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This article proposes a likelihood-ratio-based method for recovering sparse reflectivity series from noisy seismic signals. Unlike the existing methods, the proposed method is specifically developed to be adaptive to the variance of the observational noise. This enhances the robustness of the reflectivity series recovering, as shown experimentally. The proposed method is briefly summarized as follows: First, the convolutional model of seismic signals is reformulated as a discrete-time linear system. In this linear system, the nonzero reflectivity impulses are treated as abrupt state changes with unknown magnitudes occurring at unknown times. Second, a Kalman filter is applied to the linear system without considering the changes. Third, the likelihood ratio as a function of both the magnitudes and occurring times is evaluated by using the Kalman filtering innovations. Fourth, the magnitudes and occurring times of the changes are estimated by alternately fixing one parameter and maximizing the ratio with the other parameter. Finally, the reflectivity series are reconstructed from the estimated magnitudes and occurring times of the changes. Experimental results verified the reliability of the reflectivity series recovery from noisy seismic traces. [ABSTRACT FROM AUTHOR]

This article focuses on the modeling and stability analysis of the typical single-phase phase-locked loop (PLL) based on second-order generalized integrator (SOGI). Traditionally, SOGI-based PLL (SOGI-PLL) is linearized as the linear time-invariant (LTI) model for the stability analysis and parameter design. Yet, the PLL has periodical nature due to the periodical variation of the grid voltage. The traditional LTI model for PLL thereby reduces the precision of stability analysis. For addressing this problem, an accurate linear time-periodic (LTP) model of the single-phase SOGI-PLL is proposed in this article. The proposed model can precisely characterize the coupling nature of phase, frequency, and amplitude estimated by SOGI-PLL. A precise stability region of SOGI-PLL, thereby, can be derived from the proposed LTP model. The effectiveness of the proposed LTP model for SOGI-PLL is verified by simulation and experimental tests. [ABSTRACT FROM AUTHOR]

This article studies the practical prescribed time sampled-data control problem for input-constrained linear time invariant continuous time systems. By using the solution to a parametric Lyapunov equation, a bounded linear time-varying (LTV) sampled-data controller is designed to solve such a problem. In addition, stability analysis and performance analysis of the closed-loop sampled-data control system are presented by using the methodology of scalarization. Finally, the developed LTV sampled-data state controller is utilized to the whole physical simulation system of air-bearing testbed and experimental results verify the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

In three-phase three-wire (3P3W) voltage-source converter (VSC) systems, utilization of filter inductors with deep saturation characteristics is often advantageous due to the improved size, cost, and efficiency. However, with the use of conventional synchronous frame current control methods, the inductor saturation results in significant dynamic performance loss and poor steady-state current waveform quality. This article proposes an inverse dynamic model-based compensation (IDMBC) method to overcome these performance issues. For this purpose, two-phase exact modeling of the 3P3W VSC control system is obtained. Based on the modeling, the inverse system dynamic model of the nonlinear system is obtained and employed such that the nonlinear plant is converted to a virtual linear inductor system for linear current regulators to perform satisfactorily. Further, to control phase currents in the synchronous frame, a two-phase coordinate transformation is proposed. The IDMBC method is tested via dynamic command response and waveform quality simulations and experiments that employ saturable inductors reaching down from full inductance at zero current to 1/9th inductance at full current. The results obtained demonstrate the suitability of the method for 3P3W VSCs employing saturable inductors. [ABSTRACT FROM AUTHOR]

Resonant converters are often studied using their envelope models (EMs), i.e., the transfer functions (TFs) that relate the envelope of the output quantities to those of the input ones. TFs can accurately represent only the input-output relations of linear systems and hence any method used to develop the EM cannot be accurate if the resonant converters process the envelopes in a nonlinear way. This article works out a general criterion that recognizes whether the envelope processing is linear or not, the type of the eventual non-linearity and its amount. The criterion is expressed in terms of conditions that have to be fulfilled by the input-output Bode diagram of the converter. These conditions are of general validity and do not depend on the converter topology; their applicability is not limited to resonant converters, but it can be extended to any system. The conditions have been derived by reviewing the procedure that leads to the modulated variables Laplace transform method for the development of the EMs. The theoretical results are verified at first by simulations and then by experimental tests carried out on two different resonant topologies of a prototypal converter that works as wireless battery charger. [ABSTRACT FROM AUTHOR]

This article explores a novel composite signal extraction method to extract high-precision angular position from the signals detected by Hall sensors in the gimbal servo system of single-gimbal magnetically suspended control moment gyro (SGMSCMG). Due to magnetic field distortion and other factors, the detected signals involve lots of harmonics and unequal amplitude, which decrease the position resolution accuracy significantly. In the proposed method, normalization is first performed to obtain signals with equal amplitude. Then, on the basis of offline analysis, the signal reconstructed model is established to suppress the most harmonics. Finally, the errors of the models and unmodeled noise are restrained by applying the discrete extended state observer (ESO). Simulated results show that the influence of harmonics and unequal amplitude on the angular position can be almost attenuated by the proposed method. Besides, plentiful experiments on an SGMSCMG demonstrate the validity of the proposed method, and the desired angular position of the ultralow speed servo system can be extracted effectively. [ABSTRACT FROM AUTHOR]

Active disturbance compensation is crucial for realizing high-precision servo control. However, the suppression of rapidly changing disturbances is still a challenging issue. In this article, observer-based disturbance-rejection control is investigated, and an observer with adaptive switching gain is proposed for improved robustness against changing disturbances. First, a disturbance observer (DOB) is established, based on the tracking differentiator technique. Second, a sliding-mode-assisted observer with an adaptive law is designed to estimate the residual-disturbance estimation error of the DOB. The proposed scheme instantly increases the switching gain when the state deviates from a preset boundary, thus eliminating the tuning time. The switching control action with an immediately large switching gain is robust against suddenly changing disturbances. Moreover, the switching gain then decays to zero, reducing chattering in the steady state. The gain adjustment process is designed to have the same dynamic characteristics as the proposed DOB, which guarantees the convergence of the proposed scheme. This method is not only suitable for linear systems, but also extendable to nonlinear systems. The proposed scheme was evaluated experimentally; the results showed that it improves disturbance rejection and decreases servo error. [ABSTRACT FROM AUTHOR]

This article presents an additive-state-decomposition-based repetitive control (RC) method for a class of nonlinear systems with nonintegral-chain form and multiple mismatched disturbances. The key idea of this method is to decompose the original tracking problem for an uncertain nonlinear system into two tractable subproblems, namely RC problem for a primary linear time-invariant (LTI) periodic system and robust stabilization problem for a nonlinear secondary system. By taking the equivalent total effect of the multiple disturbances as one matched total disturbance, an improved linear extended state observer (ILESO) is constructed to estimate and compensate for the adverse effect of the multiple disturbances. The method has three significant features: First, it builds a bridge between the existing RC methods for LTI systems and nonlinear systems and, thus, broadens the application scope of RC; second, besides the known information of the model being used to the design of ILESO, the periodic nonlinearity in the plant is extracted to be treated by RC, which enhances both the transient and steady-state performances; and third, the ILESO-based control scheme and the RC law are designed separately, which is flexible for system design. The stability criterion and design procedure are presented in detail. Finally, numerical and experimental results illustrate the validity and superiorities of the method. [ABSTRACT FROM AUTHOR]

In this article, we proposed a scheme of modeling an air heater system with a long airflow duct, predominantly available in many industrial plants to maintain the desired temperature by simultaneously befitting the transport delay, nonlinearities, model uncertainties, and nonuniform disturbances. At first, the nonlinear delayed air heater system is formulated by combining linear fuzzy system models utilizing fuzzy parallel distributed compensation (PDC) logic. Then, a newly developed L1 adaptive control strategy is modified by replacing its conventional state feedback controller with fuzzy PDC control logic to maintain the desired temperature by nullifying nonlinearities, transport delays, uncertainties, and disturbances. The novelty of the proposed work lies in the fact that the proposed fuzzy PDC law augmented L1 adaptive scheme explicitly deals with the delays and nonlinearities by means of fuzzy PDC logic as well as eliminates time-varying uncertainties and disturbances utilizing L1 adaptive control strategy. The results obtained from real-life laboratory-scale experiments suitably demonstrate the usefulness of the proposed approach. [ABSTRACT FROM AUTHOR]

Neural networks as well as the related neural dynamics have been widely exploited to conduct online computing operations for solving various problems in recent years. This article makes progress along this direction by proposing a saturation-allowed neural dynamics (SAND) model for solving the perturbed time-dependent system of linear equations with noise-tolerant capacity. Specifically, by elaborately constructing a new general framework enhanced by the error-integration information and nonlinear projection functions (PFs), a SAND model is proposed and investigated under various additive noises. In addition, theoretical analyses reveal that the proposed SAND model is of global convergence with zero theoretical error. Moreover, when the value of PF is strictly limited by bounds, i.e., a saturation function, the upper bound of the residual errors of the proposed SAND model is subject to the noises and the bounds of PF. Computer simulation results, as well as robot experiments, verify the superior property of the proposed SAND model for solving the perturbed time-dependent system of linear equations, compared with the state of the prior art. [ABSTRACT FROM AUTHOR]

This article deals with sensor fault tolerant control design and large delay compensation for a class of linear time-invariant systems. Based on predictor-based state transformation and predictive descriptor observer design, both the state and output feedback control laws are constructed. Within the framework of Lyapunov–Krasovskii functionals, a set of stability conditions are identified. The closed-loop systems is globally asymptotically stable at the origin under the state feedback and is ultimately bounded under the output feedback. Finally, the proposed design is validated through numerical simulations and then implemented on a quadrotor trajectory tracking test. Both simulation and experimental results demonstrate the effectiveness of the proposed design. [ABSTRACT FROM AUTHOR]

The linear motor system is normally a low-damping system to achieve high speed and high acceleration without mechanical transmission devices. Therefore, the vibration issue is serious especially in the high-speed start–stop motion process, which deteriorates the control precision and decreases work efficiency. This article proposes a dual-sided hybrid excitation eddy current damper (ECD) to suppress the vibration of the linear motor during decelerating and stopping stages. This ECD is composed of a copper plate and two E-shape hybrid excited electromagnets. The plate is sandwiched between these dual-sided electromagnets to generate the eddy current damping force when it moves and the ECD current is excited simultaneously. The analytical model of the ECD considering leakage flux is established and verified by FEA with the deviation less than 7%. Experiments are conducted on the prototype to verify the effectiveness of its vibration restraint performance. With the active damping, the peak amplitude of the position error and the settling time are reduced by 68.88% and 33.33%, respectively. [ABSTRACT FROM AUTHOR]

A large number of single-phase phase-locked loops (PLLs) require generating a 90° phase-shifted version of their single-phase input signal. Among the wide variety of options, using a quarter-cycle transfer delay is particularly popular. In recent years, several single-phase transfer delay-based PLLs (TD-PLLs) have been proposed in the literature. The major difference between different TD-PLLs lies in the way they have adapted to frequency changes. Regardless of this structural difference, a common trend in investigating TD-PLLs is obtaining a linear time-invariant (LTI) model and analyzing it. Obtaining such a model, however, is often based on neglecting the input signal amplitude variations and double-frequency oscillations in the transient behavior of TD-PLLs, which results in some inaccuracies. To deal with this problem, the linear time-periodic (LTP) modeling of TD-PLLs is presented in this letter. It is demonstrated that the LTP model does not have the limitations of the LTI one and can provide much higher accuracy, but at the cost of a higher model complexity. [ABSTRACT FROM AUTHOR]

Accurate motion estimation plays a crucial role in state estimation of an unmanned aerial vehicle (UAV). This is usually carried out by fusing the kinematics of an inertial measurement unit (IMU) with the video output of a camera. However, the accuracy of existing approaches is hindered by the discretization effect of the model even at a high IMU sampling rate. In order to improve the accuracy, we propose a new IMU motion integration model for the IMU kinematics in continuous time. The kinematics are modeled using a switched linear system. A closed-form discrete formulation is derived to compute the mean measurement, the covariance matrix, and the Jacobian matrix. Thus, it is more accurate and more efficient for online estimation of visual-inertial odometry (VIO), particularly when there is a high dynamic change in the agent's motion or the agent travels with high speed. The proposed IMU factor framework is evaluated using both real public datasets and indoor environment under different scenarios of motion capture. Our evaluation shows that the proposed framework outperforms the state-of-the-art VIO approach by up to 22.71% accuracy improvement on the EuRoc dataset and 38.15% accuracy improvement for motion estimation under the indoor environment. [ABSTRACT FROM AUTHOR]

Although proportional-integral-derivative control remains one of the most common control schemes used in industry, its tuning still remains inadequately understood in many applications. This task becomes much more challenging when applied to multi-input multi-output (MIMO) systems. This article presents the design of a discrete-time robust multivariable (nonadaptive) tracking controller that comes with a simple structure, requires very limited information on the plant model, and is relatively easy to tune. In addition to being easy to tune and implement, an objective of this controller is to deal with a class of large-scale systems with complex dynamics. We analytically demonstrate the robustness and convergence of the closed-loop system for a class of MIMO linear time-varying systems. The overall superiority of the proposed controller is experimentally validated on a Barrett robot arm in a laboratory environment. The article also provides a stochastic framework of the general setting of the controller. Within this framework, two minimum mean square error optimal solutions of the controller are provided; one is designed for the case where the number of inputs is not greater than the number of outputs, and the other is for the antithesis. [ABSTRACT FROM AUTHOR]

This article introduces discrete-time controllers for double dual boost converters, suitable for renewable energy applications. The proposed schemes are based on a current ripple mitigation technique, which enables an unconstrained input-to-output voltage converter gain. This is in contrast with classical interleaved topology implementations, where duty cycles are restricted (e.g., to 50%). A discrete-time small-signal controller is proposed for those applications that require nominal specifications. This control strategy is based on a novel linear difference system approach, whereas gain tuning is performed via numerical computation of linear matrix inequalities. In addition, a discrete-time large-signal controller is proposed for those applications that require trajectory tracking. The proposed controllers, their stability, performance, and ripple cancellation properties are validated via experimental results. [ABSTRACT FROM AUTHOR]

In this article, an improved dc-link voltage regulation strategy is proposed for grid-connected converters applied in dc microgrids. For the inner loop of the grid-connected converter, a voltage modulated direct power control is employed to obtain two second-order linear time-invariant systems, which guarantees that the closed-loop system is globally exponentially stable. For the outer loop, a sliding mode control strategy with a load current sensor is employed to maintain a constant dc-link voltage even in the presence of constant power loads at the dc-side, which adversely affect the system stability. Furthermore, an observer for the dc-link current is designed to remove the dc current sensor at the same time improving the reliability and decreasing the cost. From both simulation and experimental results obtained from a 15-kVA prototype setup, the proposed method is demonstrated to improve the transient performance of the system and has robustness properties to handle parameter mismatches compared with the input–output linearization method. [ABSTRACT FROM AUTHOR]

The integration of cyber and physical domains improves the flexibility and efficiency of industrial systems. However, it also introduces security threats into the physical processes of the systems. More seriously, most of field devices, such as sensors and actuators, in industrial systems are vulnerable to security threats because they are usually not deployed with security countermeasures. Therefore, how to secure the physical processes of these industrial cyber-physical systems becomes an emerging problem. To address this problem, a zoning-based approach is presented in this article for identification and mitigation of actuator attacks in multiple-input multiple-output processes governed by linear time-invariant systems. It partitions the set of actuators into multiple zones that ensures the controllability of the surviving zones when a zone is compromised. When a zone is intruded, the system states of the compromised zone and other zones cooperate to confirm that the detected attack is against actuators. Then, to mitigate the impact of the actuator attack on the system functions, the attacked actuators are isolated. After that, the residual actuators in the surviving zones are used to reconfigure the control loops of the systems. Case studies are conducted to illustrate the effectiveness of the presented approach. [ABSTRACT FROM AUTHOR]

In this article, we treat the problem of distributed state estimation for medium- to large-scale linear systems. We consider a system, which consists of several subsystems, and assume that there already exist linear local estimators for the individual subsystems. These existing local estimators could be designed using algorithms of different types. We propose a systematic approach to connect the local estimators through information flows, such that a distributed state estimation scheme is formed for the linear system. The convergence and boundedness of the estimation error for the developed distributed scheme are proven. The proposed method is applied to a full-car active suspension system. The entire system is decomposed into five subsystems interacting with each other. A distributed estimation architecture is established based on the proposed method. The effectiveness of the proposed approach for the full-car suspension system is illustrated using simulation results, which confirm good estimation performance. [ABSTRACT FROM AUTHOR]

In this article, a novel nonfragile controller design scheme is developed for a class of periodic piecewise systems with linear time-varying subsystems. Two types of norm-bounded controller perturbations, including additive and multiplicative ones, are considered and partially characterized by periodic piecewise time-varying parameters. Using a new matrix polynomial lemma, the problems of nonfragile controller synthesis for periodic piecewise time-varying systems (PPTVSs) are made amenable to convex optimization based on the favorable property of a class of matrix polynomials. Depending on selectable divisions of subintervals, sufficient conditions of the stability and nonfragile controller design are proposed for PPTVSs. Case studies based on a multi-input multi-output PPTVS and a mass-spring-damper system show that the proposed control schemes can effectively guarantee the close-loop stability and accelerate the convergence under controller perturbations, with more flexible periodic time-varying controller gains than those obtained by the existing methods. [ABSTRACT FROM AUTHOR]

A well-established theory of statistical inference enables the generation of statistical fault detection approaches. Previous works mainly focus on parametric tests that assume that probabilistic distributions of both healthy and faulty residuals can be parameterized. However, such assumptions may be quite limited for general nonlinear stochastic systems because those residuals are usually with unknown distribution. In this article, a new fault indicator is defined to replace the traditional residual, and a multistep fault detection method is developed via the standard Mann–Whitney (MW) test. Moreover, with weak assumptions on faults and systems, a one-step fault detection approach is proposed by means of the modified MW test. Finally, the effectiveness of the proposed fault detection method is verified by a simulation of three water tank system. [ABSTRACT FROM AUTHOR]

In this article, an uncertainty and disturbance estimator (UDE)-based robust output feedback control technique without using a state observer is proposed for a general class of nonlinear single-input single-output systems that are bounded-input bounded-output stable and subject to input and output disturbances. Instead of designing a controller for the original system directly, an equivalent system consisting of a first-order linear system plus a lumped uncertainty term is used to represent the input–output relationship. Then, a UDE-based robust controller is designed only using the system output feedback and the bandwidth of the open-loop system, making the design almost modeling-free. A prominent advantage of the proposed approach is that it has converted a challenging robust control problem into an intuitive filter design problem. The effectiveness of the proposed approach is validated on an experimental piezoelectric stage in the presence of hysteresis nonlinearity. [ABSTRACT FROM AUTHOR]

In this paper, a parameter-dependent multiple discontinuous Lyapunov function (PMDLF) approach is proposed to study the $H_\infty$ refined antidisturbance control problem of switched linear parameter-varying systems. The $H_\infty$ refined antidisturbance means the disturbance appearing in the control channel can be accurately compensated by means of the estimation of the disturbance and the energy bounded external disturbance can be restrained. A key point is to set up a PMDLF framework that provides an effective tool for attenuating the energy bounded disturbances and rejecting the disturbances generated by the exosystem accurately. A parameter-driven and dwell time-dependent switching law is designed, and a solvability condition ensuring the $H_\infty$ refined antidisturbance performance is developed. Then, the $H_\infty$ refined antidisturbance switched parameter-dependent disturbance observers and the disturbance observer-based refined controllers are established to achieve required disturbance attenuation and rejection. Finally, an example of an aero-engine control system is given to verify the availability of the acquired approaches. [ABSTRACT FROM AUTHOR]

Disturbance observer (DOB) has been one of the most widely used robust control tools since it was proposed by Ohnishi in 1983. This paper introduces the origins of DOB and presents a survey of the major results on DOB-based robust control in the last 35 years. Furthermore, it explains DOB's analysis and synthesis techniques for linear and nonlinear systems by using a unified framework. In final section, this paper presents concluding remarks on DOB-based robust control and its engineering applications. [ABSTRACT FROM AUTHOR]

A new approach to the design of nonlinear disturbance observers (DOBs) for a class of nonlinear systems described by input–output differential equations is presented in this paper. In contrast with established forms of nonlinear DOBs, the most important feature of this new type of DOB is that only measurement of the output variable is required, rather than the state variables. An inverse simulation model is first constructed based on knowledge of the structure and parameters of a conventional model of the system. The disturbance can then be estimated by comparing the output of the inverse model and the input of the original nonlinear system. Mathematical analysis demonstrates the convergence of this new form of nonlinear DOB. The approach has been applied to disturbance estimation for a linear system and a new form of linear DOB has been developed. The differences between the proposed linear DOB and the conventional form of frequency-domain DOB are discussed through a numerical example. Finally, the nonlinear DOB design method is illustrated through an application involving a simulation of a jacketed continuous stirred tank reactor system. [ABSTRACT FROM AUTHOR]

In this paper, the influence of the flat and cap secondary, which are usually applied in the linear metro system on transverse forces of linear induction motors, is calculated and analyzed. First, the cap-aluminum plate and lamination back iron of the cap secondary caused relative difficulty in the analytical calculation. Then, the equivalent of the cap-aluminum plate and lamination back iron is presented, and two equivalent coefficients are obtained. The two types of the asymmetry are discussed and the different magnetic motive forces are presented. Second, the analytical model and the method of the linear induction motor are presented. Third, for a cap secondary in practice, the two equivalent coefficients are calculated and discussed. Then, the flat and cap secondary are applied, and the different transverse forces are calculated and analyzed. For two types of the secondaries, the different eddy currents and air-gap flux densities are compared. Finally, the test workbench is built and the analytical result of the transverse force is experimentally validated. It shows that cap secondary has less influence on the railcar when the transverse displacement occurs. [ABSTRACT FROM AUTHOR]

This paper presents a hierarchical Markov model to assess the reliability of a double-sided linear switched reluctance generator (DLSRG) system. The proposed reliability model can be applied to find the balance point of reliability assessment accuracy and model complexity. First, the dominant fault modes of the DLSRG system are highlighted to quantitatively obtain the operation states, survival or failure, with a novel failure criterion. Second, a hierarchical Markov model is adopted to build a systematic reliability model of the DLSRG system, wherein a state transition diagram can be built in the detailed description to constitute the graphical Markov reliability model. And then the solving process to get state probability matrix P(t) is intensively investigated. Notably, a reliability block diagram model is also built to compare with the hierarchical Markov model, whose results verify that the Markov model can capture the effect of fault-tolerance capability on system reliability. Moreover, it is expected that the one-level Markov model is the most suitable model for the DLSRG system for its ability of decreasing the model complexity and improving the assessment accuracy. Analytic investigation in conjunction with simulation and experimental measurements demonstrates the feasibility and validity of the proposed model. [ABSTRACT FROM AUTHOR]

A novel two-dimensional (2-D) linear piezoelectric stepping platform using two parallel longitudinal-bending hybrid piezoelectric actuators is proposed in this paper. The proposed platform is moved in theX-direction by combing the vertical and horizontal bending motions of the parallel actuators, whereas the movement in theY-direction is realized by the vertical bending and longitudinal hybrid motions. The platform is designed and its operating principles in two orthogonal directions are described. The finite-element method simulations are performed to verify the operating principles of the 2-D platform. Two piezoelectric actuators are fabricated and a prototype of the platform is assembled. The measured results of mechanical output performance indicate that the velocities of the platform are 101.7 and 124.2 μm/s inX- andY-directions when the voltage and frequency are ${\text{400}\,\text{V}}_{{\text{p-p}}}$ and 5 Hz, respectively, which verifies the feasibility of the proposed mechanism for the 2-D stepping platform. [ABSTRACT FROM AUTHOR]

In this paper, an optimal fault detection scheme is presented for a closed-loop control system, where an event-triggering mechanism is utilized for the transmission of output measurements, addressing the design of residual generation and evaluation, while considering the effects associated with unknown disturbances and faults in the system and event-triggered transmission errors on the generated residual. The triggering parameter-dependent residual generation is designed to achieve a best tradeoff between robustness against unknown disturbances and sensitivity to faults, and the residual evaluation is designed to deliver a time-varying threshold that accounts for the effects of disturbances and event-triggered transmission errors on the generated residual. The results are general and simplify to those developed for optimal fault detection in time-triggered systems. In addition, a vehicle lateral dynamic system is adopted to demonstrate the applicability of the proposed optimal fault detection scheme as well as its advantages over an existing widely used event-triggered fault detection scheme. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of $\mathscr {L}_\infty$ control for positive delay systems with semi-Markov process. The system is subjected to a semi-Markov process that is time-varying, dependent on the sojourn time, and related to Weibull distribution. The main motivation for this paper is that the practical systems such as the communication network model (CNM) described by positive semi-Markov jump systems (S-MJSs) always need to consider the sudden change in the operating process. To deal with the corresponding problem, some criteria about stochastic stability and $\mathscr {L}_\infty$ boundedness are presented for the open-loop positive S-MJSs. Further, some necessary and sufficient conditions for state-feedback controller satisfying $\mathscr {L}_\infty$ boundedness and positivity of the resulting closed-loop system is established in standard linear programming. Finally, the practical system about the CNM is given to verify the validity of the proposed method. [ABSTRACT FROM AUTHOR]

The current lithium-ion battery remaining useful life (RUL) prediction techniques are mainly developed dependent on offline training data. The loaded current, temperature, and state of charge of lithium-ion batteries used for electric vehicles (EVs) change dramatically under the working conditions. Therefore, it is difficult to design acceleration aging tests of lithium-ion batteries under similar working conditions as those for EVs and to collect effective offline training data. To address this problem, this paper developed an RUL prediction method based on the Box–Cox transformation (BCT) and Monte Carlo (MC) simulation. This method can be implemented independent of offline training data. In the method, the BCT was used to transform the available capacity data and to construct a linear model between the transformed capacities and cycles. The constructed linear model using the BCT was extrapolated to predict the battery RUL, and the RUL prediction uncertainties were generated using the MC simulation. Experimental results showed that accurate and precise RULs were predicted with errors and standard deviations within, respectively, [-20, 10] cycles and [1.8, 7] cycles. If some offline training data are available, the method can reduce the required online training data and, thus, the acceleration aging test time of lithium-ion batteries. Experimental results showed that the acceleration time of the tested cells can be reduced by 70%–85% based on the developed method, which saved one to three months’ acceleration test time compared to the particle filter method. [ABSTRACT FROM AUTHOR]

The problem of codesign or simultaneous synthesis of triggering and input policies is investigated. The policies are synthesized to minimize a cost function incorporating a data transmission cost. This is unlike the common practice of utilizing an a priori-designed stabilizing control policy and designing a triggering policy, which retains stability. Initially, a finite-horizon cost function that penalizes the state, the control input, and each data transmission is selected. The optimal actions comprised of the control input and the triggering decision, under the operation choice of zero-order hold (ZOH), are approximately obtained in a feedback form, using adaptive dynamic programming. Afterward, the design is extended to the case of generalized ZOH, where the last transmitted state information is updated using a possibly imperfect model. Extension to infinite-horizon cost functions is presented. After analysis of convergence and optimality, the performance of the method is demonstrated through some numerical examples. [ABSTRACT FROM AUTHOR]

In this paper, we design a linear time-invariant two-input-two-output controller for the permanent magnet synchronous motor (PMSM). First, the nonlinear system of a PMSM is approximated using a linear system with structured uncertainties according to the geometric structures of PMSM. We then design a linear controller for the approximated linear system using a standard $\mu$-synthesis robust control method. The main contribution of this paper is that we recognize that the nonlinear PMSM can be reduced to a linear system to apply the mature modern control theory, without referring to classical PID control, thus largely reducing the design effort. The newly designed robust controller is not only easy to calculate, it is also easy to implement and requires less sensors. By virtue of modern robust control theory, it responds fast to exogenous inputs, and robust against parameter uncertainties as well. The applicability of the designed robust controller is both numerically simulated and experimentally verified on a TMS320 F28335 based control board, with performance further compared with the widely used field-oriented controller. [ABSTRACT FROM PUBLISHER]

Discriminative dictionary learning has been successfully applied in pattern recognition field. In most of dictionary learning methods, $\ell 0$-norm or $\ell 1$-norm is used to regularize the sparse representation coefficients, which makes the computing time consuming. In this paper, we present a novel dictionary learning method to improve the gas identification performance of the electronic nose. It has significantly less complexity but leads to very competitive classification results. An analysis dictionary is trained to generate discriminative code by a simple linear projection, while a synthesis dictionary is trained to obtain discriminative reconstruction. Moreover, class label information is utilized to promote the discriminative power of the coding coefficients. The analysis dictionary and synthesis dictionary are trained jointly by an iterative method, which makes the learned projection dictionaries better fit with each other so that the more effective gas identification can be obtained. The proposed algorithm is evaluated on the analysis of different concentration of carbon monoxide, methane, hydrogen, benzene, formaldehyde, ethylene, propane, and ethanol. Experimental results show that the proposed method is not only effective in the signal analysis, but also useful and applicable to the performance enhancement of the current electronic noses. [ABSTRACT FROM AUTHOR]

This paper investigates the group synchronization problem for interacting clusters of agents, which can be either generic linear systems or nonlinear oscillators, by focusing on in-depth understanding of how the couplings among agents influence the group behavior. To this end, we work on both the homogeneous case that agents have the same system dynamics and the heterogeneous case that agents from different clusters have different system dynamics. It is shown that the synchronization for each cluster of agents is irrelevant to the strength of the intercluster couplings as long as the intercluster couplings are collectively acyclic; that is, the intercluster couplings do not incur desynchronization and, thus, no extra effort beyond the strengths of the intracluster couplings, which are necessary to guarantee the synchronization of each cluster in the absence of intercluster couplings, are needed. Moreover, we provide an example demonstrating that the condition of having collectively acyclic intercluster couplings is not a necessity in guaranteeing the above property. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of a network-based data-driven filter design for discrete-time linear systems with bounded noises and packet dropouts. One favorable feature is that the designed filter can be directly employed without identifying the unknown system model. To compensate the negative effects of packet dropouts, an output predictor is first designed to reconstruct the missing data based on the received outputs and the inputs of the system. The asymptotic convergence of the output prediction error is established, of which the rate can be adjusted by the parameter. Then utilizing the predicted outputs and the received measurements, an almost-optimal data-driven filter with tractability is proposed within the set membership (SM) framework and the bound on the worst case estimation error is derived. Finally, two illustrative examples, including a comparison example and an application example, are presented to show the advantages of the proposed design and the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper develops the disturbance observer-based integral sliding-mode control approach for continuous-time linear systems with mismatched disturbances or uncertainties. The disturbance observer is proposed to generate the disturbance estimate, which can be incorporated in the controller to counteract the disturbance. With the help of the proposed disturbance observer, both the memoryless and memory-based integral sliding surfaces and integral sliding-mode controllers are developed, respectively, and two approaches, i.e., $H_\infty$ control and steady-state output-based approaches, are proposed to design the controller and disturbance rejection gains. Finally, the effectiveness and applicability of the proposed technique are illustrated by a numerical example and a real-time experiment. [ABSTRACT FROM AUTHOR]

The fourteen papers in this special section focus on the design and control of linear machines (LEMs). The subjects of these papers embrace the main subjects of interest of the scientific community related to LEMs, ranging from innovative procedures for the optimal design of such machines, to their analysis with finite elements, to advanced control techniques, suitably devised for specific applications. [ABSTRACT FROM AUTHOR]

Disturbance-observer-based control (DOBC) and related methods have been researched and applied in various industrial sectors in the last four decades. This survey, at first time, gives a systematic and comprehensive tutorial and summary on the existing disturbance/uncertainty estimation and attenuation techniques, most notably, DOBC, active disturbance rejection control, disturbance accommodation control, and composite hierarchical antidisturbance control. In all of these methods, disturbance and uncertainty are, in general, lumped together, and an observation mechanism is employed to estimate the total disturbance. This paper first reviews a number of widely used linear and nonlinear disturbance/uncertainty estimation techniques and then discusses and compares various compensation techniques and the procedures of integrating disturbance/uncertainty compensation with a (predesigned) linear/nonlinear controller. It also provides concise tutorials of the main methods in this area with clear descriptions of their features. The application of this group of methods in various industrial sections is reviewed, with emphasis on the commercialization of some algorithms. The survey is ended with the discussion of future directions. [ABSTRACT FROM PUBLISHER]

This paper is dedicated to the design of unknown input (UI) observers for linear parameter-varying (LPV) systems using algebraic matrix manipulation. First, a discussion is provided concerning the classical design approach, which requires the matching condition. This condition is satisfied for a class of systems having relative degree 1. Second, for the same class of systems, a new generalized approach is proposed for simultaneous state and UI estimation. It is demonstrated that the proposed approach is more general than the classical approach. Finally, an extension of the approach is provided for LPV systems with arbitrary relative degree. Simulation examples are provided to illustrate the main results of the paper. [ABSTRACT FROM PUBLISHER]

This paper proposes a novel class of adaptive extended state observers (AESOs) that significantly expand the applications of extended state observers (ESOs) to nonlinear disturbed systems. An AESO is designed as a linear time-varying form that, as a result, combines both the advantages of theoretical completeness in a conventional linear ESO (LESO) and good practical performance in a conventional nonlinear ESO (NESO). To tune the time-varying observer gains, AESO error dynamics is first transformed into a canonical (phase-variable) form. Then, time-varying PD-eigenvalues are assigned for the canonical system based on differential algebraic spectral theory. Theorems for stability and estimate error bounds of the AESO are given in the presence of unknown disturbances. These theorems also offer some important guidelines for assigning the PD-eigenvalues. To demonstrate the effectiveness of this new observer, two representative applications, including a numerical single-input–single-output example and a practical multiple-input–multiple-output hypersonic vehicle application, are exemplified, and comparison simulations are conducted among AESO, LESO, and NESO. Future work is pointed out in the end. [ABSTRACT FROM PUBLISHER]

This paper presents a novel approach on diode model parameter identification from the $I$– $V$ characteristics of photovoltaic panels. Other than the prevailing methodology of solving a group of nonlinear equations from a few points on the $I$– $V$ curve, the proposed methodology views the diode model as the equivalent output of a dynamic system. From this new viewpoint, diode model parameters are linked to the transfer function (after Laplace transform) of the same dynamic system whose parameters are then identified by a simple integral-based linear square. The indoor flash test shows the accuracy and effectiveness of the proposed method, and outdoor module testing shows its ability of online monitoring and diagnostics. Comparisons to the methods of Lambert W function and evolution algorithms are also included. [ABSTRACT FROM PUBLISHER]

In this paper, we review relevant problems in the modeling of dc–dc converters with switched capacitors. We study several approaches that overcome the exposed modeling difficulties, addressing ideal and nonideal cases and using dynamic equations that are valid in a large-signal domain. [ABSTRACT FROM PUBLISHER]

This paper presents some new methods to analyze the stability of the equilibrium point, and the bounded-input/bounded-state (BIBS) and the bounded-input/bounded-output (BIBO) stabilities for linear systems and a class of nonlinear systems. We study these systems in both continuous-time and discrete-time forms, using approaches from model-based methods to data-driven methods. For linear systems, our work about the BIBS and the BIBO stabilities does not concern the state controllability or the state observability. The data-driven methods can analyze the stabilities by doing some simple experiments and observations, while not identifying the corresponding parameter matrices. Our methods are easier to understand and more convenient to use in engineering practice. [ABSTRACT FROM PUBLISHER]

This paper considers the problem of designing adaptive output feedback sliding mode controllers for a class of linear systems with matched external disturbances, where the norm bound of the external disturbance is unknown. First, we derive a new design approach of linear sliding surface in the singular system framework, and propose an adaptive output feedback sliding mode controller such that the motion of the closed-loop system is uniformly ultimately bounded stable. Second, to improve the transient performance, a memory-based adaptive output feedback sliding mode controller is also proposed. Finally, an illustrative example is utilized to demonstrate the design procedures proposed in this paper. It is shown that the memory-based adaptive output feedback sliding mode control approach provides a better transient performance. [ABSTRACT FROM PUBLISHER]

The input-to-state stability (ISS) for a class of networked control systems with random delays and packet dropouts appearing simultaneously in both feedback and forward channels is thoroughly investigated in this paper. A new network predictive controller scheme is introduced in order to compensate the effect of transmission delays and packet dropouts. By making use of the small gain theorem, the stability criteria of the considered new system are derived. The proposed stability conditions are fairly easy to check and considerably less conservative than the existing ones. These criteria reveal that, if the original linear systems are controllable and observable, then, by adopting the proposed networked-predictive-control scheme, the ISS properties can be guaranteed for the overall system despite the effects of networking such as transmission bounded delays, packet dropouts, and possible disturbance inputs. When no disturbance inputs occur, the system stability can be guaranteed for random delays with a certain bound or else for any large constant delays. Results for two illustrative examples are given to validate the proposed control scheme, the second one being a laboratory-scale dc-motor rig. [ABSTRACT FROM PUBLISHER]

This paper considers mainly the leader-following consensus for multiple agents with general linear system dynamics under switching topologies. Three different settings are systematically considered. We first consider the setting that the underlying interaction topologies switch arbitrarily among the possible weakly connected digraphs and then extend it to a more general setting that the weak connectivity of the interaction topologies is kept for some disconnected time intervals with short length due to the communication constraints among agents. Exponentially, consensus control is proved to be achieved, and the convergence rate can be specified as well for both settings in spite of the relaxed conditions on the system dynamics of each individual agent which even allow that each agent has exponentially unstable mode, while for the last case where the weak connectivity is only maintained on the joint of the interaction topologies, consensus control is proved to be achieved when the system matrix of each individual agent satisfies certain stability conditions. [ABSTRACT FROM PUBLISHER]

Quantization has been an important research area for a long time for networked control systems. This paper addresses the problem of a reset state observer (RSO)-based control (RSOC) for linear systems using quantized measurements. According to the characteristic of the logarithmic quantizer, an RSOC is presented based on the standard one to suppress sensor quantization effects. By using the Lyapunov approach, the closed-loop system is still asymptotically stable when the reset technique is introduced. The observer and controller gains of the closed-loop systems are obtained via solving linear matrix inequalities. At last, a numerical example is given to illustrate the effectiveness of the proposed results. [ABSTRACT FROM PUBLISHER]

A small-scale wind energy conversion system can track the maximum power point (MPP) based on a linear relationship between Vdc^2 and Idc. Unlike conventional MPP tracking (MPPT) methods using a lookup table, an advanced technique is proposed based on this relationship as a variant of the perturb and observe (P&O) method. It not only has the advantages of the conventional P&O method but also has a faster tracking speed and better performance. This paper theoretically analyzes the possible power coefficient drop when using a linear relationship for MPPT and establishes that the turbine design can ensure that the possible power coefficient drop is small. The simulation results show that the analysis is precise. The validity and performance of the proposed MPPT method are confirmed by both simulation and experimentation. [ABSTRACT FROM PUBLISHER]

This paper studies the decentralized H\infty control problem for a class of compartmental networks, where the controller gain matrix is required to be diagonal and elementwise restricted. To solve the problem, we first propose a novel characterization under which the closed-loop system is asymptotically stable with a prescribed H\infty performance. Then, a necessary and sufficient condition for the existence of a required controller is obtained, and an iterative linear matrix inequality approach is developed to solve the design condition. Moreover, a D-K iteration method is presented to optimize the initial value such that the solvability of the original problem can be further enhanced. Finally, the obtained results are illustrated through an application to a simple air traffic flow network model. [ABSTRACT FROM PUBLISHER]