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This paper presents an approach to trajectory tracking control for autonomous vehicles subject to parametric uncertainties. Such uncertainties may have the potential to significantly decrease the performance of the system, even to the point of destabilizing it. Therefore, these parametric variations must be taken into account during the design of the controller. To solve the trajectory tracking problem...
Inventory regulation and control to a desired time-varying inventory level is accomplished via an accurate on line observer-based demand rate estimation, followed by a demand rate satisfaction effort incorporated on the production rate decision rule. An extended demand rate observer is shown to efficiently allow for production rate to accurately match highly fluctuating uncertain demand rates, with...
In conditions of a mass character of higher education, the problems of student identification are relevant because of the differences in the contingent of students in terms of level of training, personal and cognitive characteristics. The learning process is characterized by the presence of uncertainty factors, which requires modeling and control of the application process of methods and tools of...
This paper presents a self-memory prediction model to mitigate the effects of image based visual servoing (IBVS) system under uncertainty. The performance of IBVS system is easily influenced by different tasks, diverse environments and uncertain disturbances. Through building a self-memory prediction model to keep previous movement tendency in the every current movement, the framework of a self-memory...
The impulse-based discrete feedback control has been proposed in previous work for the second-order motion systems with damping uncertainties. The sate-dependent discrete impulse action takes place at zero crossing of one of both states, either relative position or velocity. In this paper, the proposed control method is extended to a general hybrid motion control form. We are using the paradigm of...
The interaction between a human driver and an automated driving system may improve when the automation is designed in such a way that it behaves in a human-like manner. This paper introduces a human-like steering model, in which the driver adapts to the risk due to uncertainty in the environment. Current steering models take a risk-neutral approach, while the fields of economics and sensorimotor control...
Small/micro Unmanned Aerial Systems (UAVs) require the ability to operate with constraints of a diverse, automated airspace where obstacle telemetry is denied. This paper proposes a novel Sense, Detect and Avoid (SDA) algorithm with inherit resilience to sensor uncertainty. This is achieved through the interval geometric formulation of the avoidance problem, which by the use of interval analysis,...
In this paper, we investigate the state estimation problem for timed discrete event systems with communication delays. The problem is how to estimate the current state under the uncertainties caused by partial observations and random observation delays. We construct an augmented automaton after analyzing the influence mechanism of random observation delays existed between the supervisor and the timed...
An adaptive tracking control is proposed for a class of constrained nonlinear systems with hysteresis and uncertainty. Hysteresis and uncertainty may limit system performance such as giving rise to undesirable accuracy or oscillations, even leading to instability. First, Bouc-Wen model is used to describe the hysteresis, and the upper bound is derived. Then, a Barrier Lyapunov Function (BLF) is adopted...
This paper addresses the problem of steering Underactuated Surface Vessels (USVs) along given paths. Due to dynamical uncertainty and ocean disturbances induced by unknown wind, waves and ocean currents, there exist some imperfections in dealing with this non-linear systems with traditional control algorithms. A novel trajectory following controller based on Active Disturbance Rejection Control (ADRC)...
Adaptive iterative learning control is a popular approach to control parametric time-varying systems over finite time interval. However, initial resetting condition limits the application of a large amount of learning control algorithms. In this paper, we propose a suboptimal iterative learning control for a class of dynamic parametric systems to solve this problem. An error-tracking control strategy...
Detection task allocation plays a significant role in many military applications. A better detection task allocation strategy can improve the operational efficiency of the military actions, such as improving tracking accuracy and attacking efficiency. However, the trajectory of the target is usually random which makes the allocation difficult to solve. In this paper, we consider the optimal detection...
Indoor applications based on vehicular robotics require accurate, reliable and efficient localisation. In the absence of a GPS signal, an increasingly popular solution is based on fusing information from a dead reckoning system that utilises on-board sensors with absolute position data extracted from the environment. In the application considered in this paper, the information on absolute position...
Aircraft need to be separated from other aircraft by either a minimum vertical distance of 1000ft or by a minimum horizontal distance of 5NM to avoid mid-air collisions. Traffic Alert and Collision Avoidance System (TCAS) work well as a tactical safety backups to avoid collision, but cannot perform separation assurance. This paper presents the design aspects of system that would predict separation...
This paper focuses on developing new navigation and reconnaissance capabilities for cooperative unmanned systems in uncertain environments. The goal is to design a cooperative multi-vehicle system that can survey an unknown environment and find the most valuable route for personnel to travel. To accomplish the goal, the multi-vehicle system first explores spatially diverse routes and then selects...
We present a method to model and classify trajectory data that come from surveillance videos. Observations of the locations of moving entities are used to estimate their expected velocity in the scene. Such estimation is performed by a Gaussian process regression that enables to approximate probabilistically the expected velocity of entities given some observed evidence in the scene. Subsequently,...
The paper concerns the development of a adaptive sliding mode control based on super twisting (ASTW) and can be applied to a Human-Driven Knee Joint Orthosis. Therefore, a model of the shank-orthosis system is given considering the human effort as an external torque acting on the system. The main objective of this paper is to bring together two approaches to reduce the phenomenon of chattering, adaptation...
Three-degree-of-freedom trajectory tracking of the stratospheric airship is investigated. With a simplified planar dynamic model, an adaptive backstepping sliding mode controller is designed to keep the airship to globally asymptotically track a desired trajectory. Lyapunov functions are used to ensure the tracking performance when model parametric uncertainty and external disturbances exist. Simulation...
Model-based predictive control is an effective method for control the large scale systems. Method is based on on-lin solution of control task over the control horizon using current and past measurements as well as the system model. Because model and measurement uncertainty, predicted and plant outputs might be different and plant output may exceed plant output constraints. Generated control is not...
There are usually large uncertainties in the aerodynamic parameters of Mars entry vehicles, which inevitably degrades the performance of entry guidance algorithms. The paper presents a backstepping sliding mode controller for drag tracking in Mars entry guidance, which can guarantee the tracking error with finite-time convergence. First, the drag can track the reference trajectory under the virtual...
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