Experiment design for quantum channel parameter estimation includes the design of the quantum input to the channel and the observables to be applied on the resulting quantum output system, called the experiment config...
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Robots used in manufacturing today are tailored to their tasks by system integration based on expert knowledge concerning both production and machine control. For upcoming new generations of even more flexible robot s...
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Robots used in manufacturing today are tailored to their tasks by system integration based on expert knowledge concerning both production and machine control. For upcoming new generations of even more flexible robot solutions, in applications such as dexterous assembly, the robot setup and programming gets even more challenging. Reuse of solutions in terms of parameters, controls, process tuning, and of software modules in general then gets increasingly important. There has been valuable progress within reuse of automation solutions when machines comply with standards and behave according to nominal models. However, more flexible robots with sensor-based manipulation skills and cognitive functions for human interaction are far too complex to manage, and solutions are rarely reusable since knowledge is either implicit in imperative software or not captured in machine readable form. We propose techniques that build on existing knowledge by converting structured data into an RDF-based knowledge base. By enhancements of industrial controlsystems and available engineering tools, such knowledge can be gradually extended as part of the interaction during the definition of the robot task.
The hybrid minimum principle (HMP) is extended to hybrid systems with autonomous (internally forced) switching on switching manifolds, controlled (externally forced) switching, jumps of the continuous state when switc...
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ISBN:
(纸本)9781612848006
The hybrid minimum principle (HMP) is extended to hybrid systems with autonomous (internally forced) switching on switching manifolds, controlled (externally forced) switching, jumps of the continuous state when switching, and time-varying functions for specifying the continuous and discrete dynamics. The formulation of the hybrid optimal control problem (HOCP) includes running, switching, and terminal costs. The HMP provides necessary optimality conditions for a solution of the HOCP and can be used as basis for developing numerical optimal control algorithms.
A discrete-time sliding-mode control for the trajectory tracking problem of four driving-steering wheels (4DW/SW) autonomous vehicle SEEKUR is presented in this paper. SEEKUR is a holonomic, all-weather, outdoor robot...
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We propose an algorithm for optimal input design in nonlinear stochastic dynamic systems. The approach relies on minimizing a function of the covariance of the parameter estimates of the system with respect to the inp...
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This paper presents the results obtained by visual predictive control laws in real-time visual servoing architectures. A key role when designing a stable image based control law is played by the visual features, and t...
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This paper presents the results obtained by visual predictive control laws in real-time visual servoing architectures. A key role when designing a stable image based control law is played by the visual features, and thus both points and image moments were considered and their performance revealed. A 6 d.o.f manipulator robot with an eye-in-configuration is used to design a visual servoing architecture and realtime implementation using Matlab is described. The results of different experiments for planar static objects are presented and discussed. For establishing the performance of visual predictive control laws a comparison with classical image based control laws is conducted.
This article presents the active vibration control with bio-inspired algorithms model based system utilising genetic algorithm (GA), particle swarm intelligence (PSO) and artificial immune system (AIS). The parameter ...
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This article presents the active vibration control with bio-inspired algorithms model based system utilising genetic algorithm (GA), particle swarm intelligence (PSO) and artificial immune system (AIS). The parameter of the model is estimated and the transfer function of the active vibration controller is characterized implementing GA with real coded execution, PSO with spreading factor and AIS implemented AiNet type of algorithms. The comparisons of AVC based bio inspired algorithms are validated using time and frequency domain response, mean squares of error and correlation tests. The performances of the algorithm are assessed through determination of dominant vibration modes using spectral density of the response.
Abstract This paper describes the development of an active vibration control system for a light and flexible stress ribbon footbridge. The 13 m span Carbon Fiber Reinforced Plastics (CFRP) stress ribbon bridge was bui...
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Abstract This paper describes the development of an active vibration control system for a light and flexible stress ribbon footbridge. The 13 m span Carbon Fiber Reinforced Plastics (CFRP) stress ribbon bridge was built in the laboratory of the department of Civil and Structural engineering, Berlin Institute of Technology. Its lightness and flexibility result in high vibration sensitivity. To reduce pedestrian-induced vibrations, very light pneumatic muscle actuators are placed at handrail level introducing control forces. First, a reduced discretized analytical model is derived for the stress ribbon bridge. To verify the analytical prediction, experiments without feedback control are conducted. Based on this model, a velocity feedback control strategy is designed to actively control first mode vibrations. To handle the nonlinearities of the muscle actuator a subsidiary nonlinear force controller is implemented based on exact linearisation methods. The stability of the entire closed-loop system with actuator saturation is investigated by the Popov Criterion. control performance is verified by experiments. It is demonstrated that handrail introduced forces can efficiently control the first mode response.
Achieving high performance optimization algorithms for embedded applications can be very challenging, particularly when several requirements such as high accuracy computations, short elapsed time, area cost, low power...
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A simple tuning method for second-order active disturbance rejection control (ADRC) that achieves high performance and good robustness for a wide range of processes is presented. ADRC is a novel control strategy whose...
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