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The purpose of this study is to improve the control performance of wind energy conversion systems (WECSs) by proposing a new sensorless, robust control strategy based on a Smith predictor active disturbance rejection control (SP-ADRC) associated with a speed/position estimator.

The estimator consists of a sliding mode observer (SMO) in combination with a phase-locked loop (PLL) to estimate the permanent magnet synchronous generator (PMSG) rotor position and speed. At the same time, the SP-ADRC is applied to the speed control loop of the variable-speed WECS control system to adapt strongly to dynamic characteristics under parameter uncertainties and disturbances.

Numerical simulations are conducted to evaluate the speed tracking performances under various wind speed profiles. The results show that the proposed sensorless speed control improves the accuracy of rotor speed and position estimation and provides better power tracking performance than a regular ADRC controller under fast wind speed variations.

This paper offers a new approach for designing sensorless, robust control for PMSG-based WECSs.

A new sensorless, robust control is proposed to improve the stability and tracking performance of PMSG-based WECSs. The SP-ADRC control attenuates the effects of parameter uncertainties and disturbances and eliminates the time-delay impact. The sensorless control design based on SMO and PLL improves the accuracy of rotor speed estimation and reduces the chattering problem of traditional SMO. The obtained results support the theoretical findings.

The purpose of this paper is to present a fixed‐point implementation of a complete direct torque control (DTC) algorithm connected with a rotor speed estimation algorithm for the induction motor drive, using field‐programmable gate array (FPGA).

The parallel processing approach is described, which requires a decomposition of the control and estimation algorithms for the converter‐fed induction motor to several tasks, realised in parallel. The advanced data processing techniques are described, like PIPELINE technique for data streams design, coordinate rotation digital computer algorithm for transformation of stator flux vector components from Cartesian to polar coordinates. Moreover, the method for the qualitative analysis of the full‐order state observer's sensitivity to the variations of the induction motor equivalent circuit parameters is presented.

It is shown that the developed FPGA‐based DTC structure enables designing an efficient application for the induction motor control. Owing to the high‐processing frequency, the digital FPGA‐based DTC application is similar in its features to the analogue realisation based on the comparators. Yet all the advantages of the digital structure, i.e. high flexibility, parameterization capability, etc. remain unchanged. Furthermore, FPGA is hardware realisation of a digital data processing algorithm; hence the reliability of the control system is improved.

The investigations are performed in the developing prototype setup, based on PXI‐1042 Industrial PC equipped with Xilinx Virtex‐II FPGA matrix, programmed with LabVIEW.

The experimental tests of the FPGA‐based implementation of the whole control structure of the sensorless DTC drive system are demonstrated. It is also shown, that the full‐order state observer with the speed adaptation loop is significantly sensitive to motor parameter variations in the low‐speed region, which must be taken into account while designing the adaptation algorithm for speed estimation in real application.

The paper's value lies in the overall, FPGA‐based design of the speed sensorless DTC structure for the induction motor including motor speed, torque and stator flux control loops, stator flux and rotor speed estimation.

To propose and adaptive nonlinear controller for adjustable speed sensorless induction motor drive, using a novel adaptive rotor flux observer. The adaptive flux observer scheme in this paper provides the simultaneous estimation of the rotor speed, rotor resistance and stator resistance.

The IM rotor speed and rotor flux controllers are designed based on combination of input‐output feedback linearizing, linear optimal feedback control and sliding‐mode (SM) control methods. In addition a novel adaptive rotor flux observer is designed based on Lyapunov theory. The proposed control method is tested by simulation and experimental results.

The composite rotor speed and rotor flux observer in combination with adaptive rotor flux scheme guarantees a perfect speed, torque and flux tracking control for the IM sensorless drive.

The proposed control method has a drawback in the IM low speed operating region. Additional research may be able to solve this problem as well as should analyze the sensitivity of the IM drive system performance with respect to variation of the system controller and adaptive flux observer gains. In addition, this research should also analyze the influence of sampling rate, truncation errors, measurement noise, simplifying model assumption and magnetic saturation.

The proposed control method can be used for adaptive and robust control of the IM drive where an optimal efficiency is desired subject to the variable load torque demand.

Based on Lyapunov theory, a novel adaptive rotor flux observer is introduced in which the rotor speed, rotor resistance and stator resistance are treated as the unknown constant parameters.

This study aims to design and implement a novel tilt integral sliding mode controller and observer for sensorless speed control of a permanent magnet synchronous motor (PMSM).

A control strategy combining the tilt integral derivative (TID) with sliding mode control (SMC) is proposed to determine the tilt integral sliding mode manifold. Using this manifold, tilt integral sliding mode controller (TISMC) and observer (TISMO) are designed. The stabilities are verified by using Lyapunov method. To prove the effectiveness and robustness of proposed methods, sensorless speed control of PMSM is performed for various operating conditions such as constant and variable speed references, load disturbance injection, parameter perturbation, whereas sensor noises are not taken into account. The performance of proposed method is compared with TID controller, proportional integral derivative controller and conventional SMO.

Simulation results demonstrate that TISMC and TISMO have better performance in all operating conditions. They are robust against parameter uncertainties and disturbances. TISM based sensorless control of PMSM is well guaranteed with superior performance.

The proposed method has not been tackled in the literature. By combining TID and SMC, novel tilt integral sliding manifold is presented and used in designing of the controller and observer. It is proven by Lyapunov method that errors converge to zero.

We use a combination of continuum and car-following models to explore the potential impact of speed-controls on (i) decreasing travel times at times of congested flow; and (ii) increasing the safety of motorway flow approaching the site of an accident.

The paper aims to overcome the shortcomings that proportional‐integral‐derivative (PID) control for unmanned robot applied to automotive test (URAT) needs a priori manual retuning, has large speed fluctuations and is hard to adjust control parameters. A novel control approach based on fuzzy neural network applied to URAT was proposed.

According to the target vehicle speed and driving command table, the multiple manipulator coordinated control model was established. After that, the displacement of throttle mechanical leg, clutch mechanical leg, brake mechanical leg and shift mechanical arm for URAT was used as input of fuzzy neural network (FNN) model, and vehicle speed was used as output of FNN model. The number of membership functions was three, and the type of that was generalized bell membership function (gbellmf). The hybrid learning algorithm which combined with back propagation algorithm and least square method was applied to train the model. The Sugeno model was selected as fuzzy reasoning model.

Experimental results demonstrated that compared with PID control method, the proposed approach can greatly improve the accuracy of vehicle speed tracking. The approach can accurately realize the vehicle speed tracking of given driving test cycle. Therefore, it can ensure the accuracy and effectiveness of automotive test results.

Future work will focus on improving the efficiency of this learning algorithm.

The paper provides effective methods for improving the accuracy of speed tracking and repeatability.

After establishing the multiple manipulator coordinated control model, this paper proposes a novel control approach based on FNN for URAT.

Bar‐tacking is a specialized sewing stitch designed to provide immense tensile strength to the garment which requires a high‐speed precision bar‐tacking sewing machine. This paper aims to present an event‐driven multi‐axis cooperative control method for a bar‐tacking sewing machine.

The control method consists of two parts: the multi‐axis cooperative control and the needle stop positioning control. The challenges include the high speed and the precision. For example, the needle must stop at a set position in milliseconds.

The presented multi‐axis cooperative control can ensure the high speed response and the precision of the cooperative control. The needle stop positioning control is based on a combination of the velocity control and the position control with velocity feed‐forward and limitation.

The bar‐tacking sewing machine requires high‐speed start and stop response and coordination of displacement and velocity only at some given points. Therefore, the conventional multi‐axis cooperative control methods are not suitable. In addition, it requires high‐speed precision control under varying loading conditions.

While there are a number of commercial textile machines available in the market, designing a smart bar‐tacking sewing machine with good speed and precision performance remains a challenge.

The bar‐tacking sewing machine requires highly accurate multi‐axes cooperative control. The presented event‐driven multi‐axis control method is effective. It has not only the required high accuracy but also the fast time response.

Sensorless interior permanent magnet in-wheel motor (IPMIWM), as an exemplar of modular automation system, has attracted considerable interests in recent years. This paper aims to investigate a novel hybrid control approach for the sensorless IPMIWM from a cyber-physical systems (CPS) perspective.

The control approach is presented based on the hybrid dynamical theory. In the standstill-low (S-L) speed, the rotor position/speed signal is estimated by the method of the high frequency (HF) voltage signal injection. The least square support vector machine (LS-SVM) is used to acquire the rotor position/speed signal in medium-high (M-H) speed operation. Hybrid automata model of the IPMIWM is established due to its hybrid dynamic characteristics in wide speed range. A hybrid state observer (HSO), including a discrete state observer (DSO) and a continuous state observer (CSO), is designed for rotor position/speed estimation of the IPMIWM.

The hardware-in-the-loop testing based on dSPACE is carried out on the test bench. Experimental investigations demonstrate the hybrid control approach can not only identify the rotor position/speed signal with a certain load but also be able to reject the load disturbance. The reliability and the effectiveness of the proposed hybrid control approach were verified.

The proposed hybrid control approach for the sensorless IPMIWM promotes the deep combination and coordination of sensorless IPMIWM drive system. It also theoretically supports and extends the development of the hybrid control of the highly integrated modular automation system.