Search results

Accurate glide path tracking is vital to the automatic carrier landing task of unmanned aerial vehicle (UAV). The purpose of this paper is to develop a reliable flight controller that can simultaneously deal with external disturbance, structure fault and actuator fault.

The automatic carrier landing task is resolved into the glide path tracking problem and attitude tracking problem. The disturbance observer-based adaptive sliding mode control scheme is proposed for system stabilization, disturbance rejection and fault tolerance.

Both the Lyapunov method and exemplary simulations can prove that the disturbance estimation error and the attitude tracking error converge in finite time in the presence of external disturbances and various faults.

The presented algorithm is testified by a UAV automatic carrier landing simulation, which shows the potential of practical usage.

The barrier function is introduced to adaptively update both the sliding mode observer gain and sliding mode controller gain, so that the sliding mode surface could converge to a predefined region without overestimation. The proposed flight controller ensures a secure carrier landing task.

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 study the issue of the three-dimensional formation coordinated control for the unmanned autonomous helicopter (UAH) by using the sliding mode disturbance observer. Under the designed formation coordinated controller, the desired formation can be maintained and the closed-loop system stability is analyzed by using the Lyapunov theory.

Considering the unknown time-varying external 10; disturbance in formation flight of UAHs, a sliding mode disturbance observer has been employed to estimate them.

This work is supported in part by the National Natural Science Foundation of China under Grant 61803207, and in part by the Fundamental Research Funds for the Central Universities under Grant LGZD201806.

A sliding mode disturbance observer has been designed to estimate the unknown time-varying external disturbance in formation flight of UAHs. Aiming at the leading UAH maneuver in three-dimensional space during the formation flight progress, the formation coordinated controller has been proposed based on the output of the disturbance observer to maintain the formation.

This paper aims to investigate the problem of attitude control for a horizontal takeoff and horizontal landing reusable launch vehicle.

In this paper, a predefined-time attitude tracking controller is presented for a horizontal takeoff and horizontal landing reusable launch vehicle (HTHLRLV). Firstly, the attitude tracking error dynamics model of the HTHLRLV is developed. Subsequently, a novel sliding mode surface is designed with predefined-time stability. Furthermore, by using the proposed sliding mode surface, a predefined-time controller is derived. To compensate the external disturbances or model uncertainties, a fixed-time disturbance observer is developed, and its convergence time can be defined as a prior control parameter. Finally, the stability of the proposed sliding mode surface and the controller can be proved by the Lyapunov theory.

In contrast to other fixed-time methods, this controller only requires three control parameters, and the convergence time can be predefined instead of being estimated. The simulation results also demonstrate the effectiveness of the proposed controller.

A novel predefined-time attitude tracking controller is developed based on the predefined-time sliding mode surface (SMS) and fixed-time disturbance observer (FxTDO). The convergence time of the system can be selected as a prior control parameter for SMS and FxTDO.

The purpose of this paper is to investigate the stabilization of unstable periodic orbits of Chua’s system using adaptive fuzzy sliding mode controllers with moving surface.

For this aim, the sliding mode controller and fuzzy systems are combined to achieve the stabilization. Then, the authors propose a moving sliding surface to improve robustness against uncertainties during the reaching phase, parameter variations and extraneous disturbances.

Afterward, the authors design a sliding observer to estimate the unmeasurable states which are used in the previously designed controller.

Numerical results are provided to show the effectiveness and robustness of the proposed method.

The purpose of this paper is to design a hybrid robust tracking controller based on an improved radial basis function artificial neural network (IRBFANN) and a novel extended-state observer for a quadrotor system with various model and parametric uncertainties and external disturbances to enhance the resiliency of the control system.

An IRBFANN is introduced as an adaptive compensator tool for model and parametric uncertainties in the control algorithm of non-singular rapid terminal sliding-mode control (NRTSMC). An exact-time extended state observer (ETESO) augmented with NRTSMC is designed to estimate the unknown exogenous disturbances and ensure fast states convergence while overcoming the singularity issue. The novelty of this work lies in the online updating of weight parameters of the RBFANN algorithm by using a new idea of incorporating an exponential sliding-mode effect, which makes a remarkable effort to make the control protocol adaptive to uncertain model parameters. A comparison of the proposed scheme with other conventional schemes shows its much better performance in the presence of parametric uncertainties and exogenous disturbances.

The investigated control strategy presents a robust adaptive law based on IRBFANN with a fast convergence rate and improved estimation accuracy via a novel ETESO.

To enhance the safety level and ensure stable flight operations by the quadrotor in the presence of high-order complex disturbances and uncertain environments, it is imperative to devise a robust control law.

A new idea of incorporating an exponential sliding-mode effect instead of conventional approaches in the algorithm of the RBFANN is used, which makes the control law resistant to model and parametric uncertainties. The ETESO provides rapid and accurate disturbance estimation results and updates the control law to overcome the performance degradation caused by the disturbances. Simulation results depict the effectiveness of the proposed control strategy.

The purpose of the control method proposed in this paper is to address the problem of the poor anti-interference of the suspension winding current in the traditional bearingless induction motor (BL-IM) direct suspension force control process.

A model predictive direct suspension force control of a BL-IM based on sliding mode observer is proposed in this paper. The model predictive control (MPC) is introduced to the traditional direct suspension force control to improve the anti-interference of the suspension current. A sliding mode flux linkage observer is designed and applied to the MPC system, which reduces the error of the parameter observation and improves the robustness of the system. The strategy is designed and implemented in the MATLAB/Simulink and the two-level AC speed regulation platform.

The simulation and experimental results show that the performance of the BL-IM under the control method proposed in this paper is better than that under the traditional direct suspension force control, and the suspension performance of the motor and the anti-interference of the control system are improved.

This study helps to improve the suspension performance of the motor and the anti-interference of the control system.

The aim of this research paper is to design a disturbance observer (DO)-based robust adaptive tracking control of uncertain nonlinear system subject to unknown nonlinear disturbance.

To achieve desired control objectives, i.e. nonlinear trajectory tracking and disturbance attenuation, firstly, a control scheme is designed based on the adaptive criteria integrated in sliding mode control (SMC). In the second step, the disturbance estimation criterion is designed followed by patching with the controller obtained in the first step. Following the control development, using the Lyapunov candidate function, the stability criterion is ensured by designing appropriate adaptive gains.

In this paper, a robust adaptive nonlinear tracking method is presented. The findings includes the design of adaptive gains for the control parameters involved in the robust SMC technique, i.e. adaptive criterion is designed for the switching gain as well as for the gain used in sliding mode surface. Furthermore, a disturbance estimation criterion is developed to attenuate nonlinear disturbances with variable frequency and magnitude. Finally, the disturbance estimation scheme is combined with the control technique to obtain DO-based control (DOBC) algorithm.

Sliding mode control is a powerful robust control method. And, combining it with the DO achieves the control objectives of plants subject to disturbances and uncertainties. However, usually the uncertainties and disturbances are unknown and time varying. Thus, during practical implementation, designing the standard SMC is a challenging task due to the constant gains involved in the control design. Hence, it is important to have a criterion which adapts to the varying dynamics of plants due to the uncertainties and disturbances for achieving practical implementation of the control system.

Sliding mode control has been widely used for achieving the desired control objectives and robustness in the close-loop nonlinear systems. Besides, the SMC technique has been combined with the DOs as well. However, mostly the ideal conditions were considered during these developments, which required the control gains to be designed simply by manual tuning appropriately. However, by considering the real-time dynamics, uncertainties and disturbances, the constant control gain criteria can fail. Furthermore, due to external and internal disturbances, the model plant can vary with time. Thus, it is important to design the adaptive criteria for the control gains in DOBC schemes.

The objective of this research is to investigate various neural network (NN) observer techniques for sensors fault identification and diagnosis of nonlinear system in consideration of numerous faults, failures, uncertainties and disturbances. For the importunity of increasing the faults diagnosis and reconstruction preciseness, a new technique is used for modifying the weight parameters of NNs without enhancement of computational complexities.

Various techniques such as adaptive radial basis functions (ARBF), conventional radial basis functions, adaptive multi-layer perceptron, conventional multi-layer perceptron and extended state observer are presented. For increasing the fault detection preciseness, a new technique is used for updating the weight parameters of radial basis functions and multi-layer perceptron (MLP) without enhancement of computational complexities. Lyapunov stability theory and sliding-mode surface concepts are used for the weight-updating parameters. Based on the combination of these two concepts, the weight parameters of NNs are updated adaptively. The key purpose of utilization of adaptive weight is to enhance the detection of faults with high accuracy. Because of the online adaptation, the ARBF can detect various kinds of faults and failures such as simultaneous, incipient, intermittent and abrupt faults effectively. Results depict that the suggested algorithm (ARBF) demonstrates more confrontation to unknown disturbances, faults and system dynamics compared with other investigated techniques and techniques used in the literature. The proposed algorithms are investigated by the utilization of quadrotor unmanned aerial vehicle dynamics, which authenticate the efficiency of the suggested algorithm.

The proposed Lyapunov function theory and sliding-mode surface-based strategy are studied, which shows more efficiency to unknown faults, failures, uncertainties and disturbances compared with conventional approaches as well as techniques used in the literature.

For improvement of the system safety and for avoiding failure and damage, the rapid fault detection and isolation has a great significance; the proposed approaches in this research work guarantee the detection and reconstruction of unknown faults, which has a great significance for practical life.

In this research, two strategies such Lyapunov function theory and sliding-mode surface concept are used in combination for tuning the weight parameters of NNs adaptively. The main purpose of these strategies is the fault diagnosis and reconstruction with high accuracy in terms of shape as well as the magnitude of unknown faults. Results depict that the proposed strategy is more effective compared with techniques used in the literature.

The purpose of this paper is to obtain an accurate and robust estimation method of the rotor flux and speed for the sensorless induction motor (IM) drive with magnetizing reactance variations.

The sensorless IM drive with sliding mode flux and speed observer (SMO) is presented. Proposed estimation algorithm is extended with the additional magnetizing reactance estimator based on the magnetizing characteristic of the IM. The dynamical and steady‐state properties of the drive system in the low‐speed and in the field‐weakening regions are tested. The simulation results are verified by experimental tests, over the wide range of motor speed and drive parameter changes.

It is shown that the sensorless induction motor drive can work stable in wide speed range using the Sliding‐Mode Observer with additional magnetizing reactance estimator.

The investigation looked mainly at the speed estimation methodology with additional motor parameter estimator.

The proposed SMO can be easily implemented on digital signal processors. The implementation was tested in an experimental setup with DS1103 card. The fixed‐point realisation needs to be developed to obtain the practical application in the industrial drive systems.

The SMO with an additional magnetizing reactance estimator based on magnetizing characteristic of the IM is tested. This method of the speed and flux reconstruction can be applied in different electrical drives working in wide speed range, including very low‐speed region and field‐weakening region, too. The proposed solution is not sensitive to magnetizing reactance variations and is simple in practical implementation in the real‐time system.