Integrated servo-mechanical design of high-performance mechatronics using generalized KYP Lemma

High-performance mechatronics have specifications which are difficult to achieve when the mechanical plant is non-minimum phase and a low-order controller is used. In this paper, an integrated servo-mechanical design algorithm is proposed for systematic finite frequency redesign of a mechanical plant using the generalized Kalman–Yakubovic–Popov Lemma. The synthesis of a minimum phase plant is carried out based on a predesigned low-order controller, positive realness constraints, and performance specifications of the overall control system. Our simulation results using the proposed algorithm achieve a high-bandwidth control system with disturbance attenuation capabilities at the phase-stabilized resonant modes of the plant with the low-order controller.     

Earliest switch-on of dual-stage actuation in hard disk drives

In conventional track-settling process, dual-stage actuation (DSA) is not activated until the read/write head is in close proximity to the target track so that chances of saturation are reduced. In this paper, we propose an earliest switch-on scheme based on the calculation of the exact saturation boundary, considering both position error signal and voice coil motor velocity error. It allows the DSA loop to be switched on earlier than current practices while piezoelectric actuators remain unsaturated. Simulations on a 2.5\(''\) commercially available hard disk drive show that the proposed scheme can reduce the post-seek oscillation and shorten the 5 % track-settling time by more than 16 % in the presence of in-drive disturbances.     

An improved preimage attack against HAVAL-3

Hash functions play an important role in constructing cryptographic schemes that provide security services, such as confidentiality in an encryption scheme, authenticity in an authentication protocol and integrity in a digital signature scheme and so on. Such hash function is needed to process a challenge, a message, an identifier or a private key. In this paper, we propose an attack against HAVAL-3 hash function, which is used in open source Tripwire and is included in GNU Crypto. Under the meet-in-the-middle (MITM) preimage attack framework proposed by Aoki and Sasaki in 2008, the one-wayness of several (reduced-)hash functions had been broken recently. However, most of the attacks are of complexity close to brute-force search. Focusing on reducing the time complexity of such MITM attacks, we improve the preimage attacks against HAVAL-3 hash function to within lower time complexity and memory requirement, compared with the best known attack proposed by Sasaki and Aoki in ASIACRYPT 2008. Besides the 256-bit variant of HAVAL-3, similar improvements can be applied to some truncated variants as well. Interestingly, due to the low complexity of our attack, the preimage attack applies to the 192-bit variant of HAVAL-3 for the first time.     

Atomic Vacancy Control and Elemental Substitution in a Monolayer Molybdenum Disulfide for High Performance Optoelectronic Device Arrays

Defect engineering of 2D transition metal dichalcogenides (TMDCs) is essential to modulate their optoelectrical functionalities, but there are only a few reports on defect‐engineered TMDC device arrays. Herein, the atomic vacancy control and elemental substitution in a chemical vapor deposition (CVD)‐grown molybdenum disulfide (MoS₂) monolayer via mild photon irradiation under controlled atmospheres are reported. Raman spectroscopy, photoluminescence, X‐ray, and ultraviolet photoelectron spectroscopy comprehensively demonstrate that the well‐controlled photoactivation delicately modulates the sulfur‐to‐molybdenum ratio as well as the work function of a MoS₂ monolayer. Furthermore, the atomic‐resolution scanning transmission electron microscopy directly confirms that small portions (2–4 at% corresponding to the defect density of 4.6 × 10¹² to 9.2 × 10¹³ cm^?2) of sulfur vacancies and oxygen substituents are generated in the MoS₂ while the overall atomic‐scale structural integrity is well preserved. Electronic and optoelectronic device arrays are also realized using the defect‐engineered CVD‐grown MoS₂, and it is further confirmed that the well‐defined sulfur vacancies and oxygen substituents effectively give rise to the selective n‐ and p‐doping in the MoS₂, respectively, without the trade‐off in device performance. In particular, low‐percentage oxygen‐doped MoS₂ devices show outstanding optoelectrical performance, achieving a detectivity of ≈10¹³ Jones and rise/decay times of 0.62 and 2.94 s, respectively.     

Robust adaptive neuro-fuzzy control of uncertain nonholonomic systems

In this paper, we present an adaptive neuro-fuzzy controller design for a class of uncertain nonholonomic systems in the perturbed chained form with unknown virtual control coefficients and strong drift nonlinearities. The robust adaptive neuro-fuzzy control laws are developed using state scaling and backstepping. Semiglobal uniform ultimate bound-edness of all the signals in the closed-loop are guaranteed, and the system states are proven to converge to a small neigh-borhood of zero. The control performance of the closed-loop system is guaranteed by appropriately choosing the design parameters. By using fuzzy logic approximation, the proposed control is free of control singularity problem. An adaptive control-based switching strategy is proposed to overcome the uncontrollability problem associated with x 0 (t 0 ) = 0.     

Social Roles in an Online Support Community for Older People

In this article, an online support community for older people is studied, with the aim of developing a taxonomy of social roles based on content analysis and social network analysis. Four hundred messages (posted between August 9, 2007, and February 5, 2008) in an online support community for older people (http://www.seniornet.org) were investigated. The data were analyzed to identify and shed light on patterns of the online functional behavior as well as the social structure of active members. Drawing on the findings, a set of six social roles were identified, defined, and described in depth. The findings showed that the structural positions of online community members were associated with the kind of content these members tended to post. For example, it was found that central members were very likely to give support, whereas members not very well connected were more inclined to post self-disclosing messages.     

Comparative analysis of artificial neural networks and dynamic models as virtual sensors

This paper presents a comparison of predictive models for the estimation of engine power and tailpipe emissions for a 4 kW gasoline scooter. This study forms a benchmark toward establishing an online emissions control and monitoring system to bring the emissions to within specific limits. Three emissions predictive models were investigated in this study; direct and series artificial neural network (ANN) models and a MATLAB dynamic model. The direct models takes variables lambda, throttle position, engine and vehicle speed to predict the engine power and the emissions CO, CO₂ and HC. The series model first takes the mentioned input to predict the engine power and consequently using the engine power as the fifth input to predict the emissions. For the ANN models, two multilayered networks were compared and analyzed; the backpropagation (BP) and optimization layer-by-layer (OLL) algorithms. The predictive accuracy for each algorithm were compared and it was found that the OLL network is the most accurate with a maximum mean relative error (MRE) of 1.78% and 1.38% for the direct and series predictive model respectively. Comparative results showed that the series neural network model gives the most accurate predictions, with MRE of 0.63% and 0.47% for the engine power and emissions respectively. The series neural network model can be seen as generic virtual power and emissions sensors, substituting costly and cumbersome hardware. Simple obtainable process parameters together with the series neural network will contribute immensely in control and tuning of emissions for real-time vehicular applications.     

Sliding mode estimation schemes for incipient sensor faults

This paper proposes a new method for the analysis and design of sliding mode observers for sensor fault reconstruction. The proposed scheme addresses one of the restrictions inherent in other sliding mode estimation approaches for sensor faults in the literature (which effectively require the open-loop system to be stable). For open-loop unstable systems, examples can be found, for certain combinations of sensor faults, for which existing sliding mode and unknown input linear observer schemes cannot be employed, to reconstruct faults. The method proposed in this paper overcomes these limitations. Simulation results demonstrate the effectiveness of the design framework proposed in the paper.     

Planar Minimization Diagrams via Subdivision with Applications to Anisotropic Voronoi Diagrams

Let X = {f₁, …, f_n} be a set of scalar functions of the form f_i : ?² → ? which satisfy some natural properties. We describe a subdivision algorithm for computing a clustered ε‐isotopic approximation of the minimization diagram of X. By exploiting soft predicates and clustering of Voronoi vertices, our algorithm is the first that can handle arbitrary degeneracies in X, and allow scalar functions which are piecewise smooth, and not necessarily semi‐algebraic. We apply these ideas to the computation of anisotropic Voronoi diagram of polygonal sets; this is a natural generalization of anisotropic Voronoi diagrams of point sites, which extends multiplicatively weighted Voronoi diagrams. We implement a prototype of our anisotropic algorithm and provide experimental results.