Coupled operational optimization of smart valve system subject to different approach angles of a pipe contraction

Machiani, Sahar Ghanipoor; Ayoubi, Mohammad A.; Nataraj, C.

doi:10.1007/s00158-016-1554-7

Cited by 9 publications

(12 citation statements)

References 25 publications

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“…Note that the immediate focus of this research work is on reducing cumbersome computational burden of optimization efforts associated with high-DOF robots including Baxter. We hence propose and utilize the S-shaped trajectory (here tanhð:Þ), based on our previous efforts for operational optimization of smart valves network [45][46][47][48], which is highly compatible with the actual motion of Baxter's joints. From another aspect, using conventional trajectories, including Spline and B ezier in addition to polynomials generating S-shaped ones, expectedly imposes more variables to be optimized with respect to the joint-space optimization; we inevitably need high-order polynomials to generate such a smooth S-shaped trajectory.…”

Section: Trajectory Optimizationmentioning

confidence: 99%

Multivariable Extremum Seeking for Joint-Space Trajectory Optimization of a High-Degrees-of-Freedom Robot

Bagheri

Krstić

2018

Journal of Dynamic Systems, Measurement, and Control

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In this paper, a novel analytical coupled trajectory optimization of a seven degrees-of-freedom (7DOF) Baxter manipulator utilizing extremum seeking (ES) approach is presented. The robotic manipulators are used in network-based industrial units, and even homes, by expending a significant lumped amount of energy, and therefore, optimal trajectories need to be generated to address efficiency issues. These robots are typically operated for thousands of cycles resulting in a considerable cost of operation. First, coupled dynamic equations are derived using the Lagrangian method and experimentally validated to examine the accuracy of the model. Then, global design sensitivity analysis is performed to investigate the effects of changes of optimization variables on the cost function leading to select the most effective ones. We examine a discrete-time multivariable gradient-based ES scheme enforcing operational time and torque saturation constraints in order to minimize the lumped amount of energy consumed in a path given; therefore, time-energy optimization would not be the immediate focus of this research effort. The results are compared with those of a global heuristic genetic algorithm (GA) to discuss the locality/globality of optimal solutions. Finally, the optimal trajectory is experimentally implemented to be thoroughly compared with the inefficient one. The results reveal that the proposed scheme yields the minimum energy consumption in addition to overcoming the robot's jerky motion observed in an inefficient path.

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Section: Trajectory Optimizationmentioning

confidence: 99%

Multivariable Extremum Seeking for Joint-Space Trajectory Optimization of a High-Degrees-of-Freedom Robot

Bagheri

Krstić

2018

Journal of Dynamic Systems, Measurement, and Control

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“…The importance of the optimal operation can be visualized through a network of robots operating simultaneously to carry out a specific task defined; we have reported another effort of the interconnected operational optimization in [4] for the so-called "Smart Valves Network" [5][6][7]. The robot manipulator, which is being analyzed in this research work, is operated for thousands of cycles in industries and even homes as a reliable servant for disabled patients.…”

Section: Introductionmentioning

confidence: 99%

Experimental and Novel Analytical Trajectory Optimization of a 7-DOF Baxter Robot: Global Design Sensitivity and Step Size Analyses

Bagheri

Morsi

2017

Volume 1: Aerospace Applications; Advances in Control Design Methods; Bio Engineering Applications; Advances in Non-Linear Cont

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In this paper, we present a novel nonlinear analytical coupled trajectory optimization of a 7-DOF Baxter manipulator validated through experimental work utilizing global optimization tools. The robotic manipulators used in network-based applications of industrial units and even homes, for disabled patients, spend significant lumped amount of energy and therefore, optimal trajectories need to be generated to address efficiency issues. We here examine both heuristic (Genetics) and gradient based (GlobalSearch) algorithms for a novel approach of “S-Shaped” trajectory (unlike conventional polynomials), to avoid being trapped in several possible local minima along with yielding minimal computational cost, enforcing operational time and torque saturation constraints. The global schemes are utilized in minimizing the lumped amount of energy consumed in a nominal path given in the collision-free joint space except an impact between the robot’s end effector and a target object for the nominal operation. Note that such robots are typically operated for thousands of cycles resulting in a considerable cost of operation. Due to the expected computational cost of such global optimization algorithms, step size analysis is carried out to minimize both the computational cost (iteration) and possibly cost function by finding an optimal step size. Global design sensitivity analysis is also performed to examine the effects of changes of optimization variables on the cost function defined.

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“…We have reported broad analytical and experimental studies [1][2][3][4][5][6][7][8][9][10][11][12][13] for both an isolated actuator-valve arrangement and a network of two interconnected solenoid actuated butterfly valves operating in series. A novel third-order nondimensional analytical model of the single solenoid actuated butterfly valve was derived dealing with the coupled nonlinear magnetic, hydrodynamic, and bearing torques [8].…”

Section: Introductionmentioning

confidence: 99%

“…The coupled design optimization was then carried out for the interconnected sets using global optimization tools [2,11,12], which yielded upward of 13% energy savings. A constrained optimization problem was solved with respect to the parameters' bounds determined through the nonlinear dynamic analysis [1,3]. We, for the first time, captured chaotic and hyperchaotic dynamics of the coupled sets for some critical parameters and initial conditions.…”

Section: Introductionmentioning

confidence: 99%

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An Adaptive Centralized Approach to Control Chaotic and Hyperchaotic Dynamics of Smart Valves Network

Ashrafiuon

Ayoubi

2017

Journal of Computational and Nonlinear Dynamics

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Catastrophic chaotic and hyperchaotic dynamical behaviors have been experimentally observed in the so-called “smart valves” network, given certain critical parameters and initial conditions. The centralized network-based control of these coupled systems may effectively mitigate the harmful dynamics of the valve-actuator configuration which can be potentially caused by a remote set and would gradually affect the whole network. In this work, we address the centralized control of two bi-directional solenoid actuated butterfly valves dynamically coupled in series subject to the chaotic and hyperchaotic dynamics. An interconnected adaptive scheme is developed and examined to vanish both the chaotic and hyperchaotic dynamics and return the coupled network to its safe domain of operation.

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Coupled operational optimization of smart valve system subject to different approach angles of a pipe contraction

Cited by 9 publications

References 25 publications

Multivariable Extremum Seeking for Joint-Space Trajectory Optimization of a High-Degrees-of-Freedom Robot

Multivariable Extremum Seeking for Joint-Space Trajectory Optimization of a High-Degrees-of-Freedom Robot

Experimental and Novel Analytical Trajectory Optimization of a 7-DOF Baxter Robot: Global Design Sensitivity and Step Size Analyses

An Adaptive Centralized Approach to Control Chaotic and Hyperchaotic Dynamics of Smart Valves Network

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