator.

A constant speed control system of an ultrasonic motor(USM)is designed based on H∞ control with a repetitive compensator. Generally driving mechanism of USM uses frictional force. It comes the following disadvantages of the motors : (1)the dynamic response shows non-linear natures and depends on the operating temperature ; (2)the average rotational speed gradually decreases with temperature rise ; (3)the speed fluctuates periodically synchronizing with rotation. To tackle the problems, multiplicative uncertainties are introduced into the plant model to represent the non-linearity and the temperature dependency. The decrease and the fluctuation in speed are treated as a step and a periodic disturbance respectively. The control system is designed as follows. Firstly, and integral type H∞ controller is designed which guarantees robust stability against the uncertainties. Secondly, a repetitive compensator is attached to the system without loosing stability to attenuate the periodic disturbance. Experiments confirm the validity of the proposed control system.

Speed control of ultrasonic motors using neural network

The ultrasonic motor (USM) is a newly developed motor, and it has excellent performance and many useful features, therefore, it has been expected to be of practical use. However, the driving principle of USM is different from that of other electromagnetic-type motors, and the mathematical model is complex to apply to motor control. Furthermore, the speed characteristics of the motor have heavy nonlinearity and vary with driving conditions. Hence, the precise speed control of USM is generally difficult. This paper proposes a new speed-control scheme for USM using a neural network. The proposed controller can approximate the nonlinear input-output mappings of the motor using a neural network and can compensate the characteristic variations by on-line learning using the error backpropagation algorithm. Then, the trained network finally makes an inverse model of the motor. The usefulness and validity of the proposed control scheme are examined in experiments.

Robust Speed Control of Ultrasonic Motor based on H.INF. Control with Repetitive Compensator.

A constant speed control system of an ultrasonic motor (USM) is designed based on H∞ control with a repetitive compensator. In spite of the excellent features, USM has the following problems because of the driving mechanism using frictional force: (1) the dynamic response is non-linear and depends on the temperature. (2) the averaged rotational speed gradually decreases as the temperature rises. (3) the speed fluctuates periodically depending on the rotational angle. In this study, the input and output of the USM are driving frequency and rotational speed respectively. The multiplicative uncertainty is introduced into the plant model to represent the non-linearity and the dependency on the temperature. The decreasing and fluctuating speed are considered as a step and a periodical speed disturbance respectively. The control system is designed as follows: Firstly, an integral type H∞ controller is designed which guarantees robust stability against the uncertainty. Secondly, a repetitive compensator is attached to the system without loosing stability to attenuate the periodical disturbance. Experiments confirms the validity of the proposed control system.

Speed control of ultrasonic motors by adaptive control with a simplified mathematical model

The ultrasonic motor is a new type of motor. In recent years, some mathematical models for the ultrasonic motor have been reported. However, these models are very complex to apply to control of the motor, and therefore speed or position controllers for this type of motor have been designed based on proportional and integral controllers or fuzzy controllers. Since these controllers cannot take account of the motor's dynamics, a simple and convenient mathematical model of the ultrasonic motor is necessary in order to achieve high control performance. The authors propose a simplified mathematical model for the ultrasonic motor, which is expressed by a difference equation, and they then design a speed controller based on adaptive control theory. Adaptive control is attractive for controlling the ultrasonic motor because its speed characteristics vary with drive conditions. The effectiveness of the proposed control scheme is demonstrated by experiments. Furthermore, the paper indicates the influence of control delay and model orders on the mathematical model experimentally.

ファジィ推論を導入した繰返し制御による超音波モータの高精度速度制御

超音波モータは、これまでの電磁モータと異なる新しい原理のモータであり、優れた性能と特徴を備えている。しかし、超音波モータはその動作原理および構造から回転むらを生じる。この回転むらは従来の小形モータと比較して大きいため、モータの高精度な速度制御の障害となる。これまでに、著者らは回転むらの持つ周期性に着目して、学習係数を固定した繰返し補償器により超音波モータの回転むらを低減した。しかし、学習係数が固定の場合には高速に回転むらを低減するとともに精密な速度制御を達成することは困難である。そこで本論文では高精度の速度制御を達成するために、制御状況に応じて学習係数をファジィ推論により調整する回転むら低減法を提案する。実験の結果、本制御を用いることで回転むらを無制御時の10分の1まで低減できた。

Adjustable speed control of ultrasonic motors by adaptive control

The driving principle of the ultrasonic motor (USM) is different from those of the electro-magnetic type motors. Some mathematical models for the USM have been reported; however, these models are very complex to apply for speed control of the USM. Therefore, the speed controllers have been designed using PI controllers or fuzzy controllers and it is necessary to develop a simple and convenient mathematical model for the USM in order to achieve a high-performance speed control. In this paper, a mathematical model for the USM is proposed which is simple and useful for speed control. The speed controller is designed based on the model using adaptive control theory. Adaptive control is attractive for control of the USM because the speed characteristics of the USM vary with drive conditions. The application of this control scheme to speed control for the USM is attempted first. The effectiveness of proposed control is demonstrated by experimental. >

ハイブリット制御による超音波モータの速度制御

ハイブリット制御による超音波モータの速度制御

Speed Control of Ultrasonic Motor by Adaptive Control.

Speed Control of Ultrasonic Motor by Adaptive Control.