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A dynamic adaptive iterative learning control method applied to contouring control is developed to reduce the contour tracking error for a planar robotic system with parametric uncertainty. The proposed control scheme takes advantages of the self-tuning law and adaptive iterative learning control, which consists of a feedback controller and an adaptive learning term. The self-tuning method is applied...
The controller design is one of the major difficulties in realizing robot-aided rehabilitation program. The purpose of our study is to develop an adaptive impedance force control strategy based on dynamic recurrent fuzzy neural network to maintain the stability of the rehabilitation robot system in the case when the patient's physical condition makes a change. An on-line identification method was...
Compared with traditional dexterous humanoid robotic hands, underactuated robotic hands have the advantages of self-adaptive grasp and easy real-time control. In this paper, the development of a novel underactuated robotic hand is presented. This hand has five fingers and through using underactuation, the self-adaptability of each finger is achieved. This underactuated humanoid robotic hand can accomplish...
Scientific research and development on the control of autonomous airship have shown a significant growth in recent years. New applications appear in the areas such as freight carrier, advertising, monitoring, surveillance, transportation, military and scientific research. The control of Autonomous airship is a very important problem for the aerial robots research. In this paper, the previous research...
Focusing on the dynamic model parameter identification problem, this paper proposed an adaptive linear-time-domain system identification method for the micro unmanned helicopter robot. Based on the flash memory in the Micro Guide Navigation Control (MGNC), system recorded the flight data sequences regarding the input signal for servos and output signals for attitude and velocity information. Through...
This paper deals with impedance H∞ control problem of constrained manipulators based on neural network techniques. With this approach, it is guaranteed that the relationship between the force and position errors converges to a given dynamic behavior. The neural networks proposed in this paper adapt only the uncertain dynamics of the robotic manipulator, they actuate as complement of the nominal model...
In this paper a decentralized adaptive control for interconnected lagrangian systems is addressed. Linearly parameterized interconnections and implicit cooperation among the subsystems are assumed. Under these conditions, asymptotical tracking in each subsystem to the reference trajectory is achieved. A numerical example of controlling two interconnected pendulums is included to illustrate the performance...
Formation control experiments are performed using two robots, each equipped with a camera. When both robots are fully informed of the reference velocity, a decentralized feedback control, which achieves the desired relative position and the reference velocity, is experimentally verified. Another adaptive design is implemented in the situation where only one robot has the full reference velocity information...
This paper presents the design and implementation of a three-dimensional (3D) location system to provide accurate location information. The location information is computed by applying Trilateration technique on three sets of collected distance measurements. Trilateration technique is implemented to improve the accuracy of the location system. The 3D system is able to provide accurate locations for...
The mechanism of swarm flocking phenomena is investigated in this paper, and a distributed coadaptive control algorithm is presented for swarm robot system. We prove that this controller can enable all swarm members to converge to a common velocity only by means of the local information, then the finish time of flocking can be estimated. An improved particle swarm optimization algorithm (PSO) is adopted...
Living beings locomotion's main characteristics are oscillatory motions. These motions are sustained by a full mechanical architecture of passive and active organs, controlled by means of neural networks called Central Pattern Generators. A Karman vortex Street is a repeating pattern of swirling vortices caused by the flow's separation of a fluid passing around bluff bodies. This phenomenon is well...
This study deals with a master-slave control system for virtual reality-based tele-operation construction robot, which consists of an construction robot(CR), two joysticks for operating CR from a remote place, and two screens of 3DVisor device display used to present the virtual working field. The force presentation is essential information to the operator in this system, namely, the operator needs...
We present an adaptive control approach combining forward kinematics model learning methods with the operational space control approach. This combination endows the robot with the ability to realize hierarchically organised learned tasks in parallel, using tasks null space projectors built upon the learned models. We illustrate the proposed method on a simulated 3 degrees of freedom planar robot....
In the face of large scale parametric uncertainties, the single model (SM)-based classical adaptive control approach demands high observer, controller and adaptation gains in order to achieve good tracking performance. The well known problem of having high-gain based design is that it amplifies the input and output disturbance as well as excites hidden unmodeled dynamics causing poor tracking performance...
This paper presents a new method of using hybrid intelligent systems to solve the problem of tuning the parameters of a fuzzy logic controller. Two different hybrid intelligent systems are introduced in this paper. Each system proposes learning in a two-stage iterative process. The first system combines a fuzzy logic controller with genetic algorithms to form the iterative genetic based fuzzy logic...
In this paper, we propose an adaptive fuzzy output feedback control method for trajectory tracking control problem for robotic systems. Using Lyapunov method, we first develop a stable adaptive fuzzy state feedback control algorithm by assuming that the systems output and its derivatives are available for feedback control design. The algorithm combines fuzzy systems with robust adaptive controller...
This paper describes a robotic agent that can promote communication when people first meet. When two people meet for the first time, a communication mediator can be important because people often feel stressed and cannot talk comfortably. Our agent reduces their stress by using embodied entrainment and thus promotes communication. In the research field of embodied entrainment, suitable timing of a...
We present a novel biomimetic approach to mapless autonomous navigation based on insect neuroethology. We implemented and tested a real-time neuronal model based on the Distributed Adaptive Control framework. The model unifies different aspects of insect navigation and foraging including landmark recognition, chemical search, path integration and optimal memory usage. Consistent with recent findings...
In this paper, a neural-network based robust adaptive controller is proposed to control an industrial robot considering non- linearities, uncertainties and external perturbations. Three-axis SCARA robots is used to test the performance of this controller. The nonlinear system is treated as a partially known system. The known dynamic is used to design a nominal feedback controller based on the well-known...
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