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Extensive efforts have been conducted on the elimination of position sensors in servomotor control. The purpose of this paper is to aim at estimating the servomotor speed without using position sensors and the knowledge of its parameters by artificial neural networks (ANNs).

A neural speed observer based on the Elman neural network (NN) structure takes only motor voltages and currents as inputs.

After offline NNs training, the observer is incorporated into a DSP-based drive and sensorless control is achieved.

Future work will consider to reduce the computation time for NNs training and to adaptively tune parameters on line.

The experimental results of the proposed method are presented to show the effectiveness.

This paper achieves sensorless servomotor control by ANNs which are seldom studied.

To meet the need of reducing the cost of industrial systems, sensorless control applications on electrical machines are increasing day by day. This paper aims to improve the performance of the sensorless induction motor control system. To do this, the speed observer is designed based on the combination of the sliding mode and the fractional order integral.

Super-twisting sliding mode (STSM) and Grünwald–Letnikov approach are used on the proposed observer. The stability of the proposed observer is verified by using Lyapunov method. Then, the observer coefficients are optimized for minimizing the steady-state error and chattering amplitude. The optimum coefficients (c₁, c₂, k_i and λ) are obtained by using response surface method. To verify the effectiveness of proposed observer, a large number of experiments are performed for different operation conditions, such as different speeds (500, 1,000 and 1,500 rpm) and loads (100 and 50 per cent loads). Parameter uncertainties (rotor inertia J and friction factor F) are tested to prove the robustness of the proposed method. All these operation conditions are applied for both proportional integral (PI) and fractional order STSM (FOSTSM) observers and their performances are compared.

The observer model is tested with optimum coefficients to validate the proposed observer effectiveness. At the beginning, the motor is started without load. When it reaches reference speed, the motor is loaded. Estimated speed and actual speed trends are compared. The results are presented in tables and figures. As a result, the FOSTSM observer has less steady-state error than the PI observer for all operation conditions. However, chattering amplitudes are lower in some operation conditions. In addition, the proposed observer shows more robustness against the parameter changes than the PI observer.

The proposed FOSTSM observer can be applied easily for industrial variable speed drive systems which are using induction motor to improve the performance and stability.

The robustness of the STSM and the memory-intensive structure of the fractional order integral are combined to form a robust and flexible observer. This paper grants the lower steady-state error and chattering amplitude for sensorless speed control of the induction motor in different speed and load operation conditions. In addition, the proposed observer shows high robustness against the parameter uncertainties.

This paper aims to address the spacecraft attitude regulation problem in the presence of extrinsic disturbances and actuator faults.

Based on adaptive backstepping design technique, a new concise adaptive dual-mode control scheme is proposed, which can either use the fault information detected by fault diagnosis mechanisms or switch to the fault-unknown mode when the fault diagnosis information is non-existent for control signal generation. These two modes share an adaptive mechanism that reduces the complexity of the algorithm.

The new fault-tolerant attitude control algorithm can accommodate both modes with and without fault diagnosis mechanisms.

The proposed algorithm in this paper can be applied to both cases when the attitude control system is equipped with or without fault diagnosis capability. This also enhances the robustness of attitude control algorithm. This study performs numerical simulations and verifies that the algorithm could effectively adapt to both modes.

Schema therapy has gone through various adaptations, including the identification of various schema modes. The purpose of this paper is to suggest that there may be a further dissociative mode, the “frozen child” mode, which is active for some patients, particularly those that have experienced extreme childhood trauma.

The paper is participant observer case study which is based on the personal reflections of a forensic patient who completed a treatment programme which includes schema therapy.

The proposed mode, “frozen child”, is supported by theoretical indicators in the literature. It is proposed that patients develop this mode as a protective strategy and that unless recognised and worked with, can prevent successful completion of therapy.

Based on a single case study, this concept is presented as a hypothesis that requires validation as the use of the case study makes generalisation difficult.

It is suggested that if validated, this may be one of the blocks therapists have previously encountered that has led to the view that people with severe personality disorder are “untreatable”. Suggestions are made as to how patients with this mode, if validated, can be treated with recommendations as to the most appropriate processes to potentiate such therapy.

The suggestion of this potential “new schema mode” is based on service user initiative, arising from a collaborative enterprise between service user and clinician, as recommended in recent government policies.

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.

In recent years, use of sensorless control methods for electrical motor-based variable speed drive systems has been increasing rapidly to compensate the increasing costs in industrial systems. Also, use of induction motors is popular for a long time to decrease the cost of these industrial systems. This study aims to design an effective controller to improve the sensorless speed control performance of induction motor. To achieve this, a conformable fractional order proportional integral (CFOPI) controller is designed.

The system is modeled based on small signal analysis by using the input–output data, experimentally. To do this, system identification toolbox of Matlab is used. The proposed controller is established on conformable fractional integral approach proposed by Khalil et al. (2014). CFOPI controller coefficients are optimized using particle swarm optimization method on the created small signal-based simulation model of the system to minimize the integral time absolute error. To prove the success of the proposed method, a traditional fractional order proportional integral (TFOPI) controller is tested under the same experimental system with the CFOPI controller.

TFOPI and CFOPI controllers are tested with the optimum parameters. Reference and actual speed trends are obtained for both methods. In induction motor start-up test, settling-times are measured as 8.73 and 8.44 s and steady-state oscillations are 2.66% and 0% (almost) for TFOPI and CFOPI controllers, respectively. In variable referenced speed tracking test, CFOPI performs well at all speed levels, while TFOPI fails to reach the reference speed at most speed levels.

Proposed CFOPI control method can be easily implemented in industrial systems, thanks to its simple algorithm. digital signal peripheral interface controller (dsPIC) based driver circuit with designed CFOPI controller used in this study can be applied directly to industrial systems such as elevators, conveyors, cranes and drills. Moreover, it can improve the performance of induction motor-based variable speed drive systems.

The proposed method provides robust performance for induction motor used in control systems. Additionally, it does this by using less complex algorithm written on the processors according to the traditional fractional order controllers.