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Numerous data mining problems involve an investigation of relationships between features in heterogeneous datasets, where different prediction models can be more appropriate for different regions. We propose a technique of dagging localized weak learners. We recognize local regions having similar characteristics and then build local experts on each of these regions describing the relationship between...
This paper presents a complete methodology for mission planning and navigation of Autonomous Underwater Vehicles (AUVs) in ocean environment. Path planning near the ocean floor is accomplished via genetic algorithms and B-Splines based on known data of the ocean floor. In addition, collision free navigation is achieved in unknown environments. Prior to vehicle’s launch, a genetic algorithm based on...
This paper presents a Generalized Predictive Control (GPC) extension, called Bilateral GPC (BGPC), for teleoperation systems in the presence of both communication delays and slave force feedback. The originality of the proposed approach is to take into account the case where the reference trajectory is not a priori known. This difficulty is due to the bilateral problem where the force feedback alters...
This paper presents the application of adaptive control to PWM Dc-to-Dc Converter Operating in Continuous Conduction Mode. The system under study is a buck-boost with parasitic as non linear and variable structure plant. First the model of converter is discussed; the non linearity is handled with state space averaged modeling into the linear time-varying representation; one adopted consequently an...
A novel neuro-adaptive congestion controller is presented, capable of achieving certain time-quality characteristics, by regulating the per packet round trip. The controller is implemented at the source and is proven robust against modelling imperfections, exogenous disturbances (UDP traffic) and delays (propagation, buffering). The proposed source control theoretic framework is comprised of three...
Single-motor locomotion systems are of interest for low-cost, small robots. In this paper, one such system is presented. The vehicle has three wheels of which only one is connected to the motor. This one can switch between two positions so the vehicle can turn to either one. As a result, it follows an undulating trajectory. An empirical motion control algorithm is also presented. The corresponding...
This paper describes a method for planning six DOF trajectories for an underactuated unmanned airship and for computing the open-loop controls. Beginning with a smooth inertial 3D trajectory to be tracked by the center of mass of the vehicle, the proposed algorithm, based on the dynamics of the system, provides the 3D corresponding body-fixed linear and angular velocities and the vehicle orientation,...
Particle swarm optimization (PSO) as a novel computational intelligence technique, has succeeded in many continuous problems. But in discrete or binary version there are still some difficulties. In this paper a novel binary PSO is proposed. This algorithm proposes a new definition for the velocity vector of binary PSO. It will be shown that this algorithm is a better interpretation of continuous PSO...
Nonlinear partial differential equations (PDE) are notorious to solve. In only a limited number of cases can we find an analytic solution. In most cases, we can only apply some numerical scheme to simulate the process described by a nonlinear PDE. Therefore, approximate solutions are important for they may provide more insight about the process and its properties (stability, sensitivity etc.). The...
Diversity in unmanned vehicle designs and control as well as diversity in existing autopilots lead to major compatibility issues among different platforms. The small number of different autopilot designs currently available in the market and their limitations, justifies the rationale for proposing design of a new modular, flexible, easy to integrate autopilot, suitable for multiple platforms. A discussion...
This note focuses on deriving stability conditions for a class of linear parameter-dependent systems in a state-space representation. More precisely, we will compute the set of parameters for which the characteristic roots are located on the imaginary axis, and next we will give the characterization of the way such critical roots are crossing the imaginary axis. The methodology considered makes use...
In a companion paper [1], a novel framework characteristics are assessed via a Monte Carlo study.for the identification of stochastic dynamical systems under multiple operating conditions, with each condition characterized by a measurable variable, is introduced and used for the identification of postulated Functionally Pooled AutoRegressive with eXogenous input (FP-ARX) models. The present paper...
The recently introduced concept of system abstraction appears to be a promising tool for control purposes in a hierarchical framework. While propagation of system’s properties has been extensively studied, little investigation has been carried out on how a high-level control law is implemented on the low-level original system. In this paper we address this problem from a geometric point of view.
The goal of this study was to obtain models that described the relation between the anaesthetic drug infusions (propofol) and an electroencephalogram (EEG) derived index (Cerebral State Index - CSI) during general anaesthesia in dogs. The first phase integrated the adaptation of hardware for EEG acquisition and exploration for the best electrodes position in dogs skull. The clinical protocol implementation...
In this paper a new class of globally stable finite dimensional repetitive controllers for nonlinear passive systems is proposed. The passivity-based design of the proposed repetitive controller avoids the problem of tight stability conditions and slow convergence of the conventional, internal model-based, repetitive controllers. The existing internal and external model-based repetitive controllers...
This paper studies stabilization schemes for a discrete-time control systems in which the feedback loop includes a network link that may suffer packet drops. We model the packet dropping network link as an erasure channel and study state/output feedback stabilization schemes for linear systems of arbitrary dimension. We use the mean square deviation of the system state from zero (MSDZ) as our measure...
A multiestimation scheme with a discrete-time matching controller for linear time-invariant (LTI) continuous-time plant with unknown parameters is presented. The scheme incorporates several discretization models running in parallel. Each of these models is calculated from a different combination of the correcting gain beta in a fractional order hold (FROH) and the set of gains to reconstruct the plant...
The paper deals with design of a robust controller via algebraic μ-synthesis for two tank system, which is a well known benchmark problem. The controller is designed by decoupling two-input two-output system into two identical SISO (Single-Input Single-Output) plants. The task of designing the robust controller is then performed by finding a suitable pole placement for the SISO systems with the robustness...
The main aim of this contribution is to present the possibilities of simple PI and PID-like robust algorithms in control of systems with periodic time-varying parameters. The proposed algebraic synthesis is based on general solutions of Diophantine equations in the ring of proper and stable rational functions and sequentially on selection of appropriate controller from the set defined by Youla-Kučera...
In this paper, the generalized trajectory of a mobile manipulator is obtained. The objective is to allow the end-effector track a given trajectory in a fixed world frame. The motion of the platform and that of the manipulator are coordinated by a pseudo neural network designed from the kinematics model of the system. A learning paradigm is used to produce the required reference variables for each...
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