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...
详细信息
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 unit control and sensors to extract some *** elaborate a fuzzy controller which generates speed wheels orders in order to join the target position.
This paper presents a method to compute sub-optimal control strategies of discrete time large scale nonlinear systems by neural networks. The method is based on the principle of decomposition of the global system into...
详细信息
This paper presents a method to compute sub-optimal control strategies of discrete time large scale nonlinear systems by neural networks. The method is based on the principle of decomposition of the global system into interconnected subsystems for which we consider that non-linearities are located in the interconnection terms. Then, a mixed method is considered to coordinate between different subsystems in order to compute the optimal control. So, for each subsystem, local optimal feedback gains are expressed in terms of the interconnection vector. For this purpose, neural networks have been used in order to identify these gains. Simulation results of a rotary crane show that the proposed method yields to satisfactory performances. The robustness of the proposed approach is analysed.
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...
详细信息
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 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...
详细信息
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.
Forest growth is restricted at high latitudes and high elevations, and the limits of tree growth in these environments are dramatically marked by the treeline transition from vertical, erect tree stems to prostrate, s...
详细信息
Forest growth is restricted at high latitudes and high elevations, and the limits of tree growth in these environments are dramatically marked by the treeline transition from vertical, erect tree stems to prostrate, stunted shrub forms. However, after 4 centuries of research, there is still debate over the precise mechanism that causes Arctic and alpine treelines. We review the various theories for treeline, including excessive light, low partial pressure of CO2, snow depth, wind exposure, reproductive failure, frost drought, and temperature. Some of these theories are very old and are no longer held in high esteem;while they may help to explain treeline physiognomy or local variation in treeline position, they generally fail as global explanations. Temperature-based theories appear to be the most reasonable, since cold temperature is really the only trait that is universally characteristic of treelines around the world. Temperature may limit a variety of physiological processes, such as carbon fixation, cuticular ripening, or new tissue development, and theories invoking these mechanisms are discussed. The vertical growth habit of trees is unfavorable to growth in this hostile environment: Low-profile vegetation enjoys a far more favorable microenvironment for growth. Microsite enviroment and ecological facilitation have been shown to be essential for successful regeneration, which is a prerequisite for upward advancement of treeline. Recent evidence supports a theory based on "sink limitation," i.e., that new tissue development is restricted not by carbon availability but by cold treeline temperatures which limit cell division, and that this situation is exacerbated by arborescent growth (aboveground meristems coupled to cold ambient air temperatures) and self-shading (which keeps soil temperatures cold and restricts belowground activity).
Since its conception in the mid 1950s, artificial intelligence with its great ambition to understand and emulate intelligence in natural and artificial environments alike is now a truly multidisciplinary field that re...
Since its conception in the mid 1950s, artificial intelligence with its great ambition to understand and emulate intelligence in natural and artificial environments alike is now a truly multidisciplinary field that reaches out and is inspired by a great diversity of other fields. Rapid advances in research and technology in various fields have created environments into which artificial intelligence could embed itself naturally and comfortably. Neuroscience with its desire to understand nervous systems of biological organisms and systems biology with its longing to comprehend, holistically, the multitude of complex interactions in biological systems are two such fields. They target ideals artificial intelligence has dreamt about for a long time including the computer simulation of an entire biological brain or the creation of new life forms from manipulations of cellular and genetic information in the laboratory. The scope for artificial intelligence in neuroscience and systems biology is extremely wide. This article investigates the standing of artificial intelligence in relation to neuroscience and systems biology and provides an outlook at new and exciting challenges for artificial intelligence in these fields. These challenges include, but are not necessarily limited to, the ability to learn from other projects and to be inventive, to understand the potential and exploit novel computing paradigms and environments, to specify and adhere to stringent standards and robust statistical frameworks, to be integrative, and to embrace openness principles.
暂无评论