Search results

The purpose of this study is to test the performance of the designed automatic control system based on the Linear Quadratic Regulator (LQR) and Linear Quadratic Gaussian (LQG) algorithms during landing of the helicopter on the ship deck. This paper is a further development of the series based on Topczewski et al. (2020).

The system consists of two automatic control algorithms based on LQR and the LQG. It is integrated with the ship motion prediction system based on autoregressive algorithm with parameters calculated using Burg’s method. It is assumed that the source of necessary navigation data is integrated Inertial Navigation System with Global Positioning System. Landing of the helicopter on the ship deck is performed in automatic way, based on the preselected procedure. Performance of the control system is analyzed when all necessary navigation data is available for the system and in case when one of the parameters is unavailable during performing the procedure.

In this paper, description of the designed control system developed for performing the approach and landing of the helicopter using selected procedure is presented. Helicopter dynamic model is validated using the manufacturer data and by test pilots, overview is presented. Necessary information about ship motion model is also included. Tests showing mission performance while using LQR and LQG algorithms applied to the control system are presented and analyzed, taking into account both situations when full navigation data is available/unavailable for the control system.

Results of the system performance analyses can be used for selection of the proper control methodology for prospective helicopters autopilots. Furthermore, the system can be used to analyze the mission safety when information about one of the navigation parameters is identified by the navigation system as unavailable or incorrect and therefore unavailable during landing on the ship deck.

In this paper, control system dedicated for the automatic landing of the helicopter on the ship deck, based on two different control algorithms is presented. Influence of lack of information about one of the navigation parameters on the mission performance is analyzed.

The purpose of this review paper is to address the substantial challenges of the outdated exoskeletons used for rehabilitation and further study the current advancements in this field. The shortcomings and technological developments in sensing the input signals to enable the desired motions, actuation, control and training methods are explained for further improvements in exoskeleton research.

Search platforms such as Web of Science, IEEE, Scopus and PubMed were used to collect the literature. The total number of recent articles referred to in this review paper with relevant keywords is filtered to 143.

Exoskeletons are getting smarter often with the integration of various modern tools to enhance the effectiveness of rehabilitation. The recent applications of bio signal sensing for rehabilitation to perform user-desired actions promote the development of independent exoskeleton systems. The modern concepts of artificial intelligence and machine learning enable the implementation of brain–computer interfacing (BCI) and hybrid BCIs in exoskeletons. Likewise, novel actuation techniques are necessary to overcome the significant challenges seen in conventional exoskeletons, such as the high-power requirements, poor back drivability, bulkiness and low energy efficiency. Implementation of suitable controller algorithms facilitates the instantaneous correction of actuation signals for all joints to obtain the desired motion. Furthermore, applying the traditional rehabilitation training methods is monotonous and exhausting for the user and the trainer. The incorporation of games, virtual reality (VR) and augmented reality (AR) technologies in exoskeletons has made rehabilitation training far more effective in recent times. The combination of electroencephalogram and electromyography-based hybrid BCI is desirable for signal sensing and controlling the exoskeletons based on user intentions. The challenges faced with actuation can be resolved by developing advanced power sources with minimal size and weight, easy portability, lower cost and good energy storage capacity. Implementation of novel smart materials enables a colossal scope for actuation in future exoskeleton developments. Improved versions of sliding mode control reported in the literature are suitable for robust control of nonlinear exoskeleton models. Optimizing the controller parameters with the help of evolutionary algorithms is also an effective method for exoskeleton control. The experiments using VR/AR and games for rehabilitation training yielded promising results as the performance of patients improved substantially.

Robotic exoskeleton-based rehabilitation will help to reduce the fatigue of physiotherapists. Repeated and intention-based exercise will improve the recovery of the affected part at a faster pace. Improved rehabilitation training methods like VR/AR-based technologies help in motivating the subject.

The paper describes the recent methods for signal sensing, actuation, control and rehabilitation training approaches used in developing exoskeletons. All these areas are key elements in an exoskeleton where the review papers are published very limitedly. Therefore, this paper will stand as a guide for the researchers working in this domain.

The purpose of this paper is to present the methodology that was used to perform system identification of a dynamically unstable tilt-rotor from flight test data. The method incorporated wavelet transform into the maximum likelihood principle formulation, emphasizing both time and frequency responses. Using wavelets allowed to additionally filter noise in the data, and this increased the estimation quality. This approach did not require measurement and process noise modeling in contrast to the Kalman filter usage for parameter estimation.

In the study, lateral-directional stability and control derivatives of an unstable tiltrotor in hover were estimated. This was performed by applying the maximum likelihood output error method. The estimated model response was decomposed using the Mallat pyramid and matched to wavelet coefficients obtained directly from measurements. In addition, a coherence-based weighting function was used to put more emphasis on the most reliable data. For comparison, the same set of data was used to identify a model with the same structure using the maximum likelihood principle with an incorporated Kalman filter.

It was found that maximum likelihood principle and wavelet transform allowed for estimating aerodynamic coefficients of a dynamically unstable aircraft. The estimation was performed with high accuracy.

The designed method can be used for system identification of unstable aircraft and when additional noise is present (e.g. when noise due to turbulence was observable during the flight test or higher noise levels were present in the sensors data).

The paper presents verification of a wavelet-based maximum likelihood principle output error method using flight test data.

Generally, humanoid robots usually suffer significant impact force when walking or running in a non-predefined environment that could easily damage the actuators due to high stiffness. In recent years, the utilization of passive compliant series elastic actuators (SEA) for driving humanoid's joints has proved the capability in many aspects so far. However, despite being widely applied in the biped robot research field, the stable control problem for a humanoid powered by the SEAs, especially in the walking process, is still a challenge. This paper proposes a model reference adaptive control (MRAC) combined with the back-stepping algorithm to deal with the parameter uncertainties in a humanoid's lower limb driven by the SEA system. This is an extension of our previous research (Lanh et al., 2021).

Firstly, a dynamic model of SEA is obtained. Secondly, since there are unknown and uncertain parameters in the SEA model, a Model Reference Adaptive Controller (MRAC) is employed to guarantee the robust performance of the humanoid's lower limb. Finally, an experiment is carried out to evaluate the effectiveness of the proposed controller and the SEA mechanism.

This paper proposes an effective control algorithm that can be widely applied for the humanoid-SEA system. Besides, the effect of the coefficients in the control law is analyzed to further improve the response's quality.

Even though the simulation shows good results with stable system response, the practical experiment has not been implemented to fully evaluate the quality of the controller.

The MRAC is applied to control the humanoid's lower limb and the back-stepping process is utilized to combine with an external SEA system but still maintain stabilization. The simplified model of the lower-limb system proposed in the paper is proven to be appropriate and can be taken for further research in the future.

This paper aims to study the issues of adaptive fuzzy control for a category of switched under-actuated systems with input nonlinearities and external disturbances.

A control scheme based on sliding mode surface with a hierarchical structure is introduced to enhance the responsiveness and robustness of the studied systems. An equivalent control and switching control rules are co-designed in a hierarchical sliding mode control (HSMC) framework to ensure that the system state reaches a given sliding surface and remains sliding on the surface, finally stabilizing at the equilibrium point. Besides, the input nonlinearities consist of non-symmetric saturation and dead-zone, which are estimated by an unknown bounded function and a known affine function.

Based on fuzzy logic systems and the hierarchical sliding mode control method, an adaptive fuzzy control method for uncertain switched under-actuated systems is put forward.

The “cause and effect” problems often existing in conventional backstepping designs can be prevented. Furthermore, the presented adaptive laws can eliminate the influence of external disturbances and approximation errors. Besides, in contrast to arbitrary switching strategies, the authors consider a switching rule with average dwell time, which resolves control problems that cannot be resolved with arbitrary switching signals and reduces conservatism.

Legged walking robots have numerous advantages over the wheel or tracked robots due to their strong operational ability and exposure to the complex environment. This paper aims to present details about the mechanical formation and a new conceptual elliptical trajectory generation discussed throughout the paper of the quadruped robot.

Initially, a realistic CAD model of the four-legged robot is developed in Solidwork-2019. The proposed model’s forward and inverse kinematics equations are deduced using Denavit–Hartenberg parameters. Based on geometry and kinematics, manipulability and obstacle avoidance are investigated. A method of galloping trajectory is proposed for aiming the increase of upright direction impulse, which is produced by ground reaction force at each step frequency. Furthermore, the locomotion equation of the ellipse trajectory is derived by setting transition angle polynomial of free-fall phase, stance phase and swing phase and the constraints.

Finally, a successive simulation on a 2D sagittal plane is performed to check and verify the usefulness of the proposed trajectory. Before the development of the full quadruped, a single prototype leg is generated for experimental verification of the dynamic simulations.

The proposed trajectory is novel in that it uses force tracking control, which is intended to improve the quadruped robot’s robustness and stability.

During the operation of a wet clutch, there are fluctuations in speed and torque, which have an impact on the stability of the clutch and the strength of the friction plate and the spline pair of the dual steel plate. The purpose of this study is to investigate the vibration characteristics of the wet clutch and the dynamic load characteristics of the spline pairs.

The spline pair model is established by the piecewise linear function method, and on this basis, dynamic equations considering the spline pair of dual steel plates and friction plates are established. Considering that the wet clutch has multiple spline pairs, an equivalent model of the number of teeth and the equivalent model of the tooth width were proposed, and the Runge-Kutta numerical method was used for the wet clutch for these two models.

The research results show that the equal tooth number model has greater meshing stiffness and smaller fluctuation than the constant tooth width model, which shows that increasing the meshing stiffness of the system is beneficial to reduce system fluctuation and improve system stability.

The friction plate has the system that multiple splines are independent of each other, which is relatively complicated. Therefore, an equivalent calculation is performed on multiple pairs of steel plates (friction plates) to simplify the calculation of the spline pairs.

This paper provides a theoretical basis for further dynamic characteristics analysis of wet clutch and reducing fluctuation of speed and torque.

Dynamic equation considering the spline pair of the dual steel plates and the friction plates is established to study the vibration characteristics of the wet clutch and the dynamic load characteristics of the spline pair, etc.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2023-0078/

This paper aims to design an event-triggered adaptive prescribed performance controller for flexible manipulators, with the primary objectives of achieving output performance constraints and addressing communication resource limitations.

The authors propose a novel prescribed performance barrier Lyapunov function (PP-BLF) that considers both output and tracking performance constraints. The PP-BLF ensures that the system's output, transient behavior and steady-state performance, adhere to prescribed constraints. The boundary of the PP-BLF is established by an exponential function that decays over time. Notably, the PP-BLF can be applied seamlessly in unconstrained cases without necessitating controller redesign. Moreover, the controller design incorporates an event-triggered mechanism, effectively reducing the frequency of controller updates and optimizing the utilization of communication resources. Additionally, the authors employ adaptive techniques to estimate the system's unknown parameters and approximate unknown nonlinear functions using radial basis function neural networks (RBFNN). To address the challenge of “complexity explosion”, dynamic surface technology is employed.

Numerical simulations are conducted under five different cases to verify the effectiveness of the proposed controller. The results demonstrate that the controller successfully constrains the output tracking error within the prescribed performance boundary. Moreover, compared with the traditional time-triggered mechanism, the event-triggered mechanism significantly reduces the controller's update frequency, resolving the problem of limited communication resources.

The paper reduces the update frequency of control signals and improves resource utilization through an event-triggered mechanism in the form of relative thresholds. The authors recognize that the event-triggered mechanism may impact the output performance of the system. To address this challenge, the authors propose a prescribed performance Barrier Lyapunov Function (PP-BLF). The PP-BLF is designed to effectively constrain the output performance of the system, ensuring satisfactory control even when the control signal updates are reduced.

This study aims to elaborate on the existing link between maintenance practices and the digital world while also highlighting any unaddressed potential for digital transformation in aircraft maintenance. Additionally, explore how digital technologies contribute to optimizing efficiency within the continuing airworthiness management (CAM) processes.

A literature review was performed to provide a precise review of the authority regulations on CAM processes and existing literature on digital transformation, including artificial intelligence, machine learning, neural network and big data in civil aircraft maintenance and continuing airworthiness processes. This method is used to organize, analyze and structure the body of literature to identify research gaps in the selected scope of the study.

The high position of digital technologies in preventive and predictive maintenance and the need for legislative development for using them in CAM are emphasized. Moreover, it is shown in which area of CAM scientific research has been performed regarding the application of frontier digital technologies. In addition, the gaps between maintenance practices and the digital world, along with the potential scopes of digital transformation which has not been well addressed, are identified. And finally, how digital technologies can effectively increase efficiency in CAM processes is discussed.

To the best of our knowledge, no study comprehensively determined the body of existing knowledge on the aspects of digitalization related to the field of continuing airworthiness management and aircraft maintenance. The results of this study provide a positive contribution to airlines, policymakers, manufacturers and maintenance organizations achieving additional benefits from the implementation of digital technologies in the CAM processes.

A large number of organisations are moving towards adopting Industry 4.0 (I4.0), and simultaneously, the emphasis on attaining sustainability development goals is also increasing. Hence, it is imperative to understand the interplay between I4.0 and sustainability. However, the literature addressing the same is still in infancy. Accordingly, the purpose of this study is to fill this gap in the literature by exploring the potential sustainability impacts of I4.0 on the organisations and society in terms of sustainability risks.

To gain an understanding of sustainability aspects in the I4.0 context, relevant literature is gathered using Scopus and Web-of-Science database. An in-depth review of 51 research papers is performed to determine the sustainability risks associated with I4.0.

From the study, a total of 16 sustainability risks are identified, and I4.0 sustainability risk taxonomy is developed. The proposed taxonomy extends the sustainability implications of I4.0 beyond the triple bottom line umbrella and includes the organisational perspective as well. Furthermore, the study provides future research avenues to scholars by positing five potential research questions under different risk management stages.

The study provides an understanding of sustainability risks associated with the adoption of I4.0. The findings will help practitioners streamline their production and operation processes by finding out possible solution to the sustainability risks of their smart factories in advance. The present research will act as a stepping stone towards I4.0 sustainability. The proposed research questions will assist the future researchers in extending the field of I4.0.

To the best of the authors’ knowledge, this is one of the first studies to address the topic of sustainability risks in the context of I4.0.