In this paper, we present a VSS-based tracking control for a fixed point regulation of 2-DOF underactuated manipulators. The design approach is systematic and relies on the selection of appropriate choice of two slidi...
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In this paper, we present a VSS-based tracking control for a fixed point regulation of 2-DOF underactuated manipulators. The design approach is systematic and relies on the selection of appropriate choice of two sliding surface. The controller is designed for the both sliding surfaces are attractive. Lyapunov theory is used to study and demonstrate the stability of the system. Convergence of state space is proved and robustness issues to bounded disturbances are also investigated. Simulation results on 2-DOF whirling pendulum are presented to chow the effectiveness of this approach.
This paper presents a design approach to hybrid controlsystems, combining analytical feedback linearization control techniques with neural networks. Such a mixed implementation leads to a more effective control desig...
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This paper presents a design approach to hybrid controlsystems, combining analytical feedback linearization control techniques with neural networks. Such a mixed implementation leads to a more effective controldesign with improved system performance and robustness. The main objective of integrating neural networks is to overcome the problems with uncertainties in the plant parameters and structure encountered in the analytical model-based design. Shunt DC motor is characterized by complex nonlinear and time-varying dynamics and inaccessibility of some model parameters for on line measurements, and hence can be considered as an important challenging engineering topic. The input-state feedback linearization technique is known for its good results locally in a neighborhood of an operating point. However, these results are sensitive to model parameter variations and so performances may deteriorate. Neural network-based controllers are considered as candidates for this parameters sensitivity. In a first step, an algorithm for analytical exact input-state linearizing control is formulated. The following step is dedicated to the robust neural feedback controller design. A simulation study of these methods is presented. The effectiveness of the neural controller with respect to the analytical one is demonstrated for a large armature resistance variation.
In this paper, a new SVM (Support Vector Machines) synthesis method is presented. This method is based essentially on training criterion optimization of this machine by a set of hierarchical structures of learning aut...
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In this paper, a new SVM (Support Vector Machines) synthesis method is presented. This method is based essentially on training criterion optimization of this machine by a set of hierarchical structures of learning automata. This methodology is adopted for the development of off-line isolated handwritten digits recognition system. A comparison is taken between this new approach and that of a standard approach for SVM synthesis. These two methodologies are also compared with a neural network based classification method. The obtained results show the performances of the new suggested method for SVM synthesis.
controlling an underactuated manipulator with less actuators than degree of freedom is a challenging problem, specifically when it is to force the underactuated manipulator to track a given trajectory or to be configu...
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controlling an underactuated manipulator with less actuators than degree of freedom is a challenging problem, specifically when it is to force the underactuated manipulator to track a given trajectory or to be configurated at a specific position in the work space. This paper presents a cascade sliding mode tracking controller for set-point regulation of 2-DOF underactuated manipulators. This work builds on an observation that an underactuated manipulator can be treated as two subsystems. Consequently, a cascade sliding mode tracking controller can be designed as follows. First, a sliding mode surface is designed for both subsystems, this two sliding surfaces represent a first layer in the design architecture. A second layer sliding mode surface is then constructed based on the first layer sliding surface. The cascaded sliding mode controller is therefor deduced in terms of Lyapunov stability theorem. Robustness issues to bounded disturbances are then investigated. Simulation results on 2-DOF whiling pendulum are presented to demonstrate the effectiveness of the approach.
Using ambient energy, the operation time of batteries in mobile applications can be increased and the acceptability by the user can be improved In this paper we investigate the possibilities to design hearing aids as ...
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ISBN:
(纸本)9781424405886
Using ambient energy, the operation time of batteries in mobile applications can be increased and the acceptability by the user can be improved In this paper we investigate the possibilities to design hearing aids as power aware system scavenging energy directly from its environment. The energy source we consider is vibration produced by movements primarily in the neighbourhood of the ear and other movements of the human body. Experimental measurements of vibration were evaluated by means of a theoretical model. The results show that an interesting improvement of battery operation time can be reached.
Using ambient energy, the operation time of batteries in mobile applications can be increased and the acceptability by the user can be improved. In this paper we investigate the possibilities to design hearing aids as...
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Using ambient energy, the operation time of batteries in mobile applications can be increased and the acceptability by the user can be improved. In this paper we investigate the possibilities to design hearing aids as power aware system scavenging energy directly from its environment. The energy source we consider is vibration produced by movements primarily in the neighbourhood of the ear and other movements of the human body. Experimental measurements of vibration were evaluated by means of a theoretical model. The results show that an interesting improvement of battery operation time can be reached.
This paper addresses a nonlinear formation control of a group of underactuated ship at a dynamic level of planar formation control, while holding a desired inter-ship formation pattern. In particular we propose a comb...
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ISBN:
(纸本)9781424406340
This paper addresses a nonlinear formation control of a group of underactuated ship at a dynamic level of planar formation control, while holding a desired inter-ship formation pattern. In particular we propose a combination of the virtual structure and the path following approaches to derive the formation architecture. Ship coordination is achieved by adjusting the speed of each of the ships along its path, in the sense that the derivative of the path is left as a free input to synchronize the ships motion. The proposed controller is basically based on Lyapunov direct method and backstepping technique. Simulations illustrate the efficacy of the proposed approach.
This paper proposes a synchronization scheme for a class of continuous-time chaotic systems. We show that two systems belonging to the class of generalized Lorenz systems can be synchronized using an adaptive feedback...
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This paper proposes a synchronization scheme for a class of continuous-time chaotic systems. We show that two systems belonging to the class of generalized Lorenz systems can be synchronized using an adaptive feedback controller. This controller is added to the response system to force a subset of its state variables to oscillate synchronously with their counterpart of the drive system. We show that the controller gain vector is tuned without any knowledge of the system model. To illustrate the efficiency of the proposed scheme, we present numerical simulations to synchronize two-by-two a Lorenz-like system, Chen system and Lü system.
This paper presents an implementation of a signature recognition system based on pulse mode multilayer neural networks with on chip learning. Taking advantage of the compactness of the multiplierless solutions of puls...
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This paper presents an implementation of a signature recognition system based on pulse mode multilayer neural networks with on chip learning. Taking advantage of the compactness of the multiplierless solutions of pulse mode operations, we apply an architecture, in which the synapse is made up with a DDFS and the neuron uses a nonlinear adder. A programmable activation function is proposed by means of an adjustable pulse multiplier so that the activation function slope can be adjusted without any added hardware cost. Good learning capability is obtained. As illustration, we consider a signature learning application. The corresponding design was implemented into an FPGA platform ( virtex II PRO XC2VP7).
This article presents an adaptive multilayer neural network-based controller that feedback-linearizes the system for a class of single-input single-output (SISO) and multi-input multi-output (MIMO) continuous-time non...
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This article presents an adaptive multilayer neural network-based controller that feedback-linearizes the system for a class of single-input single-output (SISO) and multi-input multi-output (MIMO) continuous-time nonlinear systems. control action is used to achieve tracking performances for state-feedback linearizable unknown non-linear system. The control structure consists of a feedback lineariza- tion portion provided by neural networks (NN). In the standard problem of feedback-based control, the cost to minimize is a func- tion of the output derivatives. When the cost function depends on the output error, the gradient method cannot be applied to adjust the neural network parameters. In this context, the stochastic approximation approach allows computation of the cost function derivatives. In order to show the feasibility and performance of this control scheme, two applications are chosen as nonlinear case studies.
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