DSP-based self-tuning IP speed controller with load torquecompensation for rolling mill DC drive

This paper describes the design and the implementation of a self-tuning integral-proportional (IP) speed controller for a rolling mill DC motor drive system, based on a 32-bit floating point digital signal processor (DSP)-TMS 320C30. To get a better transient response than conventional proportional-integral (PI) and/or integral-proportional (IP) speed control in the presence of transient disturbance and/or parameter variations, an adaptive self-tuning IP speed control with load torque feedforward compensation was used. The model parameters, related to motor and load inertia and damping coefficient, were estimated online by using recursive extended least squares (RELS) estimation algorithm. On the basis of the estimated model parameters and a pole-placement design, a control signal was calculated. Digital simulation and experimental results showed that the proposed controller possesses excellent adaptation capability under parameter change and a better transient recovery characteristic than a conventional PI/IP controller under load change     

Online self-tuning ANN-based speed control of a PM DC motor

This paper presents an online self-tuning artificial-neural-network (ANN)-based speed control scheme of a permanent magnet (PM) DC motor. For precise speed control, an online training algorithm with an adaptive learning rate is introduced, rather than using fixed weights and biases of the ANN. The complete system is implemented in real time using a digital signal processor controller board (DS1102) on a laboratory PM DC motor. To validate its efficacy, the performances of the proposed ANN-based scheme are compared with a proportional-integral controller-based PM DC motor drive system under different operating conditions. The comparative results show that the ANN-based speed control scheme is robust, accurate, and insensitive to parameter variations and load disturbances     

Implementation of self-tuning algorithms for reference tracking ofa DC drive using a DSP chip

This paper describes the implementation of two self-tuning control algorithms for the speed control of a permanent magnet DC motor. The algorithms minimize a cost function incorporating system input, output, and set-point variation for reference tracking. Variable forgetting factor using data normalization with constant trace has been utilized. Self-tuning controllers have been implemented using a single-chip digital signal processor (DSP). It results in reduction of system hardware, cost, and calculation time     

Adaptive Multivarable Drug Delivery: Control of Artenal Pressure and Cardiac Output in Anesthetized Dogs

An adaptive algorithm (CAMAC, control advance moving average controller) to control multiinput/multioutput physiological systems has been implemented and tested. The algorithm is a self-tuning controller that determines the input on the basis of the expected difference between the output and desired output at a time interval equal to or greater than the system dead time. The algorithm was used to simultaneously control mean arterial pressure and cardiac output in anesthetized dogs by the simultaneous computer-controlled infusion of sodium nitroprusside and dobutamine. The results demonstrate the feasibility of using CAMAC for multivariable drug delivery, but they indicate the need for further work before clinical applications are attempted.     

A DSP-based adaptive controller for a smooth positioning system

The implementation of a self-tuning regulator for the positioning of a direct-drive servomotor is described. The servo motor is a permanent magnet DC motor in which no speed reducer is used. The auto-tuning regulator consists of two major loops. The inner loop contains a feedback (PD or PID) regulator with additional feedforward terms. The parameters of the feedforward compensation are adjusted by the outer loop, which contains an online parameter estimator. The estimator is based on a recursive least-squares equation, and the estimated parameters are the load inertia and viscous friction. This self-tuning regulator has been simulated with PC.MATLAB, and the results demonstrate the high performance of the scheme. Experimental results obtained with a small DC motor (Electrocraft E-576) are presented, and these results show good agreement with the digital simulation results. There are two innovative aspects to this work. First, parameter estimation is used to adapt the feedforward compensation terms instead of the gains of the feedback controller, as usually is the case in conventional indirect self-tuning regulators. Secondly, the complete adaptive controller has been implemented using a single-chip digital signal processor (DSP), which results in the reduction of system hardware and cost     

An adjustable model reference adaptive control reconfiguration of self-tuning pole replacement

An adjustable model reference adaptive control strategy is proposed where both the controller and reference model parameters are adapted. Adaptive control laws for this new structure implementing pole cancellation and replacement and avoiding the zero cancellation usually required by model reference adaptive control are developed from self-tuning adaptive algorithm modification.     

An Improved Deadbeat Current Control Scheme With a Novel Adaptive Self-Tuning Load Model for a Three-Phase PWM Voltage-Source Inverter

In this paper, an improved deadbeat current control scheme with a novel adaptive self-tuning load model for a three-phase pulsewidth-modulated (PWM) voltage-source inverter is proposed. First, to achieve high-bandwidth current control characteristics, an improved deadbeat current controller with delay compensation is adopted. The compensation method forces the delay elements, which are caused by voltage calculation, PWM, and synchronous frame rotation, to be equivalently placed outside the closed-loop control system. Hence, their effect on the closed-loop stability is eliminated, and the current controller can be designed with a higher bandwidth. Second, to relax the parameter sensitivity issue of the deadbeat controller and to realize a control scheme with reduced sensors, a novel adaptive self-tuning load model is emerged in the control structure. The adaptive model is designed with low computational demand to estimate in real time the load parameters (R,L) and the back-electromotive-force voltage simultaneously. A unified solution to the present nonlinear estimation problem is presented by adopting a parallel observer structure. Furthermore, the adaptive model has the necessary phase advance of the estimated quantities, which compensates for the total system's delay. Comparative evaluation results are presented to demonstrate the validity and effectiveness of the proposed control scheme     

New self-tuning fuzzy PI control of a novel doubly salient permanent-magnet motor drive

In a doubly salient permanent-magnet (DSPM) motor drive, it is difficult to get satisfied control characteristics by using a normal linear proportional plus integral (PI) controller due to the high nonlinearity between speed and current or torque. Hence, a new self-tuning fuzzy PI controller with conditional integral, which is performed by a single-chip N87C196KD, is proposed. The initial parameters of the controller are optimized by using genetic arithmetic. Simulation and experiments on the newly proposed 8/6-pole DSPM machine have shown that the proposed new self-tuning fuzzy PI controller offers better adaptability than the normal linear PI control and that the developed motor drive offers better steady-state and dynamic performances.     

噪声有源自校正预测控制

有源噪声控制（ANC）的经典方法是采用有限脉冲响应（FIR）滤波器的Filter-X算法，该算法的一个主要缺点是次级声路径响应对控制滤波器参数自适应的收敛速度有较大影响。将预测控制方法应用到有源噪声控制领域，给出了一种参数在线自适应算法，该算法的收敛速度不受次级声路径响应的影响。仿真结果表明，给出的控制方法比传的Filter-X控制有更小的稳态误差，而且收敛速度更快。     

High-performance speed control of electric machine usinglow-precision shaft encoder

For a high-performance servo drive system, it is important to estimate and control the motor speed precisely over a wide-speed range. Therefore, the disturbance-rejection ability and the robustness to variations of the mechanical parameters such as inertia should be considered. This paper shows that the adaptive state estimator and self-tuning regulator based on the recursive extended least squares (RELS) parameter identification method can achieve high-performance speed control over a wide-speed range. The RELS method identifies the variations of mechanical parameters, and the estimated mechanical parameters are used to replace the role of manual tuning by adjusting the gain of the speed controller automatically for good dynamic response. Also, these estimated parameters are used to adapt the Kalman filter, which is an optimal state estimator, to provide good estimation performance for the rotor speed, rotor position and disturbance torque even in a noisy environment. Simulation and experimental results show an improved speed control performance in the wide-speed range     

噪声有源反馈自校正控制

提出了一种前馈补偿和误差反馈相结合的噪声有源自校正控制方法,给出了两种未知参数的在线自适应学习算法,在控制系统中引入两个反馈闭环以改善系统的性能。仿真结果表明,前馈补偿和误差反馈相结合的噪声有源自校正控制比传统的Ｆｉｌｔｅｒ－Ｘ控制更为有效。     

Position control of ultrasonic motors using MRAC and dead-zonecompensation with fuzzy inference

The ultrasonic motor has a heavy nonlinearity, which varies with driving conditions and possesses variable dead-zone in the control input associated with applied load torque. The dead-zone is a problem as an accurate positioning actuator for industrial applications and it is important to eliminate the dead-zone in order to improve the control performance. This paper proposes a new position control scheme of ultrasonic motors to overcome dead-zone employing model reference adaptive control with fuzzy inference. The dead-zone is compensated by fuzzy inference, whereas model reference adaptive control performs accurate position control. Mathematical models are formulated and experimental results are given to validate the proposed position control scheme     

Adaptive feedback control

Adaptive control is now finding its way into the marketplace after many years of effort. This paper reviews some ideas used to design adaptive control systems. It covers early ideas which primarily attempt to compensate for gain variations and more general methods like gain scheduling, model reference adaptive control, and self-tuning regulators. It is shown that adaptive control laws can be obtained using stochastic control theory. Techniques for analyzing adaptive systems are discussed. This covers stability and convergence analysis. Issues of importance for applications like parameterization, tuning, and tracking, as well as different ways of using adaptive control are also discussed. An overview of applications which includes feasibility studies as well as products based on adaptive techniques concludes the paper.     

A novel pitch control system for a wind turbine driven by a variable-speed pump-controlled hydraulic servo system

The paper aims to develop a novel pitch control system for a large wind turbine driven by a variable-speed pump-controlled hydraulic servo system. To perform practical pitch control experiments, a full-scale test rig of the hydraulic pitch control system for a 2 MW wind turbine’s blade, including a novel pitch control mechanism, a variable-speed pump-controlled hydraulic servo system, a disturbance system and a PC-based control system, is designed and set up. The variable-speed pump-controlled hydraulic servo system, containing an AC servo motor, a constant displacement hydraulic piston pump two differential hydraulic cylinders and hydraulic circuits, achieved high response and high energy efficiency, so it is suitable for wind turbine applications. Besides, to implement the pitch control in the proposed novel pitch control system, an adaptive fuzzy controller with self-tuning fuzzy sliding-mode compensation (AFC-STFSMC) is developed to design the pitch controller. Finally, the developed variable-speed pump-controlled hydraulic servo system was built and verified for the path tracking control and path-positioning control of the pitch control of the wind turbines by practical experiments in a full-scale test rig under different path profiles, load torques, and random wind speeds.     

A fully integrated CMOS direct-conversion transmitter front-end for WiMAX

A naturally commutated six-pulse cycloconverter working in the inverting mode is used to feed power to a single phase AC motor at 400 Hz. The motor is connected at the input side of the cycloconverter while the three-phase mains is connected at its output. Three-phase mains feeds power to the input side of the cycloconverter which is arranged as a tuned load at 400 Hz. The effect of the single-phase induction motor on system performance is discussed. The principle of voltage and frequency control for proper operation of the induction motor is presented. The results are experimentally verified.     

Motion control with induction motors

Induction motors (IM) provide a very wide speed range, mechanically robust and relatively low cost motion control option. An up-to-date summary of the status of induction motor motion control technology is the subject of this paper. The topics which this paper includes are as follows: basic motion control system requirements; field orientation instantaneous torque control principles for induction motors (FO-IM); current regulators for induction motor motion control; flux and torque regulators for induction motor motion control; self commissioning and continuous self-tuning for field orientation. Technology advances based on modern control and estimation theory have the potential to further enhance the capability of this important class of servo drive systems     

An MRAC-based nonlinear speed control of an interior PM synchronous motor with improved maximum torque operation

A model reference adaptive control (MRAC)-based nonlinear speed control strategy of an interior permanent magnet (IPM) synchronous motor with an improved maximum torque operation is presented. In most servo systems, the controller is designed under the assumption that the electrical dynamics are neglected by the field-oriented control. This requires a high-performance inner-loop current control strategy. However, the separate designs for a high-performance current regulator and a robust speed controller need considerable effort. To overcome this limitation, an MRAC-based nonlinear speed control strategy for the IPM synchronous motor is presented, considering the whole nonlinear dynamics. Nonlinear speed control is achieved by an input–output linearization scheme. This scheme, however, gives an unsatisfactory performance under the mismatch of the system parameters and load conditions. For the robust output response, the controller parameters are estimated by an MRAC technique in which the disturbance torque and flux linkage are estimated. The adaptation laws are derived from Lyapunov stability theory. In view of the drive efficiency, the motor has to provide the maximum torque for a given input. To drive the IPM synchronous motor under improved maximum torque operation, the estimated flux linkage is employed for the generation of the d-axis current command. The robustness and output performance of the proposed control scheme are verified through simulation results.     

基于Dahlin算法变风量空调自校正PID控制

变风量空调具有时变、延时、非线性等特点,在此类系统中传统的PID控制算法难以取得最佳的控制效果.基于广义预测自校正的控制算法,控制精度高,具有较强的跟踪性能,但是以增大的计算量和频繁的调节系统参数为代价的.文中提出一种基于改进的Dahlin参数整定方法的自校正PID控制器,该算法在理论建模的基础上,采用在线的带遗忘因子最小二乘法,实现传递函数的参数估计,建立了系统PID参数之间的关系式,实现变风量空调系统的末端控制.算法仿真运算及实验表明,与传统PID及广义预测自校正控制方法相比,文中方法控制精度高于传统PID,同时计算复杂度低于通常广义预测自校正控制.     

电机软启动自整定模糊控制器的研究与设计

异步电动机软启动的过程中,传统的PID控制方法难以达到理想的控制效果。本文利用自适应控制理论和模糊控制理论的特性,结合二者的优点,设计出一种快速调节能力强的基于参数自整定模糊控制的电动机软启动控制器。利用自整定模糊决策对电动机启动过程中的电流大小进行控制,优化了系统的控制效果。仿真结果表明,系统具有良好的动静态性能,达到了平稳启动的目的。     

一种基于李亚普诺夫方法的非线性自整定PID控制系统的研究

应用李亚普诺夫方法与自适应控制原理针对一类非线性PID控制系统提出了一种自整定方法,运用有监督控制和在线调整自适应控制律对PID控制系统的3个控制参数进行在线调整及更新,保证了非线性PID控制系统的闭环稳定性.最后利用该方法控制倒摆系统的运动轨迹问题,仿真结果表明该方法可以获得令人满意的控制性能.