Optimal two-vector combination-based model predictive current control with compensation for PMSM drives

The duty-ratio-based model predictive control (D-MPC) is rapidly researched for permanent-magnet synchronous machine (PMSM) drives. Existing D-MPC methods produce large current ripple and distortion. To solve this issue and promote the system performance, an optimal two-vector combination MPC (OTC-MPC) is proposed for current control in this paper. The collection of the combination is firstly produced for the proposed OTC-MPC by combining the two vectors and corresponding duty-ratio, and then the optimal combination is selected among all feasible two-vector combinations, thus, the output vectors and duty-ratio are simultaneously optimised. The optimising process is simplified so that the proposed OTC-MPC can be easily implemented. Moreover, a simplified repetitive control with feed-forward compensation method is added to eliminate the predictive current errors of MPC, and also to improve the system robustness against external disturbances. Theoretical analysis, simulation and experimental results demonstrate that the proposed OTC-MPC effectively reduces current ripple and distortion while retaining fast dynamic response compared with the conventional D-MPC.     

Robust model predictive control and observer for direct driveapplications

In this paper, robust position control of a direct drive using a state space model predictive control (MPC) algorithm is presented. The proposed controller consists of a state feedback regulator and a feedforward controller. Their gains are obtained by minimizing a cost function that is a sum of the position tracking errors and the control cost over some user defined time horizons. The effects of the controller parameters on the dynamic performance and the robustness of the direct drive are investigated. To provide good estimates of the state variables in the presence of load disturbance, a new observer based on the receding horizon concept is also formulated. Experimental results are presented to demonstrate the effectiveness of the approach     

A novel AQM algorithm based on feedforward model predictive control

Developing feedforward model predictive controller as an active queue management (AQM) scheme is studied in this paper. MPC is an advanced control strategy for AQM. However, the conventional MPC is usually an implementable form of feedback MPC. In this paper, a feedforward and feedback optimal control law is presented. It is a clean, easily implementable, version of model predictive control that incorporates feedforward. Firstly, we use the nominal fluid model to design the feedforward control input so that the output tracks the given queue length with small error. Furthermore, in order to achieve robust performance and to reject the (unmeasured) disturbance, the feedback component is designed. In particular, a disturbance observer is incorporated into the prediction output in standard feedback MPC. This framework can significantly improve performance in the presence of measurement noise and certain types of model uncertainty. Finally, the simulation results show the effectiveness of FF‐AQM algorithm.     

Inverter Nonlinearity Compensation in the Presence of Current Measurement Errors and Switching Device Parameter Uncertainties

This paper proposes a compensation strategy for the unwanted disturbance voltage due to inverter nonlinearity. We employ an emerging learning technique called support vector regression (SVR). SVR constructs a motor dynamic voltage model by a linear combination of the current samples in real time. The model exhibits fast observer dynamics and robustness to observation noise. Then the disturbance voltage is estimated by subtracting the constructed voltage model from the current controller output. The proposed method compensates for all of the inverter nonlinearity factors at the same time. All the processes in estimating distortions are independent of the dead time and power device parameters. From the analysis of the effect on current measurement errors, we confirmed that the sampling error had little negative impact on the proposed estimation method. Experiments demonstrate the superiority of the proposed method in suppressing voltage distortions caused by inverter nonlinearity     

Robust High Bandwidth Discrete-Time Predictive Current Control with Predictive Internal Model—A Unified Approach for Voltage-Source PWM Converters

This paper presents a robust high bandwidth discrete-time predictive current control scheme for voltage-source pulsewidth-modulated (VS-PWM) converters. First, to achieve high bandwidth current control characteristics, a digital predictive current controller with delay compensation is adopted. The compensation method utilizes a current observer with an adaptive internal model for system uncertainties. The predictive nature of both the current observer and the internal model forces the delays elements to be equivalently placed outside the closed loop system. Second, to ensure perfect tracking of the output current in the presence of uncertainties and providing means for attenuating low- and high- frequency system disturbances, the frequency modes of the disturbances to be eliminated should be included in the stable closed loop system. Toward this, an adaptive internal model for the estimated uncertainty dynamics is proposed. To cope with the high bandwidth property of the lump of uncertainties in VS-PWM converter applications, the disturbance slowly varying assumption is relaxed in the proposed controller. The relaxation is achieved by adopting a curbing sliding-mode-based feedback gain vector within the internal model observation system. Comparative evaluation tests were carried out on a grid-connected VS-PWM converter and a direct drive permanent magnet synchronous motor (DD-PMSM) drive system to demonstrate the validity and effectiveness of the proposed control scheme at different operating conditions.     

An improved deadbeat control for UPS using disturbance observers

A digital control technique for the inverter stage of uninterruptible power supplies is proposed, which is based on a predictive regulator on both output voltage and inductor current. Its aim is to achieve a deadbeat dynamic response for the controlled variables (output voltage and inverter current). Besides the linear state feedback which allocates system poles at the origin so as to achieve deadbeat response for all state variables, the use of a disturbance observer for the estimation of the load current and of any other source of errors (such as dead-times, parameter, and model mismatches) is investigated. The proposed solution is able to guarantee a fast dynamic response and also a precise compensation of any source of unpredictable disturbance. Moreover, with a proper design of observer parameters, it is possible to reduce control sensitivity to model uncertainties, parameter mismatches, and noise on sensed variables, which usually characterizes existing deadbeat control techniques. Finally, the control algorithm is quite simple and requires only the measurements of the output voltage and inductor current. Experimental results on a single-phase 2 kVA prototype show the effectiveness of the proposed approach.     

On-line compensation of dead-time and inverter nonlinearity with disturbance voltage observer

This paper discusses and analyses a simple on-line compensation scheme for dead-time and inverter nonlinearity in the pulse width modulated (PWM) voltage source inverter (VSI). Dead-time effect and voltage drop in switching devices cause nonlinearity between reference and output voltage. In a conventional three-phase six-switch inverter, this nonideal condition adds extraneous harmonics that badly disturb voltage characteristics. In its turn, voltage disturbance causes distortion of the current waveform and degrades performance. In this paper, an on-line dead-time compensation method based on inverse dynamics control is proposed, and it is much simpler than conventional full/reduced order observation methods adopted in dead-time compensation. Disturbance voltages are observed on-line with no additional circuitry or off-line measurements. The observed disturbance voltages are fed back to the voltage reference for compensation. Stability problem of the proposed observer arisen from inverter delay and parameter mismatch was analysed. The proposed method is applied to a surface-mounted permanent-magnet synchronous motor (SPMSM) drive. The effectiveness of the proposed scheme is validated by the experimental results.     

基于扩张状态观测器的永磁同步电机无差拍电流预测控制

针对永磁同步电机预测控制中电机参数扰动偏差造成的输出电流静差及振荡问题,采用基于扩张状态观测器的无差拍电流预测控制算法,构建相应的扰动观测器来观测参数偏差造成的系统扰动,为传统预测控制算法提供实时性扰动补偿。采用有功阻尼概念对转速PI参数进行设计,并针对控制系统的延时进行了补偿。仿真结果表明所提出的算法能够快速无静差地观测系统扰动,有效避免参数扰动偏差对电流预测系统的影响,同时转速环也具有良好的动态性能。     

三相PWM整流器前馈与滑模变结构控制研究

在两相旋转坐标系下对三相电压型PWM整流器进行建模分析。针对双闭环PI控制策略抑制负载扰动及电网电压波动能力差,以及系统动态响应慢等问题,提出了负载电流前馈策略来提高系统抗负载波动能力。并且电流环采用基于PID趋近率的滑模变结构控制策略来满足前馈控制策略对内环响应速度的要求,并提高系统动态性能以及鲁棒性,PID趋近率可以有效抑制传统变结构的抖振问题。应用Matlab/Simulink软件进行仿真,并以DSP TMS320X2812为核心搭建优化控制器的三相VSR实验平台,进行仿真及实验验证。结果显示本文所提出控制方法可有效抑制负载变化、电网电压波动以及其它干扰所对直流电压稳定性的影响,具有很强的鲁棒性,动态响应速度快且性能稳定。     

扰动观测器在空间光通信PAT系统中的应用

为了提高空间光通信PAT系统的扰动抑制能力,提出了一种基于扰动观测器的控制方法。该方法首先对PAT系统进行分析,得到简化的控制模型,然后利用扰动观测器从电机转动位置和光斑位置中观测出扰动,最后将扰动等效补偿量加入到电流环前的综合点。精跟踪系统的仿真实验结果表明:相比常规的PD控制器,加入扰动观测器使扰动隔离度在电机电流饱和前的几乎所有频率处都得到了提升,最优情况可达到28.2 dB;同时,该方法具有很强的鲁棒性,在系统物理参数变化15%时扰动隔离度依然比没有使用扰动观测器时提高了至少1倍。所述的控制方法显著提高了PAT系统的抗扰动性能,对大范围与高动态的精密光电跟踪系统有一定的参考价值。     

Combined deadbeat control of a series-parallel convertercombination used as a universal power filter

This paper presents the notion of combined control of a system of interconnected power electronic converters. The concept is demonstrated using a three-phase series-parallel active power filter as an example. The described active power filter consists of a series-parallel combination of two full bridge VSIs capable of arbitrarily controlling the input current and output voltage. The proposed control scheme treats the converter combination as a single unit and uses the inverse system model to generate deadbeat control response for both input current and output voltage. A full-order predictive state observer is used to reduce the number of sensors. Simulation results show better disturbance rejection characteristics of the proposed control when compared to the separately controlled converter scheme     

Intelligent voltage control strategy for three-phase UPS inverters with output LC filter

This paper presents a supervisory fuzzy neural network control (SFNNC) method for a three-phase inverter of uninterruptible power supplies (UPSs). The proposed voltage controller is comprised of a fuzzy neural network control (FNNC) term and a supervisory control term. The FNNC term is deliberately employed to estimate the uncertain terms, and the supervisory control term is designed based on the sliding mode technique to stabilise the system dynamic errors. To improve the learning capability, the FNNC term incorporates an online parameter training methodology, using the gradient descent method and Lyapunov stability theory. Besides, a linear load current observer that estimates the load currents is used to exclude the load current sensors. The proposed SFNN controller and the observer are robust to the filter inductance variations, and their stability analyses are described in detail. The experimental results obtained on a prototype UPS test bed with a TMS320F28335 DSP are presented to validate the feasibility of the proposed scheme. Verification results demonstrate that the proposed control strategy can achieve smaller steady-state error and lower total harmonic distortion when subjected to nonlinear or unbalanced loads compared to the conventional sliding mode control method.     

An adaptive dead-time compensation strategy for voltage source inverter fed motor drives

This paper presents an adaptive dead-time compensation strategy to obtain fundamental phase voltage for inverter fed vector controlled permanent magnet synchronous motor drives. The amplitude of phase dead-time compensation voltage (DTCV) to compensate disturbance voltage due to undesirable characteristics of inverter, such as dead-time, turn-on/off time of switching devices, and on-voltages of switching devices and diodes is adaptively determined according to a dead-time compensation time (DTCT). DTCT is identified on-line with using a /spl delta/-axis disturbance voltage in the current reference frame that is synchronized with current vector. The /spl delta/-axis disturbance voltage is estimated by a disturbance observer. The accuracy of identified DTCT is experimentally confirmed by calculating the mean absolute percentage error (MAPE) between a calculated active power and a measured one. MAPE for adaptive DTCT is almost within 5% at any operating point.     

Robust friction state observer and recurrent fuzzy neural network design for dynamic friction compensation with backstepping control

In this article, we investigate a robust friction compensation scheme for the purpose of accomplishing high-precision positioning performance in a servo mechanical system with nonlinear dynamic friction. To estimate the friction state and tackle the robustness problem for uncertainty, a recurrent fuzzy neural network (RFNN) and reconstructed error compensator as well as a robust friction state observer are developed. The asymptotic stability of the series of friction compensation methodologies are verified from the Lyapunov’s stability theory. Some simulations and experiments on a frictional servo mechanical system were carried out to evaluate the effectiveness of the proposed control scheme.     

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.     

直流微电网双向AC/DC变换器鲁棒前馈控制策略研究

针对双向AC/DC功率变换器在直流微电网母线电压稳定性方面的问题,文中提出了一种结合LESO和滑模理论的前馈鲁棒控制策略。通过建立直流微电网三相AC/DC双向功率变换器的动态数学模型,架构了三阶线性扩张状态观测器,并将三阶LESO的观测值用于滑模控制器的设计。该控制策略能够在不需要额外电流传感器的情况下实现前馈控制,并确保系统具有良好的动态性能。该策略还能够有效降低滑模控制的实现难度,提高系统的鲁棒性。仿真分析验证了文中所提控制策略的有效性。     

Performance evaluation of a MPPT controller with model predictive control for a photovoltaic system

ABSTRACT

Efficiency has been a major factor in the growth of photovoltaic (PV) systems. Different control techniques have been explored to extract maximum power from PV systems under varying environmental conditions. This paper evaluates the performance of a new improved control technique known as model predictive control (MPC) in power extraction from PV systems. Exploiting the ability of MPC to predict future state of controlled variables, MPC has been implemented for tacking of maximum power point (MPP) of a PV system. Application of MPC for maximum power point tracking (MPPT) has been found to result into faster tracking of MPP under continuously varying atmospheric conditions providing an efficient system. It helps in reducing unwanted oscillations with an increase in tracking speed. A detailed step by step process of designing a model predictive controller has been discussed. Here, MPC has been applied in conjunction with conventional perturb and observe (P&O) method for controlling the dc-dc boost converter switching, harvesting maximum power from a PV array. The results of MPC controller has been compared with two widely used conventional methods of MPPT, viz. incremental conductance method and P&O method. The MPC controller scheme has been designed, implemented and tested in MATLAB/Simulink environment and has also been experimentally validated using a laboratory prototype of a PV system.     

Microprocessor based robust digital control for UPS withthree-phase PWM inverter

This paper describes a novel method of robust (insensitive to system parameter variations and load current changes) and fast digital control for an uninterruptible power supply (UPS) with a three-phase PWM inverter. The purpose of this paper is to propose a method by which characteristics better than those by conventional methods are obtained using an algorithm simpler than that of conventional methods. The experiments show that the purpose is achieved and the proposed method offers a total harmonic distortion of 0.6% of the output voltage waveform at a full nonlinear load. The analysis shows that the stability of the method is sufficient. Three features of the method are: (a) a capacitor current observer for stabilization and a disturbance observer for robustness are used to compensate the time lag by the computation and the disturbances, in a minor loop of the capacitor current through an inductor-capacitor filter of the inverter; (b) new models of the inverter and the disturbances are established to simplify these observers; and (c) the output voltage control loop can be designed easily and exactly because the minor loop realizes a rapid and robust control of the current     

Adaptive positioning control for a LPMSM drive based on adapted inverse model and robust disturbance observer

The adaptive robust positioning control for a linear permanent magnet synchronous motor drive based on adapted inverse model and robust disturbance observer is studied in this paper. First, a model following two-degrees-of-freedom controller consisting of a command feedforward controller (FFC) and a feedback controller (FBC) is developed. According to the estimated motor drive dynamic model and the given position tracking response, the inner speed controller is first designed. Then, the transfer function of FFC is found based on the inverse model of inner speed closed-loop and the chosen reference model. The practically unrealizable problem possessed by traditional feedforward control is avoided by the proposed FFC. As to the FBC, it is quantitatively designed using reduced plant model to meet the specified load force regulation control specifications. In dealing with the robust control, a disturbance observer based robust control scheme and a parameter identifier are developed. The key parameters in the robust control scheme are designed considering the effect of system dead-time. The identification mechanism is devised to obtain the parameter uncertainties from the observed disturbance signal. Then by online adapting the parameters set in the FFC according to the identified parameters, the nonideal disturbance observer based robust control can be corrected to yield very close model following position tracking control. Meanwhile, the regulation control performance is also further improved by the robust control. In the proposed identification scheme, the effect of a nonideal differentiator in the accuracy of identification results is taken into account, and the compromise between performance, stability, and control effort limit is also considered in the whole proposed control scheme.