This paper presents an optimal fuzzy logic controller design using optimization techniques. The fuzzy logic controller (FLC) has been developed and implemented for the motion of the robot from an initial position towa...
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This paper presents an optimal fuzzy logic controller design using optimization techniques. The fuzzy logic controller (FLC) has been developed and implemented for the motion of the robot from an initial position towards another desired position, taking into account the kinematic constraints. First, we have carried out a simulation of a fuzzy logic based controller which determines the speed values of each driving wheel, while seeking the goal. Secondly, an optimization of this controller has been realized using gradient method and genetic algorithms. A comparison between these methods has been effected. Not only simulation results are shown in this paper, but the ldquoreal-timerdquo implementation has been realized onto the mini robot Khepera II. Simulation results verify successfully the application of the proposed method to real motion situations.
This paper develops a new control approach to position synchronization of multiple robot manipulators based on emergent consensus algorithms. The proposed strategy only requires local neighbor-to-neighbor information ...
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This paper develops a new control approach to position synchronization of multiple robot manipulators based on emergent consensus algorithms. The proposed strategy only requires local neighbor-to-neighbor information exchange between manipulators and does not assume the existence of any explicit leaders in the team. The control strategy is to stabilise position tracking of each manipulator while synchronizing its motion with other manipulator's position motion so that differential position errors amongst robots converge to zero. Simulations conducted on a multi-robots manipulators motion control system demonstrate the effectiveness of the method.
Many researchers are interested in electric wheelchair automation because of the mobility problemsmet by a certain number of disabled and aged people. In this paper, we propose to associate a system's help navigat...
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Many researchers are interested in electric wheelchair automation because of the mobility problemsmet by a certain number of disabled and aged people. In this paper, we propose to associate a system's help navigation to a standard electric *** system is equipped with unitcontrol and sensors to extract some *** elaborate a fuzzy controller which generates speed wheels orders in order to join the target position.
In this paper, a new approach for neural PID tuning is presented based on the use of a neural network and the internal model control (IMC) principle. The neural network is used to adjust on line the PID controller aft...
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In this paper, a new approach for neural PID tuning is presented based on the use of a neural network and the internal model control (IMC) principle. The neural network is used to adjust on line the PID controller after an off line training step. The developed approach is based on the use of a neural supervisor having as inputs the control signal, its correspondent output and the filter time constant and the PID parameters as outputs. The design of the supervisor is based on the procedures of linearization and IMC principle. We briefly outline the content of the tuning course and finish the paper with illustrative example where good performances have been obtained.
This paper presents a new learning algorithm for feedforward neural networks. This algorithm uses the vigilance parameter to generate the hidden layer neurons. This process improves the initial weight problem and the ...
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This paper presents a new learning algorithm for feedforward neural networks. This algorithm uses the vigilance parameter to generate the hidden layer neurons. This process improves the initial weight problem and the adaptive neurons of the hidden layer. The proposed approach is based on combined unsupervised and supervised learning. In this algorithm, the weights between input and hidden layers are firstly adjusted by Kohonen algorithm with fuzzy neighborhood, whereas the weights connecting hidden and output layers are adjusted using gradient descent method. Two simulation examples are provided to demonstrate the efficiency of the approach compared with a number of other methods.
This paper presents the stability analysis of parameter identification. The Takagi Sugeno fuzzy model is employed to represent the discrete time nonlinear dynamical systems. Once the structure of the fuzzy model is fi...
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This paper presents the stability analysis of parameter identification. The Takagi Sugeno fuzzy model is employed to represent the discrete time nonlinear dynamical systems. Once the structure of the fuzzy model is fixed, the parameters can be optimized. The parameter identification is accomplished by applying the gradient method where the iteration rates are specific to each parameter. The stability of this algorithm is discussed by using two approaches which guarantee that the system is stable if the iteration rates satisfy sufficient conditions. The first approach deals with the consequence parameters and the second one deals with the premise parameters.
A wide bandwidth CMOS realization of high performance dual output second generation (CCIIplusmn) and third generation (CCIIIplusmn) current conveyors are presented. Both second and third generation current conveyors h...
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A wide bandwidth CMOS realization of high performance dual output second generation (CCIIplusmn) and third generation (CCIIIplusmn) current conveyors are presented. Both second and third generation current conveyors have the advantages of a wide current and voltage bandwidths, controlled intrinsic resistances at port X, Y and Z. We have developed an optimization program, thanks to Heuristic methodology that is used for optimal sizing regarding static and dynamic performance. PSPICE simulation show that the current and voltage bandwidths are respectively 1.5806 GHz and 6.506 GHz, and 454.11 Omega as R X input port resistance for a control current of 100 muA. CCIIplusmn is a useful building block for analog circuits, especially for application requiring dual outputs. The proposed circuit is able of operating at voltage supply (plusmn2.5V), with reduced power consumption. A frequency characterization of the proposed CCIIplusmn is given, this CCIIplusmn is characterized by low values for its parasitic input resistance (454.11 Omega). In this paper, we present a versatile multi-input multi-output controlled filter configuration. Either a three-input single output or single-input double-output universal filter can be realized. The proposed circuits offer the following advantageous features: realization of current-mode low-pass and band-pass filter responses from the same configuration, employing only three current conveyors and four grounded passive elements. In order to implement a current controlled Radiofrequency active filter, we use a translinear configuration for both second and third generation current conveyors. The proposed implementation exhibiting a current controlled intrinsic resistances at port X, Y and Z allow a control of the cut-off frequency. The cut-off frequency of the low pass filter can be attend 1.64 GHz and the central frequency of the band pass filter can be attend 1.13 GHz. Simulation results are in good accordance with theoretical ones. PSPICE
A three hierarchical sliding mode control is presented for a class of an underactuated system which can overcome the mismatched perturbations. The considered underactuated system is a double inverted pendulum (DIP), c...
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A three hierarchical sliding mode control is presented for a class of an underactuated system which can overcome the mismatched perturbations. The considered underactuated system is a double inverted pendulum (DIP), can be modeled by three subsystems. Such structure allows the construction of several designs of hierarchies for the controller. For all hierarchical designs, the asymptotic stability of every layer sliding mode surface and the sliding mode surface of subsystems are proved theoretically by Barbalat’s lemma. Simulation results show the validity of these methods. [ABSTRACT FROM AUTHOR]
This paper proposes a method to compute sub-optimal control strategies of discrete time large-scale non-linear systems by fuzzy logic controllers. The method is based on the principle of decomposition of the global sy...
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This paper proposes a method to compute sub-optimal control strategies of discrete time large-scale non-linear systems by fuzzy logic controllers. The method is based on the principle of decomposition of the global system into inter-connected subsystems. We consider that the non-linearities are located in the interconnections terms. Then, a mixed method of coordination procedure between different subsystems is formulated. So, for each subsystem, local optimal feedback gains are expressed as a function of the interconnection vector. Within this approach, first order Tkagi-Sugeno fuzzy logic systems have been constructed in order to identify these gains. Simulation results of a rotary crane show the effectiveness of the method and the robustness of the proposed approach.
This work consists on the evaluation of the performances of three neural classifiers. The Multi-Layer Perceptron (MLP), the Self-Organizing Map (SOM), the Learning Vector Quantization (LV Q) are considered by this stu...
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This work consists on the evaluation of the performances of three neural classifiers. The Multi-Layer Perceptron (MLP), the Self-Organizing Map (SOM), the Learning Vector Quantization (LV Q) are considered by this study. The example that will be considered in the evaluation of the technical classifications's performances is the handwritten character recognition.
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