Control of Microparticle Assembly

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Xun Tang ◽  
Martha A. Grover
Keyword(s):  
Feedback Control ◽  
System Dynamics ◽  
Real Time ◽  
Imaging Techniques ◽  
Open Loop ◽  
Optimal Feedback Control ◽  
Annual Review ◽  
Publication Date ◽  
Colloidal System ◽  
Gravitational Fields

A colloidal system is a large collection of micrometer-sized particles suspended in a liquid, and the state of the system can be measured in real time, using imaging techniques and image processing. The assembly of the particles is driven by interactions between the particles and the surrounding liquid, as well as by external fields, including electromagnetic, flow, and gravitational fields. The dynamics of the many-body system are high-dimensional, nonlinear, and stochastic. However, low-order models are derived in some cases, often using physics-based order parameters, to facilitate studying the system dynamics. With an understanding of the system dynamics, and by manipulating the aforementioned interactions, one can control the assembly process in real time using open-loop and closed-loop feedback control. Theoretical studies and experimental demonstrations of colloidal self-assembly control have been reported, with methods ranging from heuristic rules to model-based optimal feedback control. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Passive optimal feedback control of an articulated flexible arm

2020 ◽  
pp. 107754632095676
Author(s):  
Raja Tebbikh ◽  
Hicham Tebbikh ◽  
Sihem Kechida
Keyword(s):  
Optimal Control ◽  
Feedback Control ◽  
Closed Loop ◽  
Open Loop ◽  
Optimal Feedback Control ◽  
Convolution Operators ◽  
High Frequencies ◽  
Zero Initial Condition ◽  
Flexible Arm ◽  
Euler Bernoulli Beam

This article deals with stabilization and optimal control of an articulated flexible arm by a passive approach. This approach is based on the boundary control of the Euler–Bernoulli beam by means of wave-absorbing feedback. Due to the specific propagative properties of the beam, such controls involve long-memory, non-rational convolution operators. Diffusive realizations of these operators are introduced and used for elaborating an original and efficient wave-absorbing feedback control. The globally passive nature of the closed-loop system gives it the unconditional robustness property, even with the parameters uncertainties of the system. This is not the case in active control, where the system is unstable, because the energy of high frequencies is practically uncontrollable. Our contribution comes in the achievement of optimal control by the diffusion equation. The proposed approach is original in considering a non-zero initial condition of the diffusion as an optimization variable. The optimal arm evolution, in a closed loop, is fixed in an open loop by optimizing a criterion whose variable is the initial diffusion condition. The obtained simulation results clearly illustrate the effectiveness and robustness of the optimal diffusive control.

Optimal Control of a Distributed Parameter, Time-Lagged River Aeration System

1975 ◽  
Vol 97 (2) ◽  
pp. 164-171 ◽  
Author(s):  
M. K. O¨zgo¨ren ◽  
R. W. Longman ◽  
C. A. Cooper
Keyword(s):  
Optimal Control ◽  
Feedback Control ◽  
Open Loop ◽  
Optimal Feedback Control ◽  
Distributed Parameter ◽  
Control Law ◽  
Optimal Controls ◽  
Distributed Parameter System ◽  
Parameter System ◽  
Characteristic Lines

The control of artificial in-stream aeration of polluted rivers with multiple waste effluent sources is treated. The optimal feedback control law for this distributed parameter system is determined by solving the partial differential equations along characteristic lines. In this process the double integral cost functional of the distributed parameter system is reduced to a single integral cost. Because certain measurements are time consuming, the feedback control law is obtained in the presence of observation delay in some but not all of the system variables. The open loop optimal control is then found, showing explicity the effect of changes in any of the effluent sources on the aeration strategy. It is shown that the optimal strategy for a distribution of sources can be written as an affine transformation upon the optimal controls for sources of unit strength.

scholarly journals A unified framework of rapid exponential stability and optimal feedback control for nonlinear systems

2019 ◽  
Vol 11 (3) ◽  
pp. 168781401983320
Author(s):  
Yan Li ◽  
Yuanchun Li
Keyword(s):  
Feedback Control ◽  
Nonlinear Systems ◽  
Exponential Stability ◽  
Real Time ◽  
Lyapunov Functions ◽  
Bellman Equation ◽  
Optimal Feedback Control ◽  
Optimal Feedback ◽  
Hamilton Jacobi Bellman Equation ◽  
Hamilton Jacobi Bellman

A novel framework of rapid exponential stability and optimal feedback control is investigated and analyzed for a class of nonlinear systems through a variant of continuous Lyapunov functions and Hamilton–Jacobi–Bellman equation. Rapid exponential stability means that the trajectories of nonlinear systems converge to equilibrium states in accelerated time. The sufficient conditions of rapid exponential stability are developed using continuous Lyapunov functions for nonlinear systems. Furthermore, according to a variant of continuous Lyapunov functions, a rapid exponential stability is guaranteed which satisfies some canonical conditions and Hamilton–Jacobi–Bellman equation for controlled nonlinear systems. It is can be seen that the solution of Hamilton–Jacobi–Bellman equation is a continuous Lyapunov function, and, therefore, rapid exponential stability and optimality are guaranteed for nonlinear systems. Last, the main result of this article is investigated via a nonlinear model of a spacecraft with one axis of symmetry through simulations and is used to check rapid exponential stability. Moreover, for the disturbance problem of initial point, a rapid exponential stable controller can reject the large-scale disturbances for controlled nonlinear systems. In addition, the proposed optimal feedback controller is applied to the tracking trajectories of 2-degree-of-freedom manipulator, and the numerical results have illustrated high efficiency and robustness in real time. The simulation results demonstrate the use of the rapid exponential stability and optimal feedback approach for real-time nonlinear systems.

Behavior Trees in Robot Control Systems

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Petter Ögren ◽  
Christopher I. Sprague
Keyword(s):  
Control System ◽  
Feedback Control ◽  
Robot Control ◽  
Autonomous Systems ◽  
Research Area ◽  
Annual Review ◽  
Publication Date ◽  
Detailed Knowledge ◽  
Level Control ◽  
Behavior Trees

In this article, we provide a control-theoretic perspective on the research area of behavior trees in robotics. The key idea underlying behavior trees is to make use of modularity, hierarchies, and feedback in order to handle the complexity of a versatile robot control system. Modularity is a well-known tool to handle software complexity by enabling the development, debugging, and extension of separate modules without detailed knowledge of the entire system. A hierarchy of such modules is natural, since robot tasks can often be decomposed into a hierarchy of subtasks. Finally, feedback control is a fundamental tool for handling uncertainties and disturbances in any low-level control system, but in order to enable feedback control on the higher level, where one module decides what submodule to execute, information regarding the progress and applicability of each submodule needs to be shared in the module interfaces. We describe how these three concepts can be used in theoretical analysis, practical design, and extensions and combinations with other ideas from control theory and robotics. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Real-Time Infectious Disease Modeling to Inform Emergency Public Health Decision Making

2022 ◽  
Vol 43 (1) ◽  
Author(s):  
Anna Bershteyn ◽  
Hae-Young Kim ◽  
R. Scott Braithwaite
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Real Time ◽  
Disease Modeling ◽  
Disease Process ◽  
Annual Review ◽  
Publication Date ◽  
Public Health Response ◽  
Response Options ◽  
Infectious Disease Modeling

Infectious disease transmission is a nonlinear process with complex, sometimes unintuitive dynamics. Modeling can transform information about a disease process and its parameters into quantitative projections that help decision makers compare public health response options. However, modelers face methodologic challenges, data challenges, and communication challenges, which are exacerbated under the time constraints of a public health emergency. We review methods, applications, challenges and opportunities for real-time infectious disease modeling during public health emergencies, with examples drawn from the two deadliest pandemics in recent history: HIV/AIDS and coronavirus disease 2019 (COVID-19). Expected final online publication date for the Annual Review of Public Health, Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals The Parameter Variation Problem in State Feedback Control Systems

1965 ◽  
Vol 87 (1) ◽  
pp. 120-124 ◽  
Author(s):  
W. R. Perkins ◽  
J. B. Cruz
Keyword(s):  
Feedback Control ◽  
State Feedback ◽  
Parameter Variation ◽  
Open Loop ◽  
State Feedback Control ◽  
Optimal Feedback Control ◽  
Variation Problem ◽  
Quadratic Performance ◽  
New Interpretation ◽  
Low Sensitivity

The plant-parameter variation problem in multivariable linear systems described by state-vector equations is formulated using a new sensitivity measure. This formulation involves a direct comparison of open-loop and state-feedback performance in the presence of parameter variations and provides a basis for guaranteeing the superiority of the feedback design. Results are obtained for both continuous and discrete multi-input, multi-output systems. Furthermore, it is shown for single-input, multi-output plants that a low-sensitivity design is also an optimal feedback-control design with respect to a quadratic performance index. This provides a new interpretation of a similar result previously obtained by Kalman.

On the Open-Loop and Feedback Processes That Underlie the Formation of Trajectories During Visual and Nonvisual Locomotion in Humans

2009 ◽  
Vol 102 (5) ◽  
pp. 2800-2815 ◽  
Author(s):  
Quang-Cuong Pham ◽  
Halim Hicheur
Keyword(s):  
Feedback Control ◽  
Control Strategies ◽  
Open Loop ◽  
Optimal Feedback Control ◽  
Control Mechanisms ◽  
Experimental Conditions ◽  
Optimal Feedback ◽  
On Line ◽  
Kinematic Properties

We investigated the nature of the control mechanisms at work during goal-oriented locomotion. In particular, we tested the effects of vision, locomotor speed, and the presence of via points on the geometric and kinematic properties of locomotor trajectories. We first observed that the average trajectories recorded in visual and nonvisual locomotion were highly comparable, suggesting the existence of vision-independent processes underlying the formation of locomotor trajectories. Then by analyzing and comparing the variability around the average trajectories across different experimental conditions, we were able to demonstrate the existence of on-line feedback control in both visual and nonvisual locomotion and to clarify the relations between visual and nonvisual control strategies. Based on these insights, we designed a model in which maximum-smoothness and optimal feedback control principles account, respectively, for the open-loop and feedback processes. Taken together, the experimental and modeling findings provide a novel understanding of the nature of the motor, sensory, and “navigational” processes underlying goal-oriented locomotion.

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