A self-tuning controller for switched reluctance motors

A self-tuning controller for switched reluctance motors is presented, A torque ripple minimizing controller is implemented with online system identification and adaptation technique. The controller uses a nonlinear model of the machine that is updated online using a recursive identification algorithm. The real-time approach improves the overall robustness of the system. Experimental results are presented to validate the self-tuning algorithm     

A fuzzy self-tuning PI controller for HVDC links

This paper introduces a fuzzy logic-based tuning of the controller parameters for the rectifier side current regulator and inverter side gamma controller in a high voltage direct current (HVDC) power system. A typical point-to-point system has been taken with the detailed representation of converters, transmission links transformers and filters. The current error (and its derivative) and the gamma error (and its derivative) are used as the principal signals to adjust the proportional and integral gains of the rectifier pole controller and the inverter gamma controller, respectively, for optimum HVDC power system performance under various normal and abnormal conditions. Finally, a comparative study has been performed with and without tuning, to prove the superiority of the proposed control scheme     

A stable self-organizing fuzzy controller for robotic motioncontrol

It is well known that robotic manipulators are highly nonlinear coupling dynamic systems. It is difficult to establish an appropriate mathematical model for the design of a model-based controller. Although fuzzy logic control has a model-free feature, it still needs time-consuming work for the rules bank and fuzzy parameters adjustment. In this paper, a stable self-organizing fuzzy controller (SOFC) is proposed to manipulate the motion trajectory of a 5-degrees-of-freedom robot. This approach has a learning ability for responding to the time-varying characteristic of a robot. Its control rules bank can be established and modified continuously by online learning with zero initial fuzzy rules. In addition, this control strategy has effectively improved the stability problem of a previous SOFC. The experimental results show that this intelligent controller has a stable learning ability and good motion control capability     

Automatic disturbances rejection controller for precise motion control of permanent-magnet synchronous motors

A highly robust automatic disturbances rejection controller (ADRC) is developed to implement high-precision motion control of permanent-magnet synchronous motors. The proposed ADRC consists of a tracking differentiator (TD) in the feedforward path, an extended state observer (ESO), and a nonlinear proportional derivative control in the feedback path. The TD solves the difficulties posed by low-order reference trajectories which are quantized at the sensor resolution, and the ESO provides the estimate of the unmeasured system's state and the real action of the unknown disturbances only based on a measurement output of the system. Simulations and experimental results show that the proposed ADRC achieves a better position response and is robust to parameter variation and load disturbance. Furthermore, the ADRC is designed directly in discrete time with a simple structure and fast computation, which make it widely applicable to all other types of derives.     

A dual-rate self-tuning pole-placement controller

A dual-rate self-tuning pole-placement controller is proposed. It allows the use of a larger sampling interval for on-line parameter estimation and a smaller sampling interval for control. The conversion of model parameters from one sampling interval to another can be readily performed using a pole-zero mapping technique. The major problem encountered is that the process zeros at the slow sampling rate cannot be estimated accurately by using input-output data obtained at the fast sampling rate. The proposed solution of fixing the zeros at z=-1 while keeping the DC gain the same is supported by analysis of the Nyquist plot. The main merits of the dual-rate self-tuning control system are in the simultaneous achievement of robust estimation and reduced computation load and in improved performance in the regulation of deterministic and stochastic load disturbances. Its performance is substantiated by digital simulation and experiments on a pilot plant     

Experimental evaluation of a self-tuning controller

A self-tuning control (STC) scheme is examined in real time by comparing its performance with that of two other control schemes. Experimental results show that the controller is superior to a well-known conventional self-tuning controller and a proportional-plus-integral (PI) self-tuning controller whose parameters are selected on the basis of a pole assignment method. The control scheme can be extended to multi-input multi-output systems     

Neural-network-based maximum-power-point tracking of coupled-inductor interleaved-boost-converter-supplied PV system using fuzzy controller

The photovoltaic (PV) generator exhibits a nonlinear V-I characteristic and its maximum power (MP) point varies with solar insolation. In this paper, a feedforward MP-point tracking scheme is developed for the coupled-inductor interleaved-boost-converter-fed PV system using a fuzzy controller. The proposed converter has lower switch current stress and improved efficiency over the noncoupled converter system. For a given solar insolation, the tracking algorithm changes the duty ratio of the converter such that the solar cell array voltage equals the voltage corresponding to the MP point. This is done by the feedforward loop, which generates an error signal by comparing the instantaneous array voltage and reference voltage corresponding to the MP point. Depending on the error and change of error signals, the fuzzy controller generates a control signal for the pulsewidth-modulation generator which in turn adjusts the duty ratio of the converter. The reference voltage corresponding to the MP point for the feedforward loop is obtained by an offline trained neural network. Experimental data are used for offline training of the neural network, which employs a backpropagation algorithm. The proposed peak power tracking effectiveness is demonstrated through simulation and experimental results. Tracking performance of the proposed controller is also compared with the conventional proportional-plus-integral-controller-based system. These studies reveal that the fuzzy controller results in better tracking performance.     

Adaptive sliding controller with self-tuning fuzzy compensation for vehicle suspension control

Since the hydraulic actuating suspension system has nonlinear and time-varying behavior, it is difficult to establish an accurate dynamic model for a model-based sliding mode control design. Here, a novel model-free adaptive sliding controller is proposed to suppress the position oscillation of the sprung mass in response to road surface variation. This control strategy employs the functional approximation technique to establish the unknown function for releasing the model-based requirement. In addition, a fuzzy scheme with online learning ability is introduced to compensate the functional approximation error for improving the control performance and reducing the implementation difficulty. The important advantages of this approach are to achieve the sliding mode controller design without the system dynamic model requirement and release the trial-and-error work of selecting approximation function. The update laws for the coefficients of the Fourier series functions and the fuzzy tuning parameters are derived from a Lyapunov function to guarantee the control system stability. The experimental results show that the proposed control scheme effectively suppresses the oscillation amplitude of the vehicle sprung mass corresponding to the road surface variation and external uncertainties, and the control performance is better than that of a traditional model-based sliding mode controller.     

A self-tuning controller for queuing delay regulation in TCP/AQM networks

Telecommunication Systems - AQM router aims primarily to control the network congestion through marking/dropping packets which are used as congestion feedback in traffic sources to balance their...     

New antiwindup PI controller for variable-speed motor drives

The windup phenomenon appears and results in performance degradation when the proportional-integral (PI) controller output is saturated. A new antiwindup PI controller is proposed to improve the control performance of variable-speed motor drives, and it is experimentally applied to the speed control of a vector-controlled induction motor driven by a pulsewidth modulated (PWM) voltage-source inverter (VSI). The integral state is separately controlled, corresponding to whether the PI controller output is saturated or not. The experimental results show that the speed response has much improved performance, such as small overshoot and fast settling time, over the conventional antiwindup technique. Although the operating speed command is changed, similar control performance can be obtained by using the PI gains selected in the linear region     

Universal low cost controller for electric motors with programmablecharacteristic curves

The realization of a universal low-cost controller for electric motors in CMOS technology with programmable characteristic curves is presented. With regard to the required chip area of 2.7 mm² in a 1.6 μm, 40 nm technology, the general advantage in comparison to microcontroller-based solutions lies in the low factory costs. The analog dc power supply is generated directly from the 230 V ac power line. An on-chip functional unit controls the firing current for the off-chip motor driving triac. Features of this functional unit are torque control and overload protection, firing, and post firing control. A new method was used to implement programmable multidimensional characteristic curves which are temperature and technology insensitive. In the actual controller application for a drilling machine motor, the mask-programmed curve shapes have been generated with the help of fuzzy algorithms. An impression of the reproducibility of multidimensional characteristic curves in manufacturing, as well as the accuracy of their precalculation, is given by introducing simulated and measured statistics of the actual design     

Position-sensorless control of surface-mount permanent-magnet AC(PMAC) motors at low speeds

A position-sensorless field-oriented control scheme for a surface-mount permanent-magnet AC (PMAC) motor is presented. A digital signal processor is used to implement the sensorless scheme. The PMAC stator is wound like that of a conventional three-phase induction motor. The coils of the motor are all brought out and it is possible to connect the motor in different configurations. Taps are also provided which are used for voltage measurements. By measuring the tap voltages, absolute position of the PMAC motor is estimated. The estimated position information is independent of the stator resistance, thus, this scheme is even applicable at low speeds. Results are presented to show the effectiveness of the new sensorless scheme     

Tuning rules for the PI gains of field-oriented controllers ofinduction motors

The authors have previously shown that field-oriented controllers for induction motors preserve stability under a wide range of variations of the motor and controller parameters. However, as is well known, the transient performance critically depends on the tuning of the gains of the proportional-integral (PI) velocity loop, a task which is rendered difficult because of the high uncertainty on the rotor resistance. The problem we address in this paper is how to develop an offline procedure to choose these gains. The main contribution of our work is a very simple frequency-domain test that, for each setting of the PI gains, evaluates the maximum range of the relative rotor resistance estimate for which global stability is guaranteed. In this way, we provide a quantitative estimate of the performance of the PI controller. The stability result may also be used in a dual manner, fixing now the range of the rotor resistance, and estimating an admissible interval for the PI gains that preserves global stability. Instrumental for our study is the exploitation of an energy dissipation (strict passivity) property of the system     

On comparison of hybrid fuzzy PI plus conventional D controller versus fuzzy PI+D controller

This letter points out that a comparison given in an earlier paper by Er and Sun (ibid. vol. 48, pp. 1109-1117, 2001) is incorrect. The fuzzy PI+D controller designed by Misir et al. ( Fuzzy Sets Syst. vol. 79, pp. 297-314, 1996) is overall better than the hybrid fuzzy PI plus conventional D controller designed by Er and Sun.     

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     

Giant magnetostrictive clamping mechanism for heavy-load and precise positioning linear inchworm motors

This paper focuses on the development of a novel clamping principle and the mechanism that may be used to realize a linear motor capable of performing not only large thrust but also secure movement with high blocked clamping force. To verify this principle, a clamping prototype (size: ?32 × 130 mm) is constructed and tested. It generates a clamping force of 1050 N with an initial experimental set-up, and, a clamping force up to 1525 N with a modified set-up employing a hydro-press bench clamp. The theoretical and numerical analyses are carried out and suggest that the mechanism may generate a clamping force up to 2148 N with an adequate rigid guide-way.     

PID参数自整定在恒压供水控制器中的应用

传统的恒压供水控制器通常采用PID调节器,其算法难以编程实现,并且调试困难.将自整定PID调节器应用到恒压供水控制器中,这样,用户就不必调整PID参数,从而大大方便了现场调试,并保证了系统的长期稳定性.     

高精度DPSS倍频激光器数字温控系统的设计

温度影响着典型的小型化半导体泵浦固态（DPSS）倍频激光器输出模式和激光功率。为获得稳定的倍频激光横模和输出功率,应用温度传感器、ADC和DAC集成的微处理器芯片,以及半导体致冷器（TEC）,设计开发了高精度DPSS倍频激光器数字温控系统。其结构紧凑、使用方便,温度不稳定度可达±0．05℃。通过改进PID算法的程序控制,避免了积分饱和,同时也加快了系统恒温的速度。     

GA-based fuzzy PI/PD controller for automotive active suspensionsystem

A genetic-algorithm (GA)-based fuzzy proportional-plus-integral-proportional-plus-derivative (PI/PD) controller is proposed for an automotive active suspension system (AASS). The fuzzy PI- and PD-type controllers are combined to cope with the different road conditions. By using the merit of GAs, the optimal decision-making rules for both types of controllers are constructed. The real-time simulation results demonstrate that the fusion of GAs and fuzzy controller for an AASS can provide passengers much more ride comfort     

模糊参数自整定PID控制器在船载雷达伺服系统中的应用

针对传统方法难以整定船载雷达伺服系统PID参数的问题,将模糊参数自整定PID控制技术应用到伺服系统位置回路中,通过仿真实验表明该方法可以不依赖系统的数学模型,而根据输入输出关系对PID参数进行在线调整,自动调整环路带宽,调高系统的动态性能和稳态性能,具有很强的鲁棒性和自适应性。