[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Droplet based microfluidics is a rapidly growing interdisciplinary field of research combining soft matter physics, biochemistry and microsystems engineering. Its applications range from fast analytical systems or the synthesis of advanced materials to protein crystallization and biological assays for living cells. Precise control of droplet volumes and reliable manipulation of individual droplets such as coalescence, mixing of their contents, and sorting in combination with fast analysis tools allow us to perform chemical reactions inside the droplets under defined conditions. In this paper, we will review available drop generation and manipulation techniques. The main focus of this review is not to be comprehensive and explain all techniques in great detail but to identify and shed light on similarities and underlying physical principles. Since geometry and wetting properties of the microfluidic channels are crucial factors for droplet generation, we also briefly describe typical device fabrication methods in droplet based microfluidics. Examples of applications and reaction schemes which rely on the discussed manipulation techniques are also presented, such as the fabrication of special materials and biophysical experiments.

https://iopscience.iop.org/article/10.1088/0034-4885/75/1/016601/pdf

Droplet based microfluidics

IEEE transactions on computer-aided design of integrated circuits and systems : a publication of the IEEE Circuits and Systems Society

Feedback systems: Input-output properties

In this paper, a feedback linearization (FL)-based control law made implementable using an extended state observer (ESO) is proposed for the trajectory tracking control of a flexible-joint robotic system. The FL-based controller cannot be implemented unless the full transformed state vector is available. The design also requires exact knowledge of the system model making the controller performance sensitive to uncertainties. To address these issues, an ESO is designed, which estimates the state vector, as well as the uncertainties in an integrated manner. The FL controller uses the states estimated by ESO, and the effect of uncertainties is compensated by augmenting the FL controller with the ESO-estimated uncertainties. The closed-loop stability of the system under the proposed observer-controller structure is established. The effectiveness of the ESO in the estimation of the states and uncertainties and the effectiveness of the FL + ESO controller in tracking are demonstrated through simulations. Lastly, the efficacy of the proposed approach is validated through experimentation on Quanser's flexible-joint module.

Extended-State-Observer-Based Control of Flexible-Joint System With Experimental Validation

A class of dynamical systems with time-varying uncertainty is considered. No statistical information of the uncertainty is imposed. The nominal portion (i.e. the portion without uncertainty) of the system is stabilizable. The uncertainty is either assumed to be matched or not too much far away from matching. Moreover, the uncertainty is to be cone-bounded. The bound is, however, unknown. The control design is only based on the deterministic properties related to the bound of uncertainty. An adaptive scheme is adopted to track the bound. The feedback information is the state with measurement noise. >

Adaptive robust control of uncertain systems

The controllability and the observability of fuzzy dynamical system are studied. The uncertainty of the fuzzy dynamical system is due to the initial condition. The available information on the uncertainty can be described via a membership function. In this paper, we propose a systematic approach to investigate the controllability and the observability of fuzzy dynamical system via the use of the membership function. The concepts of the controllability and the observability in the fuzzy sense are presented via the use of the membership function. The necessary and sufficient conditions for the controllability and the observability of the linear time-variant and time-invariant uncertain system are derived. As a result, the paper lays the foundation for the control of fuzzy dynamical system.

On the Foundations of Fuzzy Dynamical System Theory: Controllability and Observability

This article proposes an optimal indirect approach of constraint-following control for fuzzy mechanical systems. The system contains (possibly fast) time-varying uncertainty that lies in a fuzzy set. It aims at an optimal controller for the system to render bounded constraint-following error such that it can stay within a predetermined bound at all time and be sufficiently small eventually. First, for deterministic performance, the original system is transformed into a constructed system. A deterministic (not the usual if-then rules-based) robust control is then designed for the constructed system to render it to be uniformly bounded and uniformly ultimately bounded, regardless of the uncertainty. Second, for optimal performance, a performance index, including the average fuzzy system performance and control effort, is proposed based on the fuzzy information. An optimal design problem associated with the control gain is then formulated and solved by minimizing the performance index. Finally, it is proved when the constructed system renders uniform boundedness and uniform ultimate boundedness, the original system achieves the desired performance of bounded constraint following.

Regulating Constraint-Following Bound for Fuzzy Mechanical Systems: Indirect Robust Control and Fuzzy Optimal Design.

The constraint following stabilization problem of aerospace mechanical manipulators containing uncertainty is investigated. Due to the inevitable modeling error and external disturbance, there always exists uncertainty. To guarantee that the mechanical system follows prescribed constraints (holonomic or non-holonomic), two classes of adaptive robust controls are proposed. The system performance is represented based on a $\varphi $ -measure. The control scheme consists of two parts: the nominal control part and the adaptive robust control part. By the Udwadia–Kalaba theory, the nominal control is proposed to force the nominal mechanical system to meet the constraints. Furthermore, the adaptive robust control is proposed to address the uncertainty issue, while the adaptation law is proposed to estimate the bounding information of the uncertainty. Under the control, the system is guaranteed to follow the constraint regardless of the uncertainty.

Robust Constraint Following Stabilization for Mechanical Manipulators Containing Uncertainty: An Adaptive $\varphi$ Approach

A new decentralized control is designed for a class of fuzzy complex systems. This system is in the form with dimensionality, uncertainty and information structure constraints. The uncertainty, which is bounded, may be due to the unknown parameters and input disturbance. The control scheme is high-order, while the control design is formulated as a constrained optimization problem, which reflects the system's average fuzzy characteristics. We show that the solution to this optimization problem exists and is unique regardless uncertainties and disturbance. An illustrative example is employed for further verification of this control method.

https://ieeexplore.ieee.org/iel5/6373891/6389889/06390086.pdf

Ye-Hwa Chen

Papers

Adaptive robust control of uncertain systems

On the Foundations of Fuzzy Dynamical System Theory: Controllability and Observability

Regulating Constraint-Following Bound for Fuzzy Mechanical Systems: Indirect Robust Control and Fuzzy Optimal Design.

Robust Constraint Following Stabilization for Mechanical Manipulators Containing Uncertainty: An Adaptive $\varphi$ Approach

Optimal robust decentralized control design for fuzzy complex systems