Learning-enhanced differential evolution for numerical optimization

Differential evolution (DE) is a simple and powerful population-based search algorithm, successfully used in various scientific and engineering fields. However, DE is not free from the problems of stagnation and premature convergence. Hence, designing more effective search strategies to enhance the performance of DE is one of the most salient and active topics. This paper proposes a new method, called learning-enhanced DE (LeDE) that promotes individuals to exchange information systematically. Distinct from the existing DE variants, LeDE adopts a novel learning strategy, namely clustering-based learning strategy (CLS). In CLS, there are two levels of learning strategies, intra-cluster learning strategy and inter-cluster learning strategy. They are adopted for exchanging information within the same cluster and between different clusters, respectively. Experimental studies over 23 benchmark functions show that LeDE significantly outperforms the conventional DE. Compared with other clustering-based DE algorithms, LeDE can obtain better solutions. In addition, LeDE is also shown to be significantly better than or at least comparable to several state-of-art DE variants as well as some other evolutionary algorithms.     

Consensus reaching models of linguistic preference relations based on distance functions

In group decision making (GDM) using linguistic preference relations to obtain the maximum degree of agreement, it is desirable to develop a consensus process prior to the selection process. This paper proposes two consensus models with linguistic information to support the GDM consensus reaching process. Two different distance functions between linguistic preference relations are introduced to measure both individual consistency and group consensus. Based on these measures, the consensus reaching models are developed. The two models presented have the same concept that the expert whose preference is farthest from the group preference needs to update their opinion according to the group preference relation. In addition, the convergence of the models is proved. After achieving the predefined consensus level, each expert’s consistency indexes are still acceptable under the condition that the initial preference relations are of satisfactory consistency. Finally, an example is given to show the effectiveness of the models and to verify the theoretical results.     

An efficient initialization approach of Q-learning for mobile robots

This article demonstrates that Q-learning can be accelerated by appropriately specifying initial Q-values using dynamic wave expansion neural network. In our method, the neural network has the same topography as robot work space. Each neuron corresponds to a certain discrete state. Every neuron of the network will reach an equilibrium state according to the initial environment information. The activity of the special neuron denotes the maximum cumulative reward by following the optimal policy from the corresponding state when the network is stable. Then the initial Q-values are defined as the immediate reward plus the maximum cumulative reward by following the optimal policy beginning at the succeeding state. In this way, we create a mapping between the known environment information and the initial values of Q-table based on neural network. The prior knowledge can be incorporated into the learning system, and give robots a better learning foundation. Results of experiments in a grid world problem show that neural network-based Q-learning enables a robot to acquire an optimal policy with better learning performance compared to conventional Q-learning and potential field-based Qlearning.     

Passive internet-based crane teleoperation with haptic aids

Crane operation is a challenging task, due to the combined problem of obstacle avoidance and load swing suppression in underactuated conditions. This paper presents a human-machine interface that increases the operator’s perception of a gantry crane’s workspace. With this aim, a virtual environment resembling the workspace is connected with a haptic device. This allows the user to receive not only visual but also tactile feedback, thus increasing maneuvering safety. Additionally, this capability is integrated in a teleoperation setup, adopting a passivity-based control approach that guarantees overall stability. This includes also the design of controllers by means of the IDA-PBC method. Experimental results carried out with a laboratory crane show its feasibility for internet-based teleoperation and demonstrate the improvements on the system performance.     

Path tracking control of Lagrange systems with obstacle avoidance

This paper addresses a path tracking problem with obstacle avoidance for Lagrange systems. The proposed method is based on field potential methods in combination with navigation functions for obstacle avoidance. First, it is shown that a simple combination of the navigation function with the conventional path tracking controller does not work. Therefore, in order to cope with this problem, a new feedback law is proposed for a path parameter which characterizes the reference path. It is proved that the proposed controller achieves both path following and collision avoidance. Moreover, since the method adopts bounded navigation functions, the proposed controllers generate bounded input signals even when target systems approach obstacles. Finally, an experimental evaluation is performed with a two-link manipulator to illustrate the effectiveness of the proposed method.     

Electrokinetically driven concentration of particles and cells by dielectrophoresis with DC-offset AC electric field

Insulator-based dielectrophoresis (iDEP) has been successfully used for on-chip manipulations of biological samples. Despite its effectiveness, iDEP typically requires high DC voltages to achieve sufficient electric field; this is mainly due to the coupled phenomena among linear electrokinetics: electroosmosis (EO) and electrophoresis (EP) and nonlinear electrokinetics: dielectrophoresis (DEP). This paper presents a microfluidic technique using DC-offset AC electric field for electrokinetic concentration of particles and cells by repulsive iDEP. This technique introduces AC electric field for producing iDEP which is decoupled from electroosmosis (EO) and electrophoresis (EP). The repulsive iDEP is generated in a PDMS tapered contraction channel that induces non-uniform electric field. The benefits of introducing AC electric field component are threefold: (i) it contributes to DEP force acting on particles, (ii) it suppresses EO flow and (iii) it does not cause any EP motion. As a result, the required DC field component that is mainly used to transport particles on the basis of EO and EP can be significantly reduced. Experimental results supported by numerical simulations showed that the total DC-offset AC electric field strength required to concentrate 15-μm particles is significantly reduced up to 85.9% as compared to using sole DC electric field. Parametric experimental studies showed that the higher buffer concentration, larger particle size and higher ratio of AC-to-DC electric field are favorable for particle concentration. In addition, the proposed technique was demonstrated for concentration of yeast cells.     

A power-free deposited microbead plug-based microfluidic chip for whole-blood immunoassay

We present a deposited microbead plug (DMBP)-based microfluidic chip capable of performing plasma extraction and on-chip immunoassay. The DMBP used as a porous blood filter provides pure blood plasma without the contamination of blood cells or beads. Capillary-driven flow eliminates the requirement of external pumps. The human IgG and goat anti-human IgG sample-to-answer assay was performed in this chip within 600 s using only a 10 μl whole-blood sample. This easy-to-use, rapid, inexpensive, and disposable DMBP-based chip holds a great promise for point-of-care application.     

A simple and cost-effective method for fabrication of integrated electronic-microfluidic devices using a laser-patterned PDMS layer

We report a simple and cost-effective method for fabricating integrated electronic-microfluidic devices with multilayer configurations. A CO₂ laser plotter was employed to directly write patterns on a transferred polydimethylsiloxane (PDMS) layer, which served as both a bonding and a working layer. The integration of electronics in microfluidic devices was achieved by an alignment bonding of top and bottom electrode-patterned substrates fabricated with conventional lithography, sputtering and lift-off techniques. Processes of the developed fabrication method were illustrated. Major issues associated with this method as PDMS surface treatment and characterization, thickness-control of the transferred PDMS layer, and laser parameters optimization were discussed, along with the examination and testing of bonding with two representative materials (glass and silicon). The capability of this method was further demonstrated by fabricating a microfluidic chip with sputter-coated electrodes on the top and bottom substrates. The device functioning as a microparticle focusing and trapping chip was experimentally verified. It is confirmed that the proposed method has many advantages, including simple and fast fabrication process, low cost, easy integration of electronics, strong bonding strength, chemical and biological compatibility, etc.     

Fabrication of a biocompatible flexible electroosmosis micropump

In in-vivo microsystems, one of the components is a biocompatible micropump in order to produce the necessary force to deliver the fluid from the inlet to the outlet. In this contribution, a flexible micropump is fabricated which is aimed to be suitable in drug delivery applications. It provides high degree of biocompatibility, since the only employed materials are implantation grade polydimethylsiloxane elastomer and gold for the electrical interconnects. The working principle of the micropump is based on transverse DC electroosmosis which is a new variant of conventionally applied high voltage DC electroosmosis. This new technique is based on topography irregularities introduced in the channel resulting in a non-uniform charge distribution. The advantage is to drive the micropump using a relatively low DC voltage of 10 V while getting an effective flow speed of 60 μm/s. In order to characterize the flow speed, dyed 3 μm beads are dispersed in the working fluid and their speed is measured by the line scanning technique using a confocal microscope. It is also observed that the flow has a helical profile which is an attractive feature for an efficient micro-mixer in active microfluidics and μ-TAS applications.     

Millisecond-order rapid micromixing with non-equilibrium electrokinetic phenomena

We report an active micromixer utilizing vortex generation due to non-equilibrium electrokinetics near micro/nanochannel interfaces. Its design is relatively simple, consisting of a U-shaped microchannel and a set of nanochannels. We fabricated the micromixer just using a two-step reactive ion etching process. We observed strong vortex generation in fluorescent microscopy experiments. The mixing performance was evident in a combined pressure-driven and electroosmotic flows, compared with the case with a pure pressure-driven flow. We characterized the micromixer for several conditions: different applied voltages, ion concentrations, flow rates, and nanochannel widths. The experimental results show that the mixing performance is better with a higher applied voltage, a lower ion concentration, and a wider nanochannel width. We quantified the mixing characteristics in terms of mixing time. The lowest mixing time was 2 milliseconds with the voltage of 230 V and potassium chloride solutions of 0.1 mM. We expect that the micromixer is beneficial in several applications requiring rapid mixing.