Title of the Paper: Optimal Control and
Filtering of Weakly Coupled Linear Discrete Stochastic Systems by The
Eigenvector Approach
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Authors: Naser Prljaca, Zoran Gajic
Abstract: In this paper the regulator and filter algebraic Riccati equations,
corresponding to the steady state optimal control and filtering of weakly
coupled linear discrete stochastic systems are solved in terms of
reduced-order sub problems by using the eigenvector approach. The
eigenvector method outperforms iterative methods (fixed point iterations,
Newton method) of solutions to reduced-order sub problems in case of higher
level of coupling between subsystems. In such cases the iterative methods
could fail to produce solutions of the corresponding algebraic Riccati
equations.
Keywords: Optimal control, Linear discrete stochastic systems, Weakly coupled
systems, Order reduction, Eigenvector method
Title of the Paper: Implementation and Comparison
of Contemporary Data ClusteringTechniques for a Multi-Compressor System: a
Case Study
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Authors: Gursewak S. Brar,
Yadwinder S. Brar, Yaduvir Singh
Abstract: This paper gives the implementation and deployment of fuzzy clustering algorithm applied to a
process control data along with its comparison to various other clustering algorithms. In this paper, the analysis
is carried out for the data as obtained from a multi-compressor system based on the factor of keeping the
maximum weighted square error at the minimum level. Also, this paper consists of an algorithm, which groups
the data according to fuzzy clustering, considering the intermediate values between zero and one. The paper
also outlines the comparison among other clustering algorithms on the basis of various validation parameters
there by telling us the importance of fuzzy clustering, which considers all the ambiguity in data to be a part of
n- clusters, giving an extra attribute of membership function. Keywords:
Data clustering, Data clustering Algorithms, Data mining, Fuzzy Clustering,
Multi-Compressor
Title of the Paper: Function Approximation Based Augmented Backstepping Control
for an Induction Machine
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Authors: Mohammed Belkheiri, Fares
Boudjema
Abstract: A new control approach is proposed to address the tracking problem of an induction machine based on
a modified field-oriented control (FOC) method. In this approach, one relies first on a partially known model to
the system to be controlled using a backstepping control strategy. The obtained controller is then augmented by an
online neural network that serves as an approximator for the neglected dynamics and modeling errors. The proposed
approach is systematic, and exploits the known nonlinear dynamics to derive the stepwise virtual stabilizing
control laws. At the final step, an augmented Lyapunov function is introduced to derive the adaptation laws of the
network weights. The effectiveness of the proposed controller is demonstrated through computer simulation. Keywords:
Induction machine, Nonlinear adaptive control, FOC, backstepping, Neural
networks, Function Approximation.
Title of the Paper: Performance of a Research Prototype Humanoid Robot Bonten-Maru II
to Attain Human-Like Motions
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Authors: Hanafiah Yussof, Mitsuhiro Yamano,
Yasuo Nasu, Masahiro Ohka
Abstract: This report presents development of basic human-like motions using a research prototype 21-dof
humanoid robot called Bonten-Maru II. The aim is to create suitable motion trajectories towards application of
humanoid robots in real environments. Kinematical analysis of 3-dof arm and 6-dof leg were presented to
generate trajectory in the robot’s arms and legs. To realize human-like motions, we proposed navigation
method based on contact interaction for humanoid robot to recognize its surrounding by grasping object surface
and then correcting its locomotion direction. We also proposed methods to avoid high and low obstacles.
Finally, we present crawling motions which can be applied during operation in emergency sites. The
experimental results utilizing Bonten-Maru II revealed good performance of the robot when performing humanlike
motions in the proposed navigation method, obstacle avoidance, and crawling motions. Keywords:
Humanoid robot, human-like motions, trajectory generation, kinematics, contact-based
navigation, obstacle avoidance, crawling motion
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