This study proposes a learning impedance controller comprising a proportional feedback control term, a composite-learning-based uncertainty estimation term, and a robot-environment interaction control term. The impeda...
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This study proposes a learning impedance controller comprising a proportional feedback control term, a composite-learning-based uncertainty estimation term, and a robot-environment interaction control term. The impedance control problem is converted into a particular reference-trajectory tracking problem based on a generated reference trajectory. The proposed controller ensures the exponential convergence of the auxiliary tracking error and the uncertainty estimation error. The interaction control term improves the transient control performance through suppression/encouragement of the incorrect/correct robot *** composite-learning update law enhances the transient and steady-state control performances based on the exponential convergence of the uncertainty estimation error and auxiliary tracking error. Finally, the effectiveness and advantages of the proposed impedance controller are validated by theoretical analysis and simulations on a parallel robot.
Automata-theoretic models have been used successfully in modelbased process supervision and diagnosis. From a practical viewpoint, their main drawback is their complexity, which increases fast with the size of the ori...
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This paper presents a control design approach for Input/Output (I/O) automata. The main contribution consists of an explicit description of the control design procedure, which leads to an implementation-friendly archi...
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This paper investigates control systems, where the controller influences the plant through two control input signals with different characteristics. A continuous control input is used to attenuate disturbances and for...
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The visualization system of spatial fields of synoptic objects is presented. Algorithms of scalar and vector fields' visualization are described. Results are shown for synthetic and real data.
The visualization system of spatial fields of synoptic objects is presented. Algorithms of scalar and vector fields' visualization are described. Results are shown for synthetic and real data.
The paper addresses the problem of generating the best possible communication structure for an efficient set-point following of autonomous agents. It considers a communication network in which additional communication...
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The paper proposes the modeling and control design of a variable-geometry suspension system. The goal of the modification of wheel camber is to track road trajectory and enhance the lateral stability of the vehicle. T...
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This paper presents a new formalism for fault-tolerant control of nondeterministic Input/Output automata. The mathematical framework is based on a combination of set theory, Boolean operators and automata unfolding. T...
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This paper presents a new online trajectory planning method for an unmanned aerial vehicle (UAV) acting as an aerial base station for the communication relay between moving ground vehicles, which have different qualit...
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This paper proposes an online reconfiguration method for discrete event systems described by nondeterministic Input/Ouput automata. The method modifies the control law to circumvent the effects of sensor and internal ...
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