We consider the iterative learning control problem from a 2D systems/adaptive control viewpoint. In particular, it is shown how some fundamental results from nonlinear adaptive control can be successfully applied in t...
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In this paper, we propose a new approach to the high-speed navigation of the indoor environments for wheeled mobile robots using hybrid dynamic control approach. The proposed hybrid system consists of the discrete sta...
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In this paper, we propose a new approach to the high-speed navigation of the indoor environments for wheeled mobile robots using hybrid dynamic control approach. The proposed hybrid system consists of the discrete state system as the high-level process and the continuous state system as the low-level process. In discrete state system, the di crete states are defined by the user-defined constraints and the abstracted motions specify the reference motion commands of mobile robots. The experimental results show that hybrid system approach is an effective method for the autonomous navigation and highspeed maneuvering.
In this paper, the Hopfield neural network with delay (HNND) is studied from the standpoint of regarding it as an optimizing computational model. Two general updating rules for networks with delay (GURD) are given bas...
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In this paper, the Hopfield neural network with delay (HNND) is studied from the standpoint of regarding it as an optimizing computational model. Two general updating rules for networks with delay (GURD) are given based on Hopfield-type neural networks with delay for optimization problems and characterized by dynamic thresholds. It is proved that in any sequence of updating rule modes, the GURD monotonously converges to a stable state of the network. The diagonal elements of the connection matrix are shown to have an important influence on the convergence process, and they represent the relationship of the local maximum value of the energy function to the stable states of the networks. All the ordinary discrete Hopfield neural network (DHNN) algorithms are instances of the GURD. It can be shown that the convergence conditions of the GURD may be relaxed in the context of applications, for instance, the condition of nonnegative diagonal elements of the connection matrix can be removed from the original convergence theorem. A new updating rule mode and restrictive conditions can guarantee the network to achieve a local maximum of the energy function with a step-by-step algorithm. The convergence rate improves evidently when compared with other methods. For a delay item considered as a noise disturbance item, the step-by-step algorithm demonstrates its efficiency and a high convergence rate. Experimental results support our proposed algorithm.
Recent years has seen much progress in the theory and application of iterative learning control schemes for both linear and (classes of) nonlinear dynamics. In the case of the former, many algorithms based on minimizi...
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Recent years has seen much progress in the theory and application of iterative learning control schemes for both linear and (classes of) nonlinear dynamics. In the case of the former, many algorithms based on minimizing a suitable cost function have been reported. Here the interest is in the so-called norm optimal approach where the basic philosophy is to compute the control input on the current trial such that the tracking error is reduced in an optimal way without too much deviation from the control input used on the previous trial. This paper compares the performance of a range of controllers arising from use of the norm optimal approach - both stand alone and against alternatives.
Considering that anthropo centric systems are an adequate domain for captological approaches, and that interface agents are most natural interactants for the humans involved, the paper presents a broad-spectrum generi...
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Considering that anthropo centric systems are an adequate domain for captological approaches, and that interface agents are most natural interactants for the humans involved, the paper presents a broad-spectrum generic architectural framework to support developing flexible interfaces for industrial applications, based on synergetic correlation between persuasive technologies and polymorphic agents. The design space for agent-oriented captology is defined and several of its main dimensions are elaborated upon. The main mechanisms used are dynamic priorities, "flexible cloning" and fuzzy temporal windows. Some agent-oriented test-bench applications instantiating the generic architecture, arc described briefly.
Analysis of complex systems such as hierarchically structured network systems that are employed in modelling and analysis various aspects and issues of control and management in telecommunications is investigated. The...
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Real-time scheduling methods introduce various types of jitter in task instance execution. For real-time computer-controlled systems, the introduced sampling jitter and sampling-actuation delays may degrade the system...
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Real-time scheduling methods introduce various types of jitter in task instance execution. For real-time computer-controlled systems, the introduced sampling jitter and sampling-actuation delays may degrade the system performance and even lead to instability in the system. The degradation of the system performance can be compensated on-line by updating the controller parameters at each controller task instance execution, in what we call the compensation approach. In this paper we present stability analysis for controller tasks that perform the compensation approach.
In general, characteristics of classical control theory and properties of real-time scheduling algorithms may cause unexpected controlsystem responses in the implementation of real-time computer-controlled systems. R...
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In general, characteristics of classical control theory and properties of real-time scheduling algorithms may cause unexpected controlsystem responses in the implementation of real-time computer-controlled systems. Revising real-time scheduling properties, we analyse which are the main timing problems that current scheduling algorithms may introduce in the execution of control loops. Next, we categorise those timing problems, that is, jitters on task-instances executions, in a control context. Afterwards, we show, by simulations, different types of controlsystem performance degradation that these jitters may cause. Finally, we propose possible solutions that solves this degradation, based on irregular sampling discrete-time system models with varying time delays.
A cortical network for voluntary movement control within constraints from neurophysiology and motor psychophysics is developed. A neural controller is proposed to track the desired joint trajectories of a single link ...
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A cortical network for voluntary movement control within constraints from neurophysiology and motor psychophysics is developed. A neural controller is proposed to track the desired joint trajectories of a single link controlled by an agonist-antagonist pair of actuators with muscle-like properties. The system is capable of executing voluntary reaching movements, with a typical bell-shaped velocity profile, under unexpected load conditions. The goals of this research work are: (1) to apply the knowledge of human neuro-musculo-skeletal motion control to a biomechanically designed, neural controlled, robotic system, and (2) to demonstrate that such system is able to respond voluntarily similar to human movements on an experimental platform. Through experimental performance results, we shown that neural controller exhibits key kinematic properties of human movements, dynamics compensation, and asymmetric bell-shaped velocity profiles.
Repetitive processes are a distinct class of 2D systems of both theoretical and applications interest. They are characterized by a series of sweeps through a set of dynamics with explicit interaction between the outpu...
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Repetitive processes are a distinct class of 2D systems of both theoretical and applications interest. They are characterized by a series of sweeps through a set of dynamics with explicit interaction between the outputs, or pass profiles, produced on successive passes. Their essential unique features are that (i) information propagation is over a finite duration in one of the two separate directions of information propagation; and (ii) the explicit interaction between successive pass profiles can lead to oscillations in the sequence of pass profiles that increase in amplitude in the pass to pass direction. In the case of processes with linear dynamics (either differential or discrete) a reasonably rich systems theory is available for models which are standard (or nonsingular). In this paper, we provide the first substantial results on discrete linear repetitive processes described by a singular state space model.
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