During manual driving, most human drivers often use information about the speed and position of the preceding and following vehicles in order to adjust the position and speed of their vehicles. The purpose of this pap...
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During manual driving, most human drivers often use information about the speed and position of the preceding and following vehicles in order to adjust the position and speed of their vehicles. The purpose of this paper is to design an autonomous intelligent cruise control (AICC) which mimics this human driving behavior. The proposed AICC law uses relative speed and spacing information from the preceding and following vehicles in order to choose the proper control action for smooth vehicle following and for maintaining a desired intervehicle spacing specified by the driver. The vehicle stability and platoon stability (in the case of multiple vehicles) in both directions (backward and forward) are guaranteed by the proposed AICC law. Furthermore, platoon stability is guaranteed for a speed-dependent desired spacing (time headway approach) as well as for a constant desired spacing at all speeds.
This research is aimed at the development of bipedal humanoid robots working in a human living space, with a focus on its physical construction and motion control method. At the first stage, we developed the bipedal h...
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This research is aimed at the development of bipedal humanoid robots working in a human living space, with a focus on its physical construction and motion control method. At the first stage, we developed the bipedal humanoid robot WABIAN (Waseda bipedal humanoid), and proposed a control method for dynamic cooperative biped walking. In this paper, we present a follow-walking control method with a switching patterns technique for a bipedal humanoid robot to follow human motion by hand contact. By a combination of both algorithms, the robot is able to perform dynamic stepping and walking forward and backward in a continuous time while someone is pushing or pulling its hand. In this paper, the authors describe the control methods for the realization of physical interaction between a human and a bipedal humanoid robot.
This paper describes a novel approach to the design of a control system for a short take-off, vertical landing (STOVL) aircraft gas turbine engine. A multi-level multiobjective genetic algorithm (MOGA) is employed to ...
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This paper describes a novel approach to the design of a control system for a short take-off, vertical landing (STOVL) aircraft gas turbine engine. A multi-level multiobjective genetic algorithm (MOGA) is employed to design controllers at both individual operating points, using system linearisations and small signal response characteristics, and over the full-flight envelope, using a nonlinear model and large signalresponses. The proposed approach should allow the selection of smoother controller parameters over the flight envelope and ensure that more consistent control demands are made at off-design operating points.
A fully automatic interpretation of an awake electroencephalogram (EEG) has been developed. Automatic integrative EEG interpretation consists of four main parts: quantitative EEG interpretation, EEG report making, pre...
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This paper deals with the multimode approach to nonlinear engine control, more precisely with the selection and blending of the various modes, i.e. controllers, each of which provides good control at predefined operat...
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This paper describes simple adaptive control for plants with bounded nonlinear disturbances. The proposed controller is applicable to all plants whose relative degree is less than four, in which the upper bound of the...
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We present an evolution strategy (ES) algorithm - incest prevented evolution strategy (IPES) enhancing our novel evolution strategy (NES) algorithm. Validity of NES and IPES algorithms is compared with other evolution...
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Impedance control is one of the most effective force control methods for a robot manipulator in contact with an object. It should be noted, however, that a practical study on such a method has not been successfully ap...
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Impedance control is one of the most effective force control methods for a robot manipulator in contact with an object. It should be noted, however, that a practical study on such a method has not been successfully applied to an industrial robot with 6 degree-of-freedom. A hybrid compliance/force control (HCC) in this field was suggested to deal with the practical problem, in which a desired damping coefficient is determined by repeating many simulations. To determine a suitable compliance without trial and error, we have already presented a tuning method which produces the desired time-varying compliance, giving the critical damping in contact with an object, by using the information on the inertia and Jacobian matrices. But the tuning method needs to measure the physical information of the environment. In this paper, to overcome the problem we propose a fuzzy environment model that can estimate each directional stiffness of the environments. The fuzzy environment model is composed of several fuzzy rules which are learned with genetic algorithms. Simulation results show that the proposed method is very effective for deciding the desired compliance without any complicated tuning and is very robust to the change of environment.
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