When a robot manipulator contacts objects, the contact force between the robot hand and the object as well as the position of the robot hand must be controlled in many tasks. In the previous works of hybrid position/force control, it was assumed that the mechanical constraint condition was exactly obtained or the constraint surface or the constraint line was exactly expressed by geometrical equations. In practice, however, the parameter values of geometrical equations, kinematic and dynamics of the robot contain estimation errors. This paper describes position/force trajectory tracking feedback control performance of robot manipulators under parameter estimation error. It is mathematically proven that the trajectory tracking performance can be improved by setting suitable combination of the feedback gains even though all parameters contain estimation errors.
In this paper, a parametrization of all distributed controllers based on the gradient-flow method is presented for networked multi-agent systems. By using the proposed parametrization, the first step in designing controllers will be to present a class of distributed controllers. Then, desired controllers are designed by determining the rest of freedom of controllers, which is represented by free parameters, according to tasks. The new design procedure removes the trial-and-error to keep the distributedness of controllers from conventional design methods. The proposed parametrization will be a strong tool to assist in designing distributed controllers for various kinds of tasks.
This paper investigates robust stability analysis for gene regulatory networks with cyclic interconnections where dynamics of each gene expression has a certain degree of uncertainty. By considering a class of perturbation, we treat the heterogeneity of gene's dynamics, and derive necessary and sufficient conditions for robust stability. To this end, we first show a graphical condition for robust stability based on a robustness analysis scheme for large-scale systems presented in a previous work. A key feature of the graphical condition is that robust stability is systematically confirmed by drawing elementary shapes that are determined by network structure, gene's dynamics and its uncertainty bounds. Moreover, it is shown that the criterion can be greatly simplified by using monotone properties of gene's dynamics. This reduction enables us to derive an analytic condition for robust stability, which is a main result of this paper. Finally, the results are interpreted from a biological viewpoint, and they are verified by numerical simulations.
This paper describes a methodology to build a virtual metrology (VM) model for semiconductor chemical mechanical polishing (CMP) process control. The VM model predicts the polishing rate based on equipment-derived data as soon as allowed, and immediately applies the results to advanced process control (APC). The proposed methodology uses Markov chain Monte Carlo (MCMC) methods to build an analytical model with many parameters for individual consumed materials from historical data in small quantities. The mutual interference of two kinds of consumed materials: dresser and pad are modeled in a form of multilevel predictive model. The methodology uses MCMC methods again to identify the multilevel predictive model taking into account the assumed operation of an actual manufacturing line, for instance, using preliminary test result, learning a model parameter online, and being affected by metrology lag as disturbance. The simulation results show the APC with the proposed VM model is low sensitivity to metrology lag and high precision on polishing amount control.
This article analyzes the validity of relationship banking through agent-based modeling. In the analysis, we especially focus on the relationship between economic conditions and both lenders' and borrowers' behaviors. As a result of intensive experiments, we made the following interesting findings: (1) Relationship banking contributes to reducing bad loan; (2) relationship banking is more effective in enhancing the market growth compared to transaction banking, when borrowers' sales scale is large; (3) keener competition among lenders may bring inefficiency to the market.
We proposed a new flocking model uniting two neighborhoods which are the metric and the topological distance. In our model, the flock of our model can change their direction without any external noise by switching between two interactions. Furthermore, our model can succeed to explain the recent empirical result, which is called scale-free correlation. Finally, we also proposed the new aspect of the fluctuation in the flocking behavior.
Localization and tracking of humans are essential research topics in robotics. In particular, Sound Source Localization (SSL) has been of great interest. Despite the numerous reported methods, SSL in a real environment had mainly three issues; robustness against noise with high power, no framework for selective listening to sound sources, and tracking of inactive and/or noisy sound sources. For the first issue, we extended Multiple SIgnal Classification by incorporating Generalized Eigen Value Decomposition (GEVD-MUSIC) so that it can deal with high power noise and can select target sound sources. For the second issue, we proposed Sound Source Identification (SSI) based on hierarchical Gaussian mixture models and integrated it with GEVD-MUSIC to realize a function to listen to a specific sound source according to the sort of the sound source. For the third issue, auditory and visual human tracking were integrated using particle filtering. These three techniques are integrated into an intelligent human tracking system. Experimental results showed that integration of SSL and SSI successfully achieved human tracking only by audition, and the audio-visual integration showed considerable improvement in tracking by compensating the loss of auditory or visual information.
This paper aims at design of network control system for the remote control of robot. As the system includes a communication channel, quantization is required to satisfy communication capacity limitation. Dynamic quantizer is a kind of quantization methods and has been studied in control engineering field. Optimal quantizing width designed of dynamic has been designed based on invariant sets. However, quantizing width of dynamic quantizer designed based on invariant sets has maintainability than one of designed based on reachable sets and big maintainability and poor control performance. We need to design quantizing width of dynamic quantizer based on reachable sets. In this study, we propose design method of quantizing width of dynamic quantizer based on reachable sets. The effectiveness is shown by numerical example.