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Book ; Online: Learning to Control under Uncertainty with Data-Based Iterative Linear Quadratic Regulator

Wang, Ran / Goyal, Raman / Chakravorty, Suman

2023

Abstract: This paper studies the learning-to-control problem under process and sensing uncertainties for dynamical systems. In our previous work, we developed a data-based generalization of the iterative linear quadratic regulator (iLQR) to design closed-loop ... ...

Abstract	This paper studies the learning-to-control problem under process and sensing uncertainties for dynamical systems. In our previous work, we developed a data-based generalization of the iterative linear quadratic regulator (iLQR) to design closed-loop feedback control for high-dimensional dynamical systems with partial state observation. This method required perfect simulation rollouts which are not realistic in real applications. In this work, we briefly introduce this method and explore its efficacy under process and sensing uncertainties. We prove that in the fully observed case where the system dynamics are corrupted with noise but the measurements are perfect, it still converges to the global minimum. However, in the partially observed case where both process and measurement noise exist in the system, this method converges to a biased "optimum". Thus multiple rollouts need to be averaged to retrieve the true optimum. The analysis is verified in two nonlinear robotic examples simulated in the above cases.
Keywords	Computer Science - Robotics ; Electrical Engineering and Systems Science - Systems and Control ; Mathematics - Dynamical Systems ; Mathematics - Optimization and Control
Subject code	515
Publishing date	2023-11-08
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: An Optimal Solution to Infinite Horizon Nonlinear Control Problems

Mohamed, Mohamed Naveed Gul / Goyal, Raman / Chakravorty, Suman

2023

Abstract: In this paper, we consider the infinite horizon optimal control problem for nonlinear systems. Under the conditions of controllability of the linearized system around the origin, and nonlinear controllability of the system to a terminal set containing ... ...

Abstract	In this paper, we consider the infinite horizon optimal control problem for nonlinear systems. Under the conditions of controllability of the linearized system around the origin, and nonlinear controllability of the system to a terminal set containing the origin, we establish an approximate regularized solution approach consisting of a ``finite free final time" optimal transfer problem to the terminal set, and an infinite horizon linear regulation problem within the terminal set, that is shown to render the origin globally asymptotically stable. Further, we show that the approximations converge to the true optimal cost function as the size of the terminal set decreases to zero. The approach is empirically evaluated on the pendulum and cart-pole swing-up problems to show that the finite time transfer is far shorter than the effective horizon required to solve the infinite horizon problem without the proposed regularization.
Keywords	Mathematics - Optimization and Control ; Electrical Engineering and Systems Science - Systems and Control
Subject code	515
Publishing date	2023-04-01
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Calcium dynamics at the neural cell primary cilium regulate Hedgehog signaling-dependent neurogenesis in the embryonic neural tube.

Shim, Sangwoo / Goyal, Raman / Panoutsopoulos, Alexios A / Balashova, Olga A / Lee, David / Borodinsky, Laura N

Proceedings of the National Academy of Sciences of the United States of America

2023 Volume 120, Issue 23, Page(s) e2220037120

Abstract: The balance between neural stem cell proliferation and neuronal differentiation is paramount for the appropriate development of the nervous system. Sonic hedgehog (Shh) is known to sequentially promote cell proliferation and specification of neuronal ... ...

Abstract	The balance between neural stem cell proliferation and neuronal differentiation is paramount for the appropriate development of the nervous system. Sonic hedgehog (Shh) is known to sequentially promote cell proliferation and specification of neuronal phenotypes, but the signaling mechanisms responsible for the developmental switch from mitogenic to neurogenic have remained unclear. Here, we show that Shh enhances Ca
MeSH term(s)	Calcium/metabolism ; Cell Differentiation ; Cilia/metabolism ; Hedgehog Proteins/metabolism ; Neural Tube/metabolism ; Neurogenesis/physiology ; Xenopus laevis ; Animals ; Xenopus Proteins
Chemical Substances	Calcium (SY7Q814VUP) ; Hedgehog Proteins ; Shh protein, Xenopus ; Xenopus Proteins
Language	English
Publishing date	2023-05-30
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	209104-5
ISSN	1091-6490 ; 0027-8424
ISSN (online)	1091-6490
ISSN	0027-8424
DOI	10.1073/pnas.2220037120
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Book ; Online: A Data-Driven Modeling and Control Framework for Physics-Based Building Emulators

Song, Chihyeon / Sharma, Aayushman / Goyal, Raman / Brito, Alejandro / Mostafavi, Saman

2023

Abstract: We present a data-driven modeling and control framework for physics-based building emulators. Our approach comprises: (a) Offline training of differentiable surrogate models that speed up model evaluations, provide cheap gradients, and have good ... ...

Abstract	We present a data-driven modeling and control framework for physics-based building emulators. Our approach comprises: (a) Offline training of differentiable surrogate models that speed up model evaluations, provide cheap gradients, and have good predictive accuracy for the receding horizon in Model Predictive Control (MPC) and (b) Formulating and solving nonlinear building HVAC MPC problems. We extensively verify the modeling and control performance using multiple surrogate models and optimization frameworks for different available test cases in the Building Optimization Testing Framework (BOPTEST). The framework is compatible with other modeling techniques and customizable with different control formulations. The modularity makes the approach future-proof for test cases currently in development for physics-based building emulators and provides a path toward prototyping predictive controllers in large buildings.
Keywords	Electrical Engineering and Systems Science - Systems and Control ; Computer Science - Artificial Intelligence ; Computer Science - Machine Learning
Subject code	690
Publishing date	2023-01-31
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: From Neural Tube Formation Through the Differentiation of Spinal Cord Neurons: Ion Channels in Action During Neural Development.

Goyal, Raman / Spencer, Kira A / Borodinsky, Laura N

Frontiers in molecular neuroscience

2020 Volume 13, Page(s) 62

Abstract: Ion channels are expressed throughout nervous system development. The type and diversity of conductances and gating mechanisms vary at different developmental stages and with the progressive maturational status of neural cells. The variety of ion ... ...

Abstract	Ion channels are expressed throughout nervous system development. The type and diversity of conductances and gating mechanisms vary at different developmental stages and with the progressive maturational status of neural cells. The variety of ion channels allows for distinct signaling mechanisms in developing neural cells that in turn regulate the needed cellular processes taking place during each developmental period. These include neural cell proliferation and neuronal differentiation, which are crucial for developmental events ranging from the earliest steps of morphogenesis of the neural tube through the establishment of neuronal circuits. Here, we compile studies assessing the ontogeny of ionic currents in the developing nervous system. We then review work demonstrating a role for ion channels in neural tube formation, to underscore the necessity of the signaling downstream ion channels even at the earliest stages of neural development. We discuss the function of ion channels in neural cell proliferation and neuronal differentiation and conclude with how the regulation of all these morphogenetic and cellular processes by electrical activity enables the appropriate development of the nervous system and the establishment of functional circuits adapted to respond to a changing environment.
Language	English
Publishing date	2020-04-24
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2452967-9
ISSN	1662-5099
ISSN	1662-5099
DOI	10.3389/fnmol.2020.00062
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Article: Behavioral reasoning theory (BRT) perspectives on E-waste recycling and management

Dhir, Amandeep / Koshta, Nitin / Goyal, Raman Kumar / Sakashita, Mototaka / Almotairi, Mohammad

Journal of cleaner production. 2021 Jan. 20, v. 280

2021

Abstract: Each year, millions of tons of electronic waste (or e-waste) are generated worldwide, thus, fueling concerns among scholars, practitioners, policymakers, and governments about e-waste recycling and management. The past few years have witnessed a growing ... ...

Abstract	Each year, millions of tons of electronic waste (or e-waste) are generated worldwide, thus, fueling concerns among scholars, practitioners, policymakers, and governments about e-waste recycling and management. The past few years have witnessed a growing interest among scholars to examine the behavioral issues concerning e-waste recycling. However, most of the existing studies have focused on adopting e-waste recycling and related innovations. It is already known that ‘reasons for’ and ‘reasons against’ the adoption of any innovation are quantitatively different. The current study bridges this gap by utilizing a novel consumer behavior framework called behavioral reasoning theory (BRT) to study e-waste recycling attitudes and intentions. The study examined the relative influence of ‘reasons for’ and ‘reasons against’ in predicting attitude and intentions within the context of e-waste recycling by using a single framework. The developed model was tested using structural equation modeling with 774 Japanese consumers. The study also examined the moderating role of environmental assessment and environmental concerns in influencing the studied associations. The results suggest that ‘reasons for’ was positively associated with attitude and intentions. The consumer values shared negative associations only with ‘reasons against.’ The study findings offer interesting insights for service providers, policymakers, and governments.
Keywords	attitudes and opinions ; consumer behavior ; electronic wastes ; environmental assessment ; models ; prediction ; recycling ; structural equation modeling
Language	English
Dates of publication	2021-0120
Publishing place	Elsevier Ltd
Document type	Article
ISSN	0959-6526
DOI	10.1016/j.jclepro.2020.124269
Database	NAL-Catalogue (AGRICOLA)

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Book ; Online: Model-based Shape Control of Tensegrity Robotic Systems

Goyal, Raman / Majji, Manoranjan / Skelton, Robert E.

2020

Abstract: This paper proposes a model-based approach to control the shape of a tensegrity system by driving its node position locations. The nonlinear dynamics of the tensegrity system is used to regulate position, velocity, and acceleration to the specified ... ...

Abstract	This paper proposes a model-based approach to control the shape of a tensegrity system by driving its node position locations. The nonlinear dynamics of the tensegrity system is used to regulate position, velocity, and acceleration to the specified reference trajectory. State feedback control design is used to obtain the solution for the control variable as a linear programming problem. Shape control for the gyroscopic tensegrity systems is discussed, and it is observed that these systems increase the reachable space for the structure by providing independent control over certain rotational degrees of freedom. Disturbance rejection of the tensegrity system is further studied in the paper. A methodology to calculate the control gains to bound the errors for five different types of problems is provided. The formulation uses a Linear Matrix Inequality (LMI) approach to stipulate the desired performance bounds on the error for $\mathcal{H}_\infty$, generalized $\mathcal{H}_2$, LQR, covariance control and stabilizing control problem. A high degree of freedom tensegrity $T_2D_1$ robotic arm is used as an example to show the efficacy of the formulation.
Keywords	Computer Science - Robotics ; Electrical Engineering and Systems Science - Systems and Control
Subject code	629
Publishing date	2020-11-07
Publishing country	us
Document type	Book ; Online
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Article ; Online: Localized force application reveals mechanically sensitive domains of Piezo1.

Wu, Jason / Goyal, Raman / Grandl, Jörg

Nature communications

2016 Volume 7, Page(s) 12939

Abstract: Piezos are mechanically activated ion channels that function as sensors of touch and pressure in various cell types. However, the precise mechanism and structures mediating mechanical activation and subsequent inactivation have not yet been identified. ... ...

Abstract	Piezos are mechanically activated ion channels that function as sensors of touch and pressure in various cell types. However, the precise mechanism and structures mediating mechanical activation and subsequent inactivation have not yet been identified. Here we use magnetic nanoparticles as localized transducers of mechanical force in combination with pressure-clamp electrophysiology to identify mechanically sensitive domains important for activation and inactivation.
MeSH term(s)	Animals ; Calibration ; Chickens ; Electrophysiological Phenomena ; HEK293 Cells ; Humans ; Ion Channels/chemistry ; Ions ; Macaca mulatta ; Magnetics ; Mechanical Phenomena ; Mechanotransduction, Cellular ; Mice ; Nanoparticles/chemistry ; Nanotechnology ; Pressure ; Protein Domains ; Rats ; Signal Transduction ; Wolves
Chemical Substances	Ion Channels ; Ions ; PIEZO1 protein, human
Language	English
Publishing date	2016-10-03
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ISSN	2041-1723
ISSN (online)	2041-1723
DOI	10.1038/ncomms12939
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Book ; Online: On the Convergence of Reinforcement Learning in Nonlinear Continuous State Space Problems

Goyal, Raman / Chakravorty, Suman / Wang, Ran / Mohamed, Mohamed Naveed Gul

2020

Abstract: We consider the problem of Reinforcement Learning for nonlinear stochastic dynamical systems. We show that in the RL setting, there is an inherent ``Curse of Variance" in addition to Bellman's infamous ``Curse of Dimensionality", in particular, we show ... ...

Abstract	We consider the problem of Reinforcement Learning for nonlinear stochastic dynamical systems. We show that in the RL setting, there is an inherent ``Curse of Variance" in addition to Bellman's infamous ``Curse of Dimensionality", in particular, we show that the variance in the solution grows factorial-exponentially in the order of the approximation. A fundamental consequence is that this precludes the search for anything other than ``local" feedback solutions in RL, in order to control the explosive variance growth, and thus, ensure accuracy. We further show that the deterministic optimal control has a perturbation structure, in that the higher order terms do not affect the calculation of lower order terms, which can be utilized in RL to get accurate local solutions.
Keywords	Computer Science - Machine Learning ; Electrical Engineering and Systems Science - Systems and Control
Publishing date	2020-11-21
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: On the Optimal Feedback Law in Stochastic Optimal Nonlinear Control

Mohamed, Mohamed Naveed Gul / Chakravorty, Suman / Goyal, Raman / Wang, Ran

2020

Abstract: We consider the problem of nonlinear stochastic optimal control. This problem is thought to be fundamentally intractable owing to Bellman's infamous "curse of dimensionality". We present a result that shows that repeatedly solving an open-loop ... ...

Abstract	We consider the problem of nonlinear stochastic optimal control. This problem is thought to be fundamentally intractable owing to Bellman's infamous "curse of dimensionality". We present a result that shows that repeatedly solving an open-loop deterministic problem from the current state, similar to Model Predictive Control (MPC), results in a feedback policy that is $O(\epsilon^4)$ near to the true global stochastic optimal policy. Furthermore, empirical results show that solving the Stochastic Dynamic Programming (DP) problem is highly susceptible to noise, even when tractable, and in practice, the MPC-type feedback law offers superior performance even for stochastic systems. Comment: arXiv admin note: substantial text overlap with arXiv:2002.10505, arXiv:2002.09478
Keywords	Electrical Engineering and Systems Science - Systems and Control ; Computer Science - Robotics
Publishing date	2020-04-01
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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