Stochastic Optimal Linear Control for Generalized Cost Functions With Time-Invariant Stochastic Parameters.

This study presents the design of feedback controllers for generalized cost functions to deal with stochastic optimal control problems. Target linear systems contain time-invariant stochastic parameters that describe system uncertainty. The cost functions involve nonlinear mappings and polynomial forms of the system states and inputs to express various performance metrics. Unfortunately, these properties cause difficulties in solving the problems. Conventional methods, such as the principle of optimality, are not employed to solve such problems owing to the time-invariant parameters. As opposed to the well-known quadratic functions, handling the generalized cost functions is a complicated task. This study overcomes these challenges by deriving an explicit relation between the cost function and the linear feedback gain of a controller. The derived relation enables the feedback gain to be optimized via a gradient method. A theoretical analysis ensures the convergence of the proposed gradient method. A suboptimal feedback controller is obtained to solve the problem, even for the generalized cost. Furthermore, the controller guarantees robust stability of the feedback system even with the stochastic parameters. It is demonstrated that the proposed cost function can express an expectation of a quadratic cost, risk-sensitive cost, polynomial cost, and input-to-state gain. A numerical simulation shows the effectiveness of the proposed method.

Artificial-intelligence-assisted mass fabrication of nanocantilevers from randomly positioned single carbon nanotubes.

Nanoscale cantilevers (nanocantilevers) made from carbon nanotubes (CNTs) provide tremendous benefits in sensing and electromagnetic applications. This nanoscale structure is generally fabricated using chemical vapor deposition and/or dielectrophoresis, which contain manual, time-consuming processes such as the placing of additional electrodes and careful observation of single-grown CNTs. Here, we demonstrate a simple and Artificial Intelligence (AI)-assisted method for the efficient fabrication of a massive CNT-based nanocantilever. We used randomly positioned single CNTs on the substrate. The trained deep neural network recognizes the CNTs, measures their positions, and determines the edge of the CNT on which an electrode should be clamped to form a nanocantilever. Our experiments demonstrate that the recognition and measurement processes are automatically completed in 2 s, whereas comparable manual processing requires 12 h. Notwithstanding the small measurement error by the trained network (within 200 nm for 90% of the recognized CNTs), more than 34 nanocantilevers were successfully fabricated in one process. Such high accuracy contributes to the development of a massive field emitter using the CNT-based nanocantilever, in which the output current is obtained with a low applied voltage. We further showed the benefit of fabricating massive CNT-nanocantilever-based field emitters for neuromorphic computing. The activation function, which is a key function in a neural network, was physically realized using an individual CNT-based field emitter. The introduced neural network with the CNT-based field emitters recognized handwritten images successfully. We believe that our method can accelerate the research and development of CNT-based nanocantilevers for realizing promising future applications.

Periodic switching of acoustic radiation force with beat created by multitone field.

Acoustic radiation force plays a key role in microfluidic systems for particle and cell manipulation. In this study, we investigate the acoustic radiation force resulting from synthesized ultrasounds that are emitted from multiple sound sources with slightly different oscillation frequencies. Due to the synthesized field, the acoustic radiation force is expressed as the sum of a dc component and harmonics of fundamental frequencies of a few hertz. This induces the beat of the acoustic radiation force. We demonstrate that the synthesized field provides the periodic on/off switching of the acoustic radiation force associated with the one denominational planar standing wave in a straight microfluidic channel. Consequently, our system can temporally manipulate acoustic radiation force without active controls.

Noise-induced switching from a symmetry-protected shallow metastable state.

We consider escape from a metastable state of a nonlinear oscillator driven close to triple its eigenfrequency. The oscillator can have three stable states of period-3 vibrations and a zero-amplitude state. Because of the symmetry of period-tripling, the zero-amplitude state remains stable as the driving increases. However, it becomes shallow in the sense that the rate of escape from this state exponentially increases, while the system still lacks detailed balance. We find the escape rate and show how it scales with the parameters of the oscillator and the driving. The results facilitate using nanomechanical, Josephson-junction based, and other mesoscopic vibrational systems for studying, in a well-controlled setting, the rates of rare events in systems lacking detailed balance. They also describe how fluctuations spontaneously break the time-translation symmetry of a driven oscillator.

Dependence of enhancement factor on electrode size for field emission current from carbon nanotube on silicon wafer.

This work studies the enhancement factor associated with a current emitted from a multi-wall carbon nanotube to an extremely small counter electrode. The experimental data show that the field enhancement factor increases by 1.15 times when the width of the counter electrode increases from 50 to 200 nm. To better understand this enhancement effect, field intensities at the emitter surface are numerically simulated. The experimental work and simulations demonstrate that the observed field enhancement results from increases in the capacitance between the emitter and counter electrode. In addition, corrugated counter electrodes are found to greatly affect both the capacitance and enhancement factor. This is because the corrugation of the anode surface raises the capacitance and thus provides a higher current. We experimentally show that an effective surface area enlargement of 1.67 times due to the corrugation provides a 1.06-fold increase of the enhancement factor. These results should assist in the future development of field emission devices based on semiconductor fabrication processes.

Driven nonlinear nanomechanical resonators as digital signal detectors.

Because of their nonlinearity, vibrational modes of resonantly driven nanomechanical systems have coexisting stable states of forced vibrations in a certain range of the amplitude of the driving force. Depending on its phase, which encodes binary information, a signal at the same frequency increases or decreases the force amplitude. The resulting force amplitude can be outside the range of bistability. The values of the mode amplitude differ significantly on the opposite sides of the bistability region. Therefore the mode amplitude is very sensitive to the signal phase. This suggests using a driven mode as a bi-directional bifurcation amplifier, which switches in the opposite directions depending on the signal phase and provides an essentially digital output. We study the operation of the amplifier near the critical point where the width of the bistability region goes to zero and thus the threshold of the signal amplitude is low. We also develop an analytical technique and study the error rate near the threshold. The results apply to a broad range of currently studied systems and extend to micromechanical systems and nonlinear electromagnetic cavities.

Singular probability distribution of shot-noise driven systems.

We study the stationary probability distribution of a system driven by shot noise. We find that both in the overdamped and underdamped regime, the coordinate distribution displays power-law singularities in its central part. For sufficiently low rate of noise pulses they correspond to distribution peaks. We find the positions of the peaks and the corresponding exponents. In the underdamped regime the peak positions are given by a geometric progression. The energy distribution in this case also displays multiple peaks with positions given by a geometric progression. Such structure is a signature of the shot-noise induced fluctuations. The analytical results are in excellent agreement with numerical simulations.

Relation between optimal nonlinearity and non-Gaussian noise: enhancing a weak signal in a nonlinear system.

In the study of stochastic resonance, it is often mentioned that nonlinearity can enhance a weak signal embedded in noise. In order to give a systematic proof of the signal enhancement in nonlinear systems, we derive an optimal nonlinearity that maximizes a signal-to-noise ratio (SNR). The obtained optimal nonlinearity yields the maximum unbiased signal estimation performance, which is known in the context of information theory. It is found that a linear system is optimal for a Gaussian noise, but for a non-Gaussian noise, there exist nonlinear systems that can achieve an SNR higher than that obtained from linear systems. This analysis refers to a system subjected to an additive non-Gaussian noise with a small signal input.

Design and characterization of nonlinear functions for the transmission of a small signal with non-Gaussian noise.

We design nonlinear functions for the transmission of a small signal with non-Gaussian noise and perform experiments to characterize their responses. Using statistical design theory [A. Ichiki and Y. Tadokoro, Phys. Rev. E 87, 012124 (2013)], a static nonlinear function is estimated from the probability density function of the given noise in order to maximize the signal-to-noise ratio of the output. Using an electronic system that implements the optimized nonlinear function, we confirm the recovery of a small signal from a signal with non-Gaussian noise. In our experiment, the non-Gaussian noise is a mixture of Gaussian noises. A similar technique is also applied to the optimization of the threshold value of the function. We find that, for non-Gaussian noise, the response of the optimized nonlinear systems is better than that of the linear system.

Singular response of bistable systems driven by telegraph noise.

We show that weak periodic driving can exponentially strongly change the rate of escape from a potential well of a system driven by telegraph noise. The analysis refers to an overdamped system, where escape requires that the noise amplitude θ exceed a critical value θ(c). For θ close to θ(c), the exponent of the escape rate displays a nonanalytic dependence on the amplitude of an additional low-frequency modulation. This leads to giant nonlinearity of the response of a bistable system to periodic modulation. Also studied is the linear response to periodic modulation far from θ(c). We analyze the scaling of the logarithm of the escape rate with the distance to the saddle-node and pitchfork bifurcation points. The analytical results are in excellent agreement with numerical simulations.