In this note, we propose a novel adaptive fixed-time control scheme for output tracking problems of a class of multi-input multi-output (MIMO) nonlinear systems with asymmetric output constraint ...requirements, using a new universal barrier function . It is universal in the sense that the proposed scheme is a general one that also works for systems with symmetric constraints or without constraint requirements, without changing the control structure. Novel adaptive estimations and analysis are introduced to address system uncertainties in the fixed-time convergence settings. We show that under the proposed novel control scheme, each element in the system output tracking error vector of the MIMO nonlinear system can converge into small sets near zero with fixed-time convergence rate, while the asymmetric output constraint requirements on each element of the output tracking error are satisfied at all time. The proposed scheme can effectively deal with unmatched system uncertainties and uncertain gain functions. In the end, a simulation example on a two-degree-of-freedom robot manipulator is presented to demonstrate the efficacy of the proposed scheme.
In this paper, we present a novel iterative learning control (ILC) algorithm for the leader-follower formation tracking problem of a class of nonlinear multiagent systems that are subject to actuator ...faults. Unlike most ILC works that require identical reference trajectories over the iteration domain, the desired line-of-sight (LOS) range and angle profiles can be iteration dependent based on different tasks and environment in each iteration. Furthermore, the LOS range and angle tracking errors are subject to iteration and time dependent constraint requirements. Both parametric and nonparametric system unknowns and uncertainties, in particular the control input gain functions that are not fully known, are considered. We show that under the proposed algorithm, the formation tracking errors can converge to zero uniformly over the iteration domain beyond a certain time interval in each iteration, while the constraint requirements on the LOS range and angle will not be violated during operations. A numerical simulation involving two agents in leader-follower formation is presented in the end to demonstrate the efficacy of the proposed algorithm.
Most works on iterative learning control (ILC) assume identical reference trajectories for the system state over the iteration domain. This fundamental assumption may not always hold in practice, ...where the desired trajectories or control objectives may be iteration dependent. In this paper, we relax this fundamental assumption, by introducing a new way of modifying the reference trajectories. The concept of modifier functions has been introduced for the first time in the ILC literature. This proposed approach is also a unified framework that can handle other common types of initial conditions in ILC. Multi-input multi-output nonlinear systems are considered, which can be subject to the actuator faults. Time and iteration dependent constraint requirements on the system output can be effectively handled. Backstepping design and composite energy function approach are used in the analysis. We show that in the closed loop analysis, the proposed control scheme can guarantee uniform convergence on the full state tracking error over the iteration domain, beyond a small initial time interval in each iteration, while the constraint requirements on the system output are never violated. In the end two simulation examples are shown to illustrate the efficacy of the proposed ILC algorithm.
This paper presents a dual-polarized patch antenna with quasi-elliptic bandpass responses. The proposed antenna is mainly composed of a feeding network, a driven patch, and a stacked patch, with its ...entire height being 0.09λ. The feeding network consists of two orthogonal H-shaped lines that coupled to the driven patch, each for one polarization. The elaborately designed feeding lines not only ensure a sharp roll-off rate at the lower band edge, but also help to achieve low cross polarization and high isolation between two feeding ports. On the other hand, the upper stacked patch provides improved suppression levels at the upper stopband and also an enhanced gain within passband. Consequently, a compact dual-polarized antenna with satisfying filtering performance is obtained, without using extra filtering circuits. For demonstration, an antenna is designed to fit the specification of LTE band (2.49-2.69 GHz). The implemented antenna achieves an average a gain of 9 dBi, a cross-polarization ratio of 29 dB, an isolation of 35 dB within LTE band. The out-of-band suppression level is more than 40 dB within the 2G and 3G frequency bands from 1.71-2.17 GHz. It can be used as the antenna elements in multiband base station antenna arrays to reduce the mutual coupling.
Probe Machine Xu, Jin
IEEE transaction on neural networks and learning systems,
2016-July, 2016-07-00, 2016-7-00, 20160701, Letnik:
27, Številka:
7
Journal Article
In this paper, we present a novel computing model, called probe machine (PM). Unlike the turing machine (TM), PM is a fully parallel computing model in the sense that it can simultaneously process ...multiple pairs of data, rather than sequentially process every pair of linearly adjacent data. We establish the mathematical model of PM as a nine-tuple consisting of data library, probe library, data controller, probe controller, probe operation, computing platform, detector, true solution storage, and residue collector. We analyze the computation capability of the PM model, and in particular, we show that TM is a special case of PM. We revisit two NP-complete problems, i.e., the graph coloring and Hamilton cycle problems, and devise two algorithms on basis of the established PM model, which can enumerate all solutions to each of these problems by only one probe operation. Furthermore, we show that PM can be implemented by leveraging the nano-DNA probe technologies. The computational power of an electronic computer based on TM is known far more than that of the human brain. A question naturally arises: will a future computer based on PM outperform the human brain in more ways beyond the computational power?
Reaction networks are widely used as mechanistic models in systems biology to reveal principles of biological systems. Reactions are governed by kinetic laws that describe reaction rates. Selecting ...the appropriate kinetic laws is difficult for many modelers. There exist tools that attempt to find the correct kinetic laws based on annotations. Here, I developed annotation-independent technologies that assist modelers by focusing on finding kinetic laws commonly used for similar reactions.
Recommending kinetic laws and other analyses of reaction networks can be viewed as a classification problem. Existing approaches to determining similar reactions rely heavily on having good annotations, a condition that is often unsatisfied in model repositories such as BioModels. I developed an annotation-independent approach to find similar reactions via reaction classifications. I proposed a two-dimensional kinetics classification scheme (2DK) that analyzed reactions along the dimensions of kinetics type (K type) and reaction type (R type). I identified approximately ten mutually exclusive K types, including zeroth order, mass action, Michaelis-Menten, Hill kinetics, and others. R types were organized by the number of distinct reactants and the number of distinct products in reactions. I constructed a tool, SBMLKinetics, that inputted a collection of SBML models and then calculated reaction classifications as the probability of each 2DK class. The effectiveness of 2DK was evaluated on BioModels, and the scheme classified over 95% of the reactions.
2DK had many applications. It provided a data-driven annotation-independent approach to recommending kinetic laws by using type common for the kind of models in combination with the R type of the reactions. Alternatively, 2DK could also be used to alert users that a kinetic law was unusual for the K type and R type. Last, 2DK provided a way to analyze groups of models to compare their kinetic laws. I applied 2DK to BioModels to compare the kinetics of signaling networks with the kinetics of metabolic networks and found significant differences in K type distributions.
This paper presents a novel method for designing single- and dual-band filtering switches based on coupling control. First, the ON- and OFF-state coupling matrices are analyzed to achieve bandpass ...responses and high isolation, respectively. Then, they are used to guide the low temperature cofired ceramic circuit realization. The ON- and OFF-states are enabled by controlling the PIN diodes in the filter feeding structures. In the ON-state, the circuit is equivalent to a bandpass filter without signals passing through the PIN diodes, which avoids additional loss introduced by the PIN diodes. For the OFF-state isolation, it is realized by controlling the coupling of the filtering circuit, which is different from that of conventional switches by turning off transistors or diodes to obtain isolation. Thus, isolation is considerably enhanced. For demonstration, a single-band filtering switch is implemented with a compact size of 0.050 λg × 0.048 λg × 0.023 λg . Furthermore, a dual-band one of the same dimension is realized with controllable passband frequencies and bandwidths in the ON-state as well as high isolation in OFF-state. The presented filtering switches feature compact size, low ON-state insertion loss, high OFF-state isolation, and high reliability, which are suitable for industrial applications.
In this paper, a dual-channel dielectric resonator (DR) filter is presented for the first time. Two bandpass filters (BPFs) are integrated as one dual-channel filter with two input ports and two ...output ports. By using a common quad-mode DR shared by two second-order BPFs, only one metallic cavity is needed, which greatly reduces the circuit size. Frequency control of the DR is investigated and electromagnetic field properties at HEH11 and HEE11 resonant pairs are studied for guiding the dual-channel filter realization. By properly arranging the input and output feeding probes, two of the resonant modes are excited for one channel and other two for the other channel. Since the feeding probes of one channel filter do not excite the resonant modes of the other one, isolation between two filters is achieved. Three transmission zeros are generated near the passband, resulting in high selectivity. For verification, the dual-channel filter is implemented, which features good bandpass responses and offers a significant size reduction in comparison with conventional two DR filters. What is more, the dual-channel filter with the impedance transformation function is integrated with a <inline-formula> <tex-math notation="LaTeX">2 \times 2 </tex-math></inline-formula> Doherty power amplifier for 5G massive multiple-input multiple-output system application, featuring high efficiency, good filtering responses, and high integration.
Recent technological advances in communications and computation have spurred a broad interest in control law architectures involving the monitoring, coordination, integration, and operation of ...sensing, computing, and communication components that tightly interact with the physical processes that they control. These systems are known as cyber-physical systems and due to their use of open computation and communication platform architectures, controlled cyber-physical systems are vulnerable to adversarial attacks. In this technical note, we propose a novel adaptive control architecture for addressing security and safety in cyber-physical systems. Specifically, we develop an adaptive controller that guarantees uniform ultimate boundedness of the closed-loop dynamical system in the face of adversarial sensor and actuator attacks that are time-varying and partial asymptotic stability when the sensor and actuator attacks are time-invariant. Finally, we provide a numerical example to illustrate the efficacy of the proposed adaptive control architecture.
Scintillation based X-ray detection has received great attention for its application in a wide range of areas from security to healthcare. Here, we report highly efficient X-ray scintillators with ...state-of-the-art performance based on an organic metal halide, ethylenebis-triphenylphosphonium manganese (II) bromide ((C
H
P
)MnBr
), which can be prepared using a facile solution growth method at room temperature to form inch sized single crystals. This zero-dimensional organic metal halide hybrid exhibits green emission peaked at 517 nm with a photoluminescence quantum efficiency of ~ 95%. Its X-ray scintillation properties are characterized with an excellent linear response to X-ray dose rate, a high light yield of ~ 80,000 photon MeV
, and a low detection limit of 72.8 nGy s
. X-ray imaging tests show that scintillators based on (C
H
P
)MnBr
powders provide an excellent visualization tool for X-ray radiography, and high resolution flexible scintillators can be fabricated by blending (C
H
P
)MnBr
powders with polydimethylsiloxane.
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