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Autonomous swarm control, which is expected to be able to handle multiple unmanned vehicles (UxVs), is an important technology that can be applied to many operations and incorporated in many systems. For operations in real environments, we have to consider severe conditions under which communications between UxVs may be inadequate and the environment changes unexpectedly. In addition to optimality,...
We propose a swarm control algorithm for unmanned vehicles that adapts to unexpected environments while making the optimal formation. Our proposed algorithm, “autonomous and adaptive control”, is inspired by the control mechanism of living organisms and reconciles adaptability under a complex and changing environment and optimality for the various purposes of the system. In this paper, we apply the...
We proposed two adaptive control methods for speed control of brushless direct current(BLDC) motor disturbed by two kinds of disturbances in this paper. The dynamic model of BLDC motor possessing either parametric uncertainties disturbed by unknown with known bound external disturbances or parametric uncertainties disturbed by unknown with known structure model external disturbances is considered,...
This paper proposes a novel adaptive sliding mode observer to improve the performance of sensorless control of permanent magnet synchronous motor (PMSM) in the More Electric Aircraft (MEA) system. An adaptive sliding mode observer base on adaptively tuning the observer gain is investigated to relax the requirement for the bound of load uncertainties and strengthen the anti-interference ability. System...
This work presents an ensemble-based visual object tracker called KFebT. This method can fuse using a Kalman Filter the result of several out-of-the box trackers or specialist methods that solve parts of the problem, like methods that only estimate the target scale variation. Our purpose in joining multiple trackers is to take advantage of the different strengths and weaknesses of each approach. The...
This paper presents an adaptive nonsingular terminal sliding mode formation control by means of output recurrent fuzzy wavelet neural networks for a group of networked heterogeneous Mecanum-wheeled omnidirectional robots with uncertainties. The dynamic behavior of each uncertain heterogeneous omnidirectional robot is modelled by a reduced three-input-three-output second-order state equation with uncertainties...
The paper observes methods of qualimetry of dynamic processes based on the “entropy” approach. Also the paper presents variants of criteria for the processes quality assessment, adapted to different situations, as well as justifies the expediency of their application. The proposed models are based on the use of typical statistical characteristics of the analyzed parameters, are compact and convenient...
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...
Quadrotors, like any dynamical system, are subjected to model uncertainties which may cause instability and inaccuracy in navigation. In addition, the presence of input constraints violates the affine property which, as a result, adds additional challenges and complicates designing the control system for quadrotors. In this paper, an adaptive nonlinear control algorithm is designed to overcome these...
Due to the rapid growth in scale and complexity of information networks, self-organizing systems have been focused on for realizing new network control architectures that have high scalability, adaptability, and robustness. However, in self-organizing systems, the uncertainty (incompleteness, ambiguity, and dynamicity) of information observable for components in the system can lead to the slow adaptation...
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...
Load Frequency Control (LFC) for an islanded microgrid is so critical due to intermittent behaviors of load and renewable energies. Performance of PID controllers deteriorates under uncertainties necessitating a controller that specifically considers these uncertainties. A stochastic controller can count for these uncertainties and hence a self-tuning PID controller based on Hebbian Learning method...
The article considers methods of processing uncertainties in solving dynamic planning problems. Various types of uncertainties are considered, such as stochastic uncertainties, uncertainties in the parameters and structure of models, the uncertainty of the amplitude type and the probabilistic type. Methods for processing data for reducing uncertainties are proposed.
The model-based event-triggered strategies have been developed as an alternate for Zero-Order-Hold (ZOH)- based event triggered scheme in continuous-time for multi-agent systems (MAS). However, traditional event-triggered schemes need the knowledge of system dynamics whereas model-based schemes are sensitive to model uncertainties. Therefore, in this paper, a novel distributed robust event-triggered...
This paper proposes an adaptive integral back-stepping control scheme for tracking control of 2-DOF (Degree of Freedom) helicopter. The helicopter is an important model from the control prospective due to its nonlinear behavior, highly cross coupling effects and instability in open loop. Classical control methods (PI, PD and PID Controllers) and baseline controllers with a linear quadratic regulator...
The paper considers the problem of ship autopilot design based on Bech's model of the vessel. Since the ship model is highly nonlinear and the state vector is not completely measurable, the control system synthesis is performed by means of output feedback linearization method combined with a state observer. Due to considerable parameter variations and other substantial uncertainties a robust-adaptive...
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...
This paper proposes a Decision-Theoretic approach to problems involving interaction between robot systems and human users, which takes into account the latent aspects of Human-Robot interaction, e.g., the user's status. The presented approach is based on the Partially Observable Markov Decision Process framework, which handles uncertainty in planning problems, extended with information rewards to...
In this work, we present a framework for handling multiple, simultaneous, natural language queries, in a resource constrained environment, using Quality of Information (QoI). Incoming queries are first parsed into response graphs, tree-like structures designed to formalize a system's understanding of user intent, via a pragmatics toolkit. The system then uses a combination of QoI-awareness, adaptive...
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