Matrix Differential Calculus with Applications in Statistics and Econometrics

Water network synthesis has been an active area of research for the past one and a half decades. Many think that the technology reached a mature stage in the late 1990s, especially for the insight-based technique based on pinch analysis. The only review for the field dates back to 2000. However, many new papers published in this century reveal that new research gaps are found and more works were carried out to address the limitations of the “old” techniques. The main objective of this review is to provide a state-of-the-art overview of the insight-based techniques developed in the 21st century, particularly those developed for single impurity network of the fixed flow rate problems. Comparisons were also made between these recent techniques and those developed for the fixed load problems in the past century. Various flow rate targeting techniques developed for water reuse/recycle, regeneration, and wastewater treatment are reviewed in detail, along with the network design techniques that achieve the estab...

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State-of-the-Art Review of Pinch Analysis Techniques for Water Network Synthesis

An algorithm is proposed to target the minimum freshwater for fixed flow rate (FF) problems in single-contaminant water networks. The approach is based on an extension of the limiting composite curve concept proposed earlier for fixed contaminant-load (FC) problems. The targeting method is elegant, noniterative, and can be applied to FF problems involving regeneration to minimize waste discharge. To design networks that achieve the minimum freshwater targets set for FF problems, an algorithm is presented based on the principle of nearest neighbors. The principle simply states that the sources to be chosen to satisfy a particular water demand must be the nearest available neighbors in terms of contaminant concentration. A significant advantage of the approach is that the same targeting concepts can be profitably used to determine the minimum makeup utility in hydrogen networks. Furthermore, hydrogen networks may be designed by the unified conceptual approach using the nearest neighbors algorithm. The hydrogen networks may then be evolved to account for the pressure constraints imposed by compressors or improved by regeneration through purification processes such as pressure-swing adsorption. © 2005 American Institute of Chemical Engineers AIChE J, 2006

Unified conceptual approach to targeting and design of water and hydrogen networks

Process Integration supporting process design, integration and optimisation has been around for more than 40 years. Its development has been closely related to developing the Chemical Engineering, implementation of mathematical modelling and the application of information technology. Its development has been accelerating as the methodology has been able to provide answers and support for important issues regarding economic development—energy, water and resources better utilisation and savings. This contribution is targeted towards a short overview of recent achievements and future challenges.

Recent developments in Process Integration

A method to learn and reproduce robot force interactions in a human–robot interaction setting is proposed. The method allows a robotic manipulator to learn to perform tasks that require exerting forces on external objects by interacting with a human operator in an unstructured environment. This is achieved by learning two aspects of a task: positional and force profiles. The positional profile is obtained from task demonstrations via kinesthetic teaching. The force profile is obtained from additional demonstrations via a haptic device. A human teacher uses the haptic device to input the desired forces that the robot should exert on external objects during the task execution. The two profiles are encoded as a mixture of dynamical systems, which is used to reproduce the task satisfying both the positional and force profiles. An active control strategy based on task-space control with variable stiffness is then proposed to reproduce the skill. The method is demonstrated with two experiments in which the robot learns an ironing task and a door-opening task.

Imitation Learning of Positional and Force Skills Demonstrated

Targeting and design of water networks for fixed flowrate and fixed contaminant load operations

Design and evolution of water networks by source shifts

On the intraday dynamics of oil price and exchange rate: What can we learn from China and India?

Grasping of novel objects in pick and place applications is a fundamental and challenging problem in robotics, specifically for complex-shaped objects. It is observed that the well-known strategies like i) grasping from the centroid of object and ii) grasping along the major axis of the object often fails for complex-shaped objects. In this paper, a realtime grasp pose estimation strategy for novel objects in robotic pick and place applications is proposed. The proposed technique estimates the object contour in the point cloud and predicts the grasp pose along with the object skeleton in the image plane. The technique is tested for the objects like ball container, hand weight, tennis ball and even for complex shape objects like blower (non-convex shape). It is observed that the proposed strategy performs very well for complex shaped objects and predicts the valid grasp configurations in comparison with the above strategies. The experimental validation of the proposed grasping technique is tested in two scenarios, when the objects are placed distinctly and when the objects are placed in dense clutter. A grasp accuracy of 88.16% and 77.03% respectively are reported. All the experiments are performed with a real UR10 robot manipulator along with WSG-50 two-finger gripper for grasping of objects.

Real-time Grasp Pose Estimation for Novel Objects in Densely Cluttered Environment

Complex and interactive robot manipulation skills, such as playing a game of table tennis against a human opponent, are a novel problem with multifaceted challenges. Accurate dynamic trajectory generation in order to respond to the tennis ball from the opponent and a novel control scheme for robust and high-performance tracking of the ball in such dynamic situations is a prerequisite to winning the game. In this paper, the dynamic movement primitives (DMPs) are employed for the stable generation of dynamic trajectories in the presence of environmental uncertainties such as ball position and velocity, opponent position and velocity and so on. In DMP, kernels parameters need to be found from expert demonstrations using a learning technique. To mitigate environmental uncertainties by accurate reconstruction of novel dynamic trajectories by combining multiple DMPs, we propose a piecewise linear canonical system (PLCS)-based modified DMP in contrast to the standard exponential canonical system (ECS)-based DMP. To enhance effectiveness and performance, a novel learning technique based on Lyapunov stability is embedded with the above-developed formulation. We show that the proposed learning technique is faster, has the best steady state error performance, and requires almost half the kernels than the state of the art. Next, to intercept the dynamic moving ball in real-time using the DMP, a novel control scheme is needed and designed using fuzzy fractional order sliding mode control. The control scheme results in chatter free tracking of the desired trajectories because the control law is free from sgn( $\cdot $ ) function. The tracking control performance is guaranteed theoretically via the Lyapunov approach and also verified through simulations and experiments. Finally, we have developed a complete system (including a vision system for tracking the ball) using a real 4 degrees-of-freedom (DOFs) Barrett Wam robotic arm and show that the proposed overall framework is able to respond to a hanging ball with high accuracy.

Ravi Prakash

Papers

Targeting and design of water networks for fixed flowrate and fixed contaminant load operations

Design and evolution of water networks by source shifts

On the intraday dynamics of oil price and exchange rate: What can we learn from China and India?

Real-time Grasp Pose Estimation for Novel Objects in Densely Cluttered Environment

Dynamic Trajectory Generation and a Robust Controller to Intercept a Moving Ball in a Game Setting