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The purpose of this study is to solve the issues of time-consuming and complicated computation of traditional measures, as well as the underutilization of two-dimensional (2D) phase-trajectory projection matrix, so a new set of features were proposed based on the projection of attractors trajectory to characterize the friction-induced attractors and to reveal the tribological behavior during the running-in process.

The frictional running-in experiments were conducted by sliding a ball against a static disk, and the friction coefficient was collected to reconstruct the friction-induced attractors. The projection of the attractors in 2D subspace was then mapped and the distribution of phase points was adapted to conduct the feature extraction.

The evolution of the proposed moment measures could be described as “initial rapid decrease/increase- midterm gradual decrease/increase- finally stable,” which could effectively reveal the convergence degree of the friction-induced attractors. Moreover, the measures could also describe the relative position of the attractors in phase–space domain, which reveal the amplitude evolution of signals to some extent.

The proposed measures could reveal the evolution of tribological behaviors during the running-in process and meet the more precise real-time running-in status identification.

This study presents an image processing algorithm capable of calculating selected flight parameters requested by flight control systems to guide aircraft along the horizontal projection of the landing trajectory. The parameters identified based on the basics of the image of the Calvert light system appearing in the on-board video system are used by flight control algorithms that imitate the pilot’s schematics of control. Controls were generated using a fuzzy logic expert system. This study aims to analyse an alternative to classical solutions that can be applied to some specific cases.

The paper uses theoretical discussions and breakdowns to create the basics for the development of structures for both image processing algorithms and control algorithms. An analytical discussion on the first stage was transformed into laboratory rig tests using a real autopilot unit. The results of this research were verified in a series of software-in-the-loop computer simulations.

The image processing method extracts the most crucial parameters defining the relative position of the aircraft to the runway, as well as the control algorithm that uses it.

In flight control systems that do not use any dedicated ground or satellite infrastructure to land the aircraft.

This paper presents the original approach of the author to aircraft control in cases where visual signals are used to determine the flight trajectory of the aircraft.

The purpose of this paper is to plan the penetration trajectory for unmanned aerial vehicle (UAV) in the presence of radar‐guided surface to air missiles (SAMs).

The penetration trajectory planning problem is modelled based on four aspects of radar tracking features. As penetration just utilizes the low observability of radar cross section (RCS) to satisfy temporal constraints of tracking, the problem is formulated as multi‐phase trajectory planning with detected probability (MTP‐DP). While utilizing both the low observability of RCS and the radial velocity blind area of radar, the problem is formulated as multi‐phase trajectory planning with detected probability and radial velocity (MTP‐DP&RV). The pseudospectral multi‐phase optimal control based trajectory planning algorithm is proposed.

The results of the examples illustrate that the multi‐phase trajectory planning method can finely utilize the radar tracking features to optimize the comprehensive efficiency of penetration. The pseudospectral multi‐phase optimal control based trajectory planning algorithm could effectively solve the trajectory planning problem.

This paper provides new structured method to plan UAV penetration trajectory for military application and academic study.

The paper aims to present a new approach for safe operation, and maintenance cost reduction, regarding electrical and electromechanical systems of power production, power conversion and power transmission, primarily in industrial units.

The paper adapts a theoretical approach to real‐time monitoring of pulse energy conversion systems (PECSs), and prediction of abnormal dynamics incipient and developing failure. The approach utilizes the preliminary bifurcation analysis results and the geometrical interpretation of the fractal regularities in PECS dynamics, to reveal degradation development.

It turns out that this new approach enables one to fill the joint requirements of real‐time failure prediction of the high frequency power control devices, and of the relating failure symptoms to cause parameters. Discussions are led on the fundamental outcomes of numerical and experimental investigations of a DC‐DC buck voltage converter with pulse‐width‐modulation (PWM) control.

The real‐time monitoring of incipient abnormal dynamics in key nonlinear devices of electrical and electromechanical systems constitutes a mean to predict and prevent failures. It provides invaluable information for deciding and planning predictive maintenance actions, from the insurance of optimal operating conditions to abnormal operating prevention, either by means of modification of controlled parameters and control laws or, in the worst case, by change of the power components' structure.

About “failure prediction”, this paper proposed to pay attention, not to identification of the dynamics evolution specific reason, but real‐time monitoring of this reason consequence – incipient abnormal dynamics in the electrical and electromechanical systems – that can lead to failure. The advantage of this approach consists in the possibility of taking into account PECS operating conditions of models ambiguity of both disturbing parameter changes and PECS behavior.

This paper aims to increase the safety of the robots’ operation by developing a novel method for real-time implementation of velocity scaling and obstacle avoidance as the two widely accepted safety increasing concepts.

A fuzzy version of dynamic movement primitive (DMP) framework is proposed as a real-time trajectory generator with imbedded velocity scaling capability. Time constant of the DMP system is determined by a fuzzy system which makes decisions based on the distance from obstacle to the robot’s workspace and its velocity projection toward the workspace. Moreover, a combination of the DMP framework with a human-like steering mechanism and a novel configuration of virtual impedances is proposed for real-time obstacle avoidance.

The results confirm the effectiveness of the proposed method in real-time implementation of the velocity scaling and obstacle avoidance concepts in different cases of single and multiple stationary obstacles as well as moving obstacles.

As the provided experiments indicate, the proposed method can effectively increase the real-time safety of the robots’ operations. This is achieved by developing a simple method with low computational loads.

This paper proposes a novel method for real-time implementation of velocity scaling and obstacle avoidance concepts. This method eliminates the need for modification of original DMP formulation. The velocity scaling concept is implemented by using a fuzzy system to adjust the DMP’s time constant. Furthermore, the novel impedance configuration makes it possible to obtain a non-oscillatory convergence to the desired path, in all degrees of freedom.

Lower-limb exoskeleton systems enable people with spinal cord injury to regain some degree of locomotion ability, as the expected motion curve needs to adapt with changing scenarios, i.e. stair heights, distance to the stairs. The authors’ approach enables exoskeleton systems to adapt to different scenarios in stair ascent task safely.

In this paper, the authors learn the locomotion from predefined trajectories and walk upstairs by re-planning the trajectories according to external forces posed on exoskeleton systems. Moreover, instead of using complex sensors as inputs for re-planning in real-time, the approach can obtain forces acting on exoskeleton through dynamic model of human-exoskeleton system learned by an online machine learning approach without accurate parameters.

The proposed approach is validated in both simulation environment and a real walking assistance exoskeleton system. Experimental results prove that the proposed approach achieves better performance than the traditional predefined gait approach.

First, the approach obtain the external forces by a learned dynamic model of human-exoskeleton system, which reduces the cost of exoskeletons and avoids the heavy task of translating sensor input into actuator output. Second, the approach enables exoskeleton accomplish stair ascent task safely in different scenarios.

Planning and control of humanoid biped walking has been an active research topic for many years. But, there is no definite answer to the question of how to practicre‐examinedally achieve speedy and stable walking in real‐time and in a changing environment. The purpose of this paper is to re‐examine the issue of planning and controlling humanoid biped walking, then to propose two new ideas.

The first idea is to treat the supporting foot of a biped to be part of the ground. In this way, there is a foot reaction force acting at a fixed virtual joint, which can be at, or below, the ankle joint. And, a new concept is come our that is named as in‐foot ZMP in contrast to the existing concept of on‐ground ZMP. The unique benefit with this new concept of in‐foot ZMP is that the ZMP control is no longer an issue because the in‐foot ZMP can be controlled so as to to be at a fixed virtual joint during a stable walking. Such a fixed virtual joint can be called a ZMP joint.

The second idea is to focus on hip's trajectory (instead of on‐ground ZMP's trajectory) and to split a hip's dynamic response into two independent parts: one is the steady‐state response contributing to the stability of walking (or standing), and the other is the transient response contributing to the speed of walking. This idea allows us to explicitly postulate the necessary and sufficient condition for achieving leg stability as well as the necessary and sufficient condition for achieving foot stability. The paper shows that the implementation of these two new ideas help realize a unified framework for task‐guided, intention‐guided, and sensor‐guided, planning and control of humanoid biped walking.

This paper first re‐examines the issue of planning and controlling humanoid biped walking, then proposes two new ideas. The first idea is to treat the supporting foot of a biped to be part of the ground. The second idea is to focus on hip's trajectory (instead of on‐ground ZMP's trajectory) and to split a hip's dynamic response into two independent parts: one is the steady‐state response contributing to the stability of walking (or standing), and the other is the transient response contributing to the speed of walking.

The paper aims to present an outline of the technology of the active anti-surge algorithm based on high-frequency pressure measurement. The presented system is fast, inexpensive and reliable and does not limit the machine-operating range. Many contemporary anti-surge systems are based on theoretical surge margin. This solution limits machine operating range by about 10-15 per cent in the region of the highest pressure ratios. It is also often sensitive to change in external conditions such as temperature or density, as the system reacts to limits calculated theoretically.

This paper presents results of pressure measurements obtained on the low-speed centrifugal blower DP1.12. The pressure signals were presented in the form of phase diagrams, and conclusions were drawn from their phase portraits to develop the surge indication parameter.

The presented safety system uses the signal to develop the so-called (rate of derivative fluctuation) RDF parameter. In nominal working conditions, this parameter keeps the value close to 1. When RDF reaches values over 3, the anti-surge procedure should be implemented. Experimental studies have shown that this algorithm assures enough time to incur actions suppressing unstable phenomena.

The system reacts to real machine working conditions and is hence reliable. The RDF algorithm could also be used to identify local flow instabilities, as well as off-design operation.

The purpose of this paper is to develop a superconvergent trajectory optimization method for the design of low-thrust transfer trajectories from parking orbit to libration point orbits near the collinear libration points.

The optimization method is developed by merging the concept of Lyapunov feedback control law with the manifold dynamics. First, the whole transfer trajectory is divided into two segments, raising segment and coast segment. Then, the trajectories of each segment are described in different coordinate frames, and designed with Lyapunov feedback control law and the manifold dynamics, respectively. The Poincaré section is used as an effective tool to search the compatible patching point between these two segments on the manifold. Finally, the transfer trajectory is optimized using sequential quadratic programming.

In the numerical simulation, the proposed optimization method does not have any convergence problem. It is a fast and effective method for the very sensitive trajectory optimization problem.

The nonlinear constraints in the original trajectory optimization problem are satisfied by using the Lyapunov feedback control law; hence, the problem is transformed into a nonconstrained parameter optimization problem. The convergence problem of the sensitive optimization problem is solved thoroughly.

Automated robotic assembly on a moving workpiece, referred to as assembly in motion, demands that an assembly robot is synchronised in all degrees of freedom to the moving workpiece, on which assembly parts are installed. Currently, this requirement cannot be met due to the lack of robust estimation of 3D positions and the trajectory of the moving workpiece. The purpose of this paper is to develop a camera system that measures the 3D trajectory of the moving workpiece for robotic assembly in motion.

For the trajectory estimation, an assembly robot-guided, monocular camera system is developed. The motion trajectory of a workpiece is estimated, as the trajectory is considered as a linear combination of trajectory bases, such as discrete cosine transform bases.

The developed camera system for trajectory estimation is tested within the robotic assembly of a cylinder block in motion. The experimental results show that the proposed method is able to reconstruct arbitrary trajectories of an assembly point on a workpiece moving in 3D space.

With the developed technology, a point trajectory can be recovered offline only after all measurement images are acquired. For practical assembly tasks in real production, this method should be extended to determine the trajectory online during the motion of a workpiece.

For practical, robotic assembly in motion, such as assembling tires, wheels and windscreens on conveyed vehicle bodies, the developed technology can be used for positioning a moving workpiece, which is in the distant field of an assembly robot.

Besides laser trackers, indoor global positioning systems and stereo cameras, this paper provides a solution of trajectory estimation by using a monocular camera system.