[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

Decentralized adaptive robust control design : the uncertainty is time varying

Two classes of decentralized robust controls, namely, nonadaptive and adaptive, are presented for a class of uncertain interconnected nonlinear systems. The uncertainty considered here is time-varying and appears at each system and interconnections. No statistical information of the uncertainty is invoked. The possible bound of the uncertainty is assumed to be known for the nonadaptive robust control. For the adaptive control, the bound is unknown and the adaptive scheme tracks the bound. Compared with nonadaptive control, more assumptions are imposed on the structure of the uncertainty for the use of adaptive control. These assumptions include that no uncertainty appears in the input matrix. >

Decentralized control of nonlinear uncertain systems with bounded uncertainties

The problem of stabilizing a class of linear uncertain systems by using estimated state feedback is discussed. The system possesses uncertainty which is time-varying. The uncertainty is unknown, but lies within a prescribed set (hence it is bounded). No statistical information about the uncertainty is imposed. The estimated state is constructed via an observer. Necessary and sufficient conditions for quadratic stabilizability are formulated. The controller synthesis and stability analysis are investigated by a two-level optimization process. The inner level searches for the minimum and can be achieved by checking a finite number of vertices if the bounding set is a hyperpolyhedron. The outer level can reach the global maximum. The result is believed to be practical (in the sense that it can be implemented for nontrivial physical systems) and nonconservative. >

Combined controller-observer design for uncertain systems: using necessary and sufficient conditions

Motion control for an uncertain swarm robot system consisting of N robots is considered. The robots interact with each other through attractions and repulsions, which mimic some biological swarm systems. The uncertainty in the system is possibly fast time varying and bounded with unknown bound, which is assumed to be within a prescribed fuzzy set. On this premise, an adaptive robust control is proposed. Based on the proposed control, an optimal design problem under the fuzzy description of the uncertainty is formulated. This optimal problem is proven to be tractable, and the solution is unique. The solution to this optimal problem is expressed in the closed form. The performance of the resulting control is twofold. First, it assures the swarm robot system deterministic performances (uniform boundedness and uniform ultimate boundedness) regardless of the actual value of the uncertainty. Second, the minimization of a fuzzy-based performance index is assured. Therefore, the optimal design problem of the adaptive robust control for fuzzy swarm robot systems is completely solved.

Optimal Design of Adaptive Robust Control for Fuzzy Swarm Robot Systems

A novel class of high-order robust controls is presented for uncertain fuzzy systems in this article. The optimal tunable parameters are also obtained based on the Stackelberg game theory. First, a dynamical system structure is formulated with uncertainty. The uncertain portion in the system is bounded, nonlinear, and time-varying which is within prescribed fuzzy set. Thus, this is a fuzzy system. Then, the proof based on the Lyapunov minimax approach shows that the novel high-order robust controls are able to assure deterministic system performance, which is uniform boundedness and ultimate uniform boundedness. Furthermore, the optimal choice of the tunable parameters in the control is considered. We creatively apply the Stackelberg strategy to solving the optimization problem. Two parameters are regarded as leader and follower in a sequential game, respectively. Based on the Stackelberg game rules, we are able to design different cost functions for different parameters. The cost functions include both performance measures and control cost. Finally, the simulations of an electronic throttle system are presented for demonstration.

Ye-Hwa Chen

Papers

Decentralized adaptive robust control design : the uncertainty is time varying

Decentralized control of nonlinear uncertain systems with bounded uncertainties

Combined controller-observer design for uncertain systems: using necessary and sufficient conditions

Optimal Design of Adaptive Robust Control for Fuzzy Swarm Robot Systems

Stackelberg Game Theory-Based Optimization of High-Order Robust Control for Fuzzy Dynamical Systems