Fuzzy adaptive single neuron NN control of brushless DC motor

Inherently, the brushless DC motor (BLDCM) is a nonlinear plant. So, it is hard to get a good performance by using the conventional PI controller for the speed control of BLDCM. In this paper, a fuzzy adaptive single neuron neural networks (NN) controller for BLDCM is developed. The fuzzy logic system (FLS) is adopted to adjust the parameter K of single neuron NN controller online. By this way, performance of the system can be improved. Performances of the proposed fuzzy adaptive single neuron NN controller are compared with the performances of conventional PI controller and normal single neuron NN controller. The experimental results demonstrate that a good control performance is achieved. The using of fuzzy adaptive single neuron NN makes the drive system robust, accurate, and insensitive to parameter variations.     

Anti-windup compensator for active queue management in TCP networks

In this paper, we apply a dynamic anti-windup scheme for improving the performance of a conventional proportional–integral (PI) controller for active queue management (AQM) supporting TCP flows. When a PI controller is used for AQM, the windup phenomenon of the integral action can cause performance degradation because the packet drop probability is limited between 0 and 1. Therefore we suggest a TCP/AQM model with a saturating actuator and apply a dynamic anti-windup method for improving the performance of the conventional PI AQM scheme. The proposed scheme not only provides graceful performance degradation, but also guarantees the stability of the overall system with the linearized TCP model. We verify the performance of the proposed scheme through ns-2 simulations. The simulation results show that our scheme outperforms the conventional PI controller when the traffic load is not stationary, which is always the case in real network environment.     

Robust control design for precision positioning of a generic piezoelectric system with consideration of microscopic hysteresis effects

This study performs precision positioning of a generic piezoelectric structure against hysteresis effects by finite elements, microscopic hysteresis cancellation and robust H _?? compensation. The designed control algorithm is expected to be effective in enhancing servo performance of hard disk drives. The precision positioning is accomplished by adding a polarization term into the linear constitutive equations of piezoelectric materials. This polarization term is then described by the well-known Preisach model. Applying basic principles of finite elements and Hamilton??s thoery, the macroscopic governing equations of an arbitrary piezoelectric system in finite elements are obtained. Based on the macro-model, a controller consisting of two parts is designed to perform the precision positioning of a generic piezo-structure. The first part is responsible for direct hysteresis cancellation at the microscopic level, while the second one is a robust H _?? controller to overcome inevitable cancellation errors. In this way, the control effort is then more effective than the conventional PI and double-lead controller without microscopic hysteresis cancellation. A simple piezoelectric structure of a bender-bimorph cantilever beam is considered for designs and experimental validation. Based on experimental results, the proposed control design is found effective to suppress hysteresis effects as opposed to conventional controllers.     

Advantages of the passivity based control in dynamic voltage restorers for power quality improvement

A better and feasible control strategy for dynamic voltage restorers (DVR) is presented in this paper: the passivity based control (PBC) allows a better compensation performance under transient and steady state operating conditions, and provides tracking with zero error of any reference for linear and nonlinear loads. The closed-loop source-DVR-PBC-load system is asymptotically stable at all operating points, with practically very slight constraints; its transient response is faster than with classical controllers, and does not present overshoots. These characteristics do not depend on source voltage disturbances, the kind of load, or parameter variations. The PBC uses less digital operations than the PI, and does not require dq transformations.     

Robust sampled-data H∞-flight-controller design for high α stability-axis roll maneuver

This paper demonstrates a design application of a robust sampled-data H_∞-controller for a high-performance fighter aircraft executing a high α stability-axis roll maneuver. The performance of the sampled-data H_∞-controller is compared with that of the continuous-time H_∞-controller (based on the mixed-sensitivity and the closed-loop model matching approaches) and also of the conventional digital H_∞-controllers. At low sampling rates, nonlinear simulations show better performance using the sampled-data H_∞-controller than those of other controllers. The sampled-data H_∞-controller also has the advantage that the stability of the resulting closed-loop system is more tolerant to sampling time and controller gain uncertainties, thus leading to a more resilient and practical controller design approach.     

A robust two degree-of-freedom controller for systems with both model and measurement uncertainty

This paper presents a design method for robust two degree-of-freedom (DOF) controllers that optimize the control performance with respect to both model uncertainty and signal measurement uncertainty. In many situations, non-causal feedforward is a welcome control addition when closed loop feedback bandwidth limitations exist due to plant dynamics such as: delays, non-minimum phase zeros, poorly placed zeros and poles (Xie, Alleyne, Greer, and Deneault (2013); Xie (2013), etc. However, feedforward control is sensitive to both model uncertainty and signal measurement uncertainty. The latter is particularly true when the feedforward is responding to pre-measured disturbance signals. The combined sensitivity will deteriorate the feedforward controller performance if care is not taken in design. In this paper a two DOF design is introduced which optimizes the performance based on a given estimate of uncertainties. The controller design uses H_∞ tools to balance the controlled system bandwidth with increased sensitivity to signal measurement uncertainties. A successful case study on an experimental header height control system for a combine harvester is shown as an example of the approach.     

The intelligent integrated speed controller of DTC for induction motor

The parameters selection of proportional coefficient and integral coefficient (PI) for speed controller is important for direct torque control system. However, it is difficult to adjust these parameters. In this paper, firstly, we use particle swarm optimization to search the appropriate PI values of the speed controller. Secondly, based on the optimized PI parameters, the fuzzy-PI speed control strategy is presented to solve the poor self-adaptability problem. Thus, the proportional coefficient k _p and integral coefficient k _i can be adjusted dynamically to adapt to the speed variations. And finally, to obtain the high-speed parallel processing ability, the well-trained RBF neural network replaces the fuzzy-PI speed controller. The comparison with conventional PI speed controller shows that the proposed intelligent integrated speed controller brings good benefits of fast speed response and good stability and reduces the torque ripple. The validity of the proposed intelligent integrated speed controller is verified by the simulation results.     

Characteristic model based all-coefficient adaptive control of an AMB suspended energy storage flywheel test rig

Feedback control of active magnetic bearing (AMB) suspended energy storage flywheel systems is critical in the operation of the systems and has been well studied. Both the classical proportional-integral-derivative (PID) control design method and modern control theory, such as H_∞ control and μ-synthesis, have been explored. PID control is easy to implement but is not effective in handling complex rotordynamics. Modern control design methods usually require a plant model and an accurate characterization of the uncertainties. In each case, few experimental validation results on the closed-loop performance are available because of the costs and the technical challenges associated with the construction of experimental test rigs. In this paper, we apply the characteristic model based all-coefficient adaptive control (ACAC) design method for the stabilization of an AMB suspended flywheel test rig we recently constructed. Both simulation and experimental results demonstrate strong closed-loop performance in spite of the simplicity of the control design and implementation.     

Model-reference robust tuning of 2DoF PI controllers for first- and second-order plus dead-time controlled processes

The aim of this paper is to present a robust tuning method for two-degree-of-freedom (2DoF) proportional integral (PI) controllers. This is based on the use of a model reference optimization procedure with servo and regulatory target closed-loop transfer functions for first- and second-order plus dead-time (FOPDT, SOPDT) controlled process models. The designer is allowed to deal with the performance/robustness trade-off of the closed-loop control system by specifying the desired robustness level by selecting a maximum sensitivity in the range from 1.4 to 2.0. In addition, a smooth servo/regulatory performance combination is obtained by forcing both closed-loop transfer functions to perform as closely as possible to non-oscillatory dynamic targets. A unified set of controller tuning equations is provided for FOPDT and SOPDT models with normalized dead-times from 0.1 to 2.0 that guarantees the achievement of the design robustness level. The robustness of the control system is analyzed as well as the robustness–fragility and performance–fragility of the optimized controllers. Comparative examples show the effectiveness of the proposed tuning method. The exact achievement of the control system robustness target for all the controlled process models considered (first- and second-order) is one of the distinctive characteristics of the proposed model reference robust tuning (MoReRT) method.     

DC Thruster Controller Implementation with Integral Anti-wind up Compensator for Underwater ROV

This paper presents the implementation and experimental results of different conventional position control schemes for positioning an experimental model, the THETIS Underwater Remotely Operated Vehicle (UROV). To achieve minimum response time and in order to avoid the so-called Integral Wind-up phenomenon, Proportional-Integral (PI) plus integral antiwind-up compensation is used. Hardware implementation of the design is described and experimental results of a digital position control system over one direction using two dc thrusters fed by four quadrant (PWM-Driven) transistor choppers are given. All control algorithms are implemented using a TI's Digital Signal Processor (DSP). The actual position and orientation of the vehicle in a 3-D space is derived through a combination of an ultrasonic scanning system, a direction gyrocompass, and a pressure depth sensor. The vehicle's use at the present stage of development is to perform water pollution measurements.     

Measurement noise filtering for PID controllers

Measurement noise can generate undesired control activity resulting in wear of actuators and reduced performance. The effects of measurement noise can be alleviated by filtering the measurement signal. The design of the filter is then a trade-off; heavy filtering reduces the undesired control activity but performance is degraded. In this paper we discuss the trade-offs for PID control. Based on the insight gained we introduce two quantities that characterize the effect of measurement noise the SDU, which is a measure of noise activity analog to the IAE commonly used to characterize load disturbance response, and the noise gain k_n, which tells how fluctuations in the filtered measurement signal are reflected in variations of the control signal. Simple rules for choosing the filter time constant for PI and PID controllers are also given. The results are illustrated by simulations and lab experiments.     

A mixed PI/VI design method for nonlinear H∞ Control

This paper proposes a new mixed policy iteration and value iteration (PI/VI) design method for nonlinear H_∞ control based on the theories of polynomial optimization and Lasserre's hierarchy. The design of a mixed PI/VI controller can be carried out in four steps: firstly, initialize design parameters and expand nonlinear system matrices; secondly, obtain a polynomial matrix inequality for policy improvement; thirdly, obtain the Lasserre's hierarchy of a global polynomial optimization problem for value improvement; fourthly, perform the mixed PI/VI algorithm to approximate the optimal nonlinear H_∞ control law. The novelty of this work lies in that the problem of designing a nonlinear H_∞ controller is translated into a polynomial global optimization problem, which can be solved by Lasserre's hierarchy directly, and then, the mixed PI/VI algorithm is presented to approximate the optimal nonlinear H_∞ control law by updating global optimizers iteratively. The main results of this paper consist of the mixed PI/VI algorithm and the related three theorems, which guarantee robust stability and performance of the closed‐loop nonlinear system. Numerical simulations show that the mixed PI/VI algorithm converges very fast and achieves good robust stability and performance in transient behavior, disturbance rejection, and enlarging the domain of attraction of the close‐loop system.     

Correlation between conventional control figures of merit and the Q matrix of the quadratic cost function : Third-order plant†

In conventional control theory the techniques for achieving some or all of the desired figures of merit have been highly developed (D'Azzo and Houpis 1966). Modern control theory optimizes a system performance based upon a desired performance index, PI. The work of Rynaski and Whitbeek (1966) is extended to form the basis for the correlation between the conventional control figures of merit (M_p, t_p, t_s and w_d, and steady-state error) and the diagonal elements of the Q matrix of the quadratic PI (the off-diagonal terms being zero). This correlation is established for a third-order single-input, single-output system, enabling a system designer to optimize a system and at the same time satisfying some or all of the conventional figures of merit.     

Fuzzy predictive PI control for processes with large time delays

This paper presents the design, tuning and performance analysis of a new predictive fuzzy controller structure for higher order plants with large time delays. The designed controller consists of a fuzzy proportional-integral (PI) part and a fuzzy predictor. The fuzzy predictive PI controller combines the advantages of fuzzy control while maintaining the simplicity and robustness of a conventional PI controller. The dynamics of the prediction term are adaptive to the system's time delay. The prediction term has two parts: a fuzzy predictor that uses the system time delay as an input for calculating the prediction horizon and an exponential term that uses the prediction horizon as its positive power. The prediction term also introduces phase lead into the system which compensates for the phase lag due to the time delay in the plant, thereby stabilizing the closed-loop configuration. The performance of the proposed controller is compared with the responses of the conventional predictive PI controller, showing many advantages of the new design over its conventional counterpart.     

Comparing 2DOF PI and predictive disturbance observer based filtered PI control

This paper analyses the optimal nominal tuning of a new modification of predictive disturbance observer (PDO) based filtered PI control (PDO FPI) applied to a first order plus dead time (FOPDT) plant with exactly known parameters.The impacts of applied filters on optimal controller tuning and on achievable closed loop performance are evaluated first of all. The limits of achievable performance are compared with those of traditional two degree of freedom (2DOF) PI control, with both controllers tuned by the multiple real dominant pole method. This comparison shows the potential of PDO FPI control to improve tracking and regulatory dynamics significantly, permitting the Pareto-like servo/regulator trade-off of 2DOF PI control to be removed.Two PDO FPI tuning approaches are proposed, allowing optimal filter degree and time constants to be evaluated.The first tuning scenario considers optimization of closed loop performance expressed in terms of the Integral of the Absolute Error (IAE) weighted alternatively by the relative total variance TV₁ of the control signal. This is carried out by changing the filter order n under the constraint that a constant position of the dominant closed loop pole is maintained. This keeps the dynamics of the setpoint step responses almost unchanged. In the second tuning scenario the optimization is carried out under a constraint on constant speed of disturbance step responses.All the main results are then numerically checked for the integral first order plant with dead time by the performance portrait (PP) method.The analysis presented here shows that the new PDO FPI structure substantially enriches the spectrum of controllers applicable to simple control tasks.     

Open-loop neuro-fuzzy speed estimator applied to vector and scalar induction motor drives

Scalar and vector drives have been the cornerstones of control of industrial motors for decades. In both the elimination of mechanical speed sensor consists in a trend of modern drives. This work proposes the development of an adaptive neuro-fuzzy inference system (ANFIS) angular rotor speed estimator applied to vector and scalar drives. A multi-frequency training of ANFIS is proposed, initially for a V/f scheme and after that a vector drive with magnetizing flux oriented control is proposed. In the literature ANFIS has been commonly proposed as a speed controller in substitution of the classical PI controller of the speed control loop. This paper investigates the ANFIS as an open-loop speed estimator instead. The subtractive clustering technique was used as strategy for generating the membership functions for all the incoming signal inputs of ANFIS. This provided a better analysis of the training data set improving the comprehension of the estimator. Additionally the subtractive cluster technique allowed the training with experimental data corrupted by noise improving the estimator robustness. Simulations to evaluate the performance of the estimator considering the V/f and vector drive system were realized using the Matlab/Simulink^® software. Finally experimental results are presented to validate the ANFIS open loop estimator.     

Fractional order and BICO disturbance observers for a run-of-mine ore milling circuit

Grinding mill circuits are hard to control due to poor plant models, large external disturbances, uncertainties from internal couplings, and process variables that are difficult to measure. This paper proposes a novel fractional order disturbance observer (FO-DOB) for a run-of-mine (ROM) ore milling circuit. A fractional order low pass filter (Q-filer) is used in the DOB to offer an additional degree of freedom in tuning for set-point tracking performance and disturbance rejection performance. Another disturbance observer is introduced in which a Bode ideal cut-off (BICO) filter is used for the Q-filter. A full non-linear plant model is used for evaluation of the performance gained over the ubiquitous PI controller. The simulation results show that the FO-DOB and BICO-DOB schemes are useful additional tools for ROM ore milling circuit control implementations.     

基于D稳定域和ITAE准则的主动队列管理算法

主动队列管理(active queue management,简称AQM)是网络拥塞控制的研究热点之一,其中的关键问题是如何设计反馈控制策略.提出一种新的基于D稳定域和时间乘以误差绝对值乘积积分(integral of time-weighted absolute error,简称ITAE)性能准则的比例-积分-微分(proportional-integral-differential,简称PID)优化设计方法(简称DITAE-PID),并用于AQM控制器的设计,控制闭环系统的理想动态性能.首先在复平面上设定一组理想的D稳定域,然后以ITAE为目标函数,通过数值优化算法求出控制器的参数,使得闭环系统的所有特征根都在D稳定域内,以降低排队延时,提高有效吞吐量.对比仿真实验结果表明,该算法能够预先探测和控制拥塞,有较好的鲁棒性,链路利用率更高,丢包率更小,平均队列长度更趋于期望值,同时,趋于期望队列长度的时间更短,其综合性能明显优于典型的随机早期探测(random early detection,简称RED)和比例-积分(proportional-integral,简称PI)算法.     

Design and experiment of an electromagnetic levitation system for a micro mirror

In this paper, the design and characterization of a contactless electromagnetic levitation and electrostatic driven microsystem is presented, which has applications for example for large scale angle rotation micro mirrors. The proposed design can levitate a fabricated aluminum micro rotor which can incorporate a mirror and control it to rotate around the vertical axis within the range of ± 180°, which enlarges the scanning angle dramatically compared with conventional torsion micro mirrors. The rotation angle of the micro rotor is detected by the change of capacitance and controlled by the electrostatic force produced by variable capacitors. The levitation of the micro rotor is realized by utilizing electromagnetic inductions. The rotation is achieved through electrostatic forces generated by a digital controller. The hybrid system design for a micro rotor, combining magnetic and electrostatic forces is introduced. The digital control strategy is based on a PID controller with bias voltage. The detection interface circuit, which is based on frequency multiplexing, is also presented in this paper. It has been experimentally shown that the proposed design can levitate a 1.65 mm radius and 8 µm thickness aluminum micro rotor to 100 µm height with 20 MHz frequency and 0.5A p-p input current. Square and slope wave input experiments were carried out. The experimental results show that the control principal is in good agreement with the simulation models and this applies as well to the time-response performance and stability.

     

Nonlinear model predictive control of a reactive distillation column

This paper considers the application of nonlinear model predictive control (NLMPC) to a highly nonlinear reactive distillation column. NLMPC was applied as a nonlinear programming problem using orthogonal collocation on finite elements to approximate the ODEs that constitute the model equations for the reactive distillation column. Diagonal PI controls were used to identify that the [L/D,V] and the [L/D,V/B] configurations performed best. NLMPC was applied using the [L/D,V] configuration and found to provide a factor of 2–3 better performance than the corresponding PI controller. The effect of process/model mismatch on the performance of the NLMPC controller was also evaluated.