A generalised minimum variance controller is developed for linear time-varying systems. The plants to be controlled are described using a controlled autoregressive moving average model and are exponentially stable. Bo...
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A generalised minimum variance controller is developed for linear time-varying systems. The plants to be controlled are described using a controlled autoregressive moving average model and are exponentially stable. Both, the plant parameters and the noise variance are time-varying. The generalised minimum variance cost functional is the sum of a tracking error variance between a filtered plant output and a filtered reference plus a penalty term of filtered plant input. Time-varying filters are introduced for weighting to make the controller more flexible.
This paper proposes a cooperative evolutionary method for optimizing the properties of an ANFIS-architecture-based model where only the input-output data of the identified system are available. The primary tasks of fu...
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The output tracking control problem for fuzzy time-delay systems in presence of parameter perturbations has been solved via fuzzy T-S system models and variable-structure control approach. Following the reaching condi...
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Graduate studies in fields of eng.neering typically include advanced control theory. in turn, these courses enhance both academic and applied research, hence contributing to combined knowledge and technology transfer,...
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in this paper, LTI systems with parameter uncertainty are considered. For such systems, a method is presented for determining permissible perturbations of the parameters of the system that maintain stability (the so-c...
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Minimally invasive surgery (MIS) characterizes a sophisticated operation technique in which long instruments are inserted into the patient through small incisions. Though providing crucial benefits compared to open su...
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Minimally invasive surgery (MIS) characterizes a sophisticated operation technique in which long instruments are inserted into the patient through small incisions. Though providing crucial benefits compared to open surgery (i.e. reduced tissue traumatization) it is also faced with a number of disadvantages. One of the major problems is that the operating tissue cannot be palpated any more and that appearing contact forces can hardly be sensed. To overcome some of the drawbacks minimally invasive robotic surgery (MIRS) constitutes a promising approach. Due to the remote control the operating instruments can be equipped with miniaturized force/torque sensors and thus the appearing contact forces can be displayed to the surgeon. As the development of sensorized surgical devices is challeng.ng there are no commercially available robotic systems which provide kinesthetic feedback currently. In this work, a prototypical force reflecting MIRS system is presented and the importance of kinesthetic feedback is evaluated empirically. Based on the results of a psychophysical pre-experiment, a representative dissection task was realized which was accomplished by 25 surgeons. The study revealed that robot assisted surgery is actually suited to reduce unintentional injuries when appropriate force feedback is available, although it has to be mentioned that the operating time increased compared to a manual intervention. Further interesting insights were gained by a qualitative video analysis which revealed that robotic surgery affords acquisition instead of manual surgical skill transfer. Especially experienced surgeons have to get accustomed to a more continuous working style.
Learning distributed object grasp by a group of robots with redundant members is the main focus of this paper. In Elahibakhsh, A. H., et al. (2004), we tackled the problem of learning form closure grasp for planar con...
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Learning distributed object grasp by a group of robots with redundant members is the main focus of this paper. In Elahibakhsh, A. H., et al. (2004), we tackled the problem of learning form closure grasp for planar convex objects by multiple non-communicating robots without any information about the shape of objects. In this paper, the problem in presence of redundant agents is investigated. Agents' states and actions are designed such that the group learns grasping different objects using Q-learning method. As the environment is not intelligent enough to assess each agent's effect on the team performance, a credit assignment algorithm based on knowledge evaluation is designed. The proposed method considers the environment credit for the team, number of redundant agents, and the expertness level of each agent in its credit assignment. Applicability of the designed approach is verified through a set of simulations. It is shown that the team learns grasping different objects. Therefore, it is expected that the proposed method can be extended for distributed grasp of deformable objects
In this paper, LTI systems with parameter uncertainty are considered. For such systems, a method is presented for determining permissible perturbations of the parameters of the system that maintain stability (the so-c...
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In this paper, LTI systems with parameter uncertainty are considered. For such systems, a method is presented for determining permissible perturbations of the parameters of the system that maintain stability (the so-called parameter stability margins) for the case in which the coefficients of the characteristic equation of the system are polynomial functions of the uncertain parameters. A globally convergent polynomial programming technique is used to solve the underlying parametric non-convex subproblems for computing the stability margins. The approach is illustrated using a four-parameter numerical example.
Graduate studies in fields of eng.neering typically include advanced control theory. In turn, these courses enhance both academic and applied research, hence contributing to combined knowledge and technology transfer,...
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Graduate studies in fields of eng.neering typically include advanced control theory. In turn, these courses enhance both academic and applied research, hence contributing to combined knowledge and technology transfer, in particular if supported by industry as well. This paper reports on such fruitful experiences at our universities through the math-analytical back-stepping and state-feedback control design methodologies. computer simulation and laboratory experiments have demonstrated these controller designs possess quality performances, which are comparable with the other designs for the same applications.
The output tracking control problem for fuzzy time-delay systems in presence of parameter perturbations has been solved via fuzzy T-S system models and variable-structure control approach. Following the reaching condi...
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The output tracking control problem for fuzzy time-delay systems in presence of parameter perturbations has been solved via fuzzy T-S system models and variable-structure control approach. Following the reaching condition, a variable-structure fuzzy control method is proposed accordingly, when the time delay is known and available and when unknown and unavailable. The method guarantees the system operation arrives to the sliding surface in finite time interval and be kept there thereafter while tracking the desired trajectory. The sufficient condition for globally bounded state is derived by using the ISS theory and the LMI method. A simulation example demonstrates the validity and effectiveness of the proposed method.
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