Variable Sampling Period Research Articles

Variable selective control for networked systems: A switched quadratic Lyapunov functional approach

This paper presents a new method for control of linear networked systems by combining the predictive control and the variable sampling period approaches. In this way, event-driven sensors are implemented, i.e. by construction the sensors are triggered to sample the outputs of the plant, when new control input signals are received by the actuators. In light of this formulation, at each sampling instant, total control loop delay will be equal to the sampling period which is unknown. In order to deal with the network effects associated with a range of pre-specified time delays, appropriate step invariant discrete-time models of the networked plant are calculated offline. Based on these, some stabilizing control signals are constructed online. The control signals are then packed in the control-side packet, transmitted back to the plant side and received by a time delay compensator module. A less conservative class of Lyapunov functions, called switched quadratic Lyapunov, is used here for stability analysis and stabilizing controller design. Simulation studies on well-known benchmark problems demonstrate the effectiveness of the proposed method.

Response of medium‐ and large‐sized terrestrial fauna to corridor restoration along the middle Sacramento River

A fundamental challenge in restoration ecology is to understand when species are expected to colonize newly created habitat. Determining this is important for assessing progress toward restoration goals and, more generally, for gaining insight into ecosystem functioning and dynamics. We studied this question as it relates to mid‐ to large‐sized terrestrial fauna in restored riparian habitats at the Sacramento River National Wildlife Refuge, in northern California. We used camera traps to document use of 16 riparian corridor sites of varying restoration age. Comparisons of species richness (diversity) and visitation frequency (activity) were made across different‐aged sites. We found that predator diversity and activity levels tended to be higher in restored forests than in remnant forests, and that they tended to be highest in young restored forests. This trend persisted when data from variable sampling periods were pooled, although significant differences occurred more often in wet and cold sampling periods. The trend did not always hold for the animal community at large (consisting of both predator and non‐predator species). We conclude that restoration age affects predator diversity and activity levels in restored and remnant floodplain forests, and that predator communities can establish soon after restoration. Our results suggest that restoring natural river processes that promote habitat regeneration may benefit mid‐ to large‐sized terrestrial predators that appear to mostly use early successional habitat.

Robust Variable Sampling Period Control for Networked Control Systems

The aim of this paper is to develop a novel robust variable sampling period controller (RVSPC) for networked control systems (NCSs) in the presence of random time delays and packet losses. Different from the existing control techniques for NCSs, the RVSPC controller is constructed as a hybrid robust controller with the adaptive variable sampling period. To adapt to the delay variation, a so-called variable sampling period adjuster based on a time delay predictor (TDP) and a time delay and packet detector is designed to adjust effectively the sampling period. To efficiently compensate for the random delays and packet losses, the hybrid controller is designed as a combination of a quantitative feedback theory (QFT)-based robust controller and a robust state feedback controller (RSFC) with adaptive control gain. A smart switch based on the TDP is then used to select properly the main control unit as the QFT or RSFC corresponding to the current delay and packet loss status. Illustrative examples with NCSs including both computation and communication delays and packet losses are finally carried out to illustrate the effectiveness of the proposed method.

Stochastic sampled-data H∞ synchronization of coupled neutral-type delay partial differential systems

This paper discusses the asymptotical synchronization and H∞ synchronization of coupled neutral-type delay partial differential systems (NDPDSs). A sampled-data controller with m stochastically varying sampling periods whose occurrence probabilities are given constants is considered. By using the method of a nonsingular matrix transformation, we decouple the coupled error dynamical systems. Then, sufficient conditions that guarantee the asymptotic stability of decoupled synchronization error dynamical systems are derived in terms of linear matrix inequalities (LMIs) by constructing a suitable Lyapunov–Krasovskii functional with triple integral terms and by using Jensen׳s inequality and reciprocally convex combination technique, which implies the asymptotical synchronization of the coupled NDPDSs. Moreover, the stability criteria for the H∞ stabilization of decoupled synchronization error dynamical systems with external disturbances are also derived in terms of LMIs, which guarantee the H∞ synchronization of the coupled NDPDSs. The equivalence between the H∞ stability of decoupled synchronization error dynamical systems and the H∞ synchronization of coupled NDPDSs is also proved by mathematical analysis. Finally, numerical examples are provided to demonstrate the effectiveness of the obtained results.

A new method for control of networked systems with an experimental verification

This paper presents a variable selective control methodology for control of networked systems subject to transfer delay, packet-loss and packet-disordering. This approach is based upon the extension of the variable sampling period idea with a new packet based control methodology. In this way, corresponding to a range of expected time delays, a number of step-invariant discrete-time plant models are considered and based on them, a switching observer-based controller is designed by solving linear matrix inequalities (LMIs). A sufficient condition for closed-loop asymptotic stability is derived. Simulation and experimental investigations demonstrate the effectiveness of the proposed method in the real world.

Piecewise continuous hybrid systems based observer design for linear systems with variable sampling periods and delay output

The present paper deals with a new continuous undelayed state observer design approach by using only the sampled and delayed measurements where the sampling period and delayed value are variable and unknown. This proposed piecewise continuous observer (PCO), which is derived by using the theory of a particular hybrid systems called piecewise continuous hybrid systems (PCHS), has a very simple structure and can be easily implemented to the networked visual serving systems. This type PCO observer can be also adapted easily according to other kind feedbacks, such as sampled output, delayed output, sampled and delayed state, sampled state, or delayed state whose sampling periods and delayed values are unknown. The proposed PCO observer stability is also analyzed and demonstrated. Moreover, to show the proposed PCO observer performance, a comparison with a Lyapunov–Krasovskii technique and descriptor representation based observer is conducted via a numerical example.

Nonfragile Reliable Guaranteed Cost Controller Design for Networked Control System with Variable Sampling Period Sensors

In this paper, the problem of nonfragile reliable guaranteed cost control for networked control systems with time-varying sampling period sensors and actuator failures is concerned for a given quadratic cost function. For linear time-invariant controlled plant, under the assumption that the sampling period is time-varying within a certain known bound, the time delay is constant and shorter than the sampling period of the sensors, the system is transformed into a time-varying discrete time system, where the time-varying sampling period parts are transformed into norm bounded un- certainties of the structure parameter. A new linear matrix inequality (LMI)-based approach is proposed to derive a suffi- cient condition for the existence of nonfragile reliable guaranteed cost controller. Furthermore, the design method of the optimal nonfragile reliable guaranteed cost controller is formulated to minimize the upper bound of the closed-loop sys- tem cost. A numerical example is given to show the usefulness and effectiveness of the proposed method.

Consensus of Discrete Multiagent System with Various Time Delays and Environmental Disturbances

In this paper, the consensus problem of discrete multiagent systems with time varying sampling periods is studied. Firstly, with thorough analysis of various delays among agents, the control input of each agent is designed with consideration of sending delay and receiving delay. With construction of discrete dynamics of state error vector, it is proved by applying Halanay inequality that consensus of the system can be reached. Further, the definition of bounded consensus is proposed in the situation where environmental disturbances exist. In order to handle this problem, the Halanay inequality is extended into a more general one with boundedness property. Based on the new Halanay inequality obtained, the boundedness of consensus error is guaranteed. At last, simulation examples are presented to demonstrate the theoretical conclusions.

Sampled-data leader-following consensus for nonlinear multi-agent systems with Markovian switching topologies and communication delay

This paper is concerned with sampled-data leader-following consensus of nonlinear multi-agent systems with random switching network topologies and communication delay. By modeling the switching of network topologies by a Markov process and considering the effect of communication delay, a new sampled-data consensus control protocol with variable sampling period is proposed. With this protocol, the leader-following consensus problem is equivalently converted to the stability of a class of Markovian jump systems with a time-varying delay. Then, by employing Lyapunov–Krosovskii functional method and the weak infinitesimal operation, a new delay-dependent stability criterion is derived, which ensures that the leader-following consensus can be globally exponentially achieved in mean-square sense. Based on this criterion, the switching consensus controller gains are obtained by solving a set of linear matrix inequalities. Finally, a numerical example is given to illustrate the effectiveness of the design method.

Three-phase harmonics measurement method based on mSDFT

This work presents a three-phase harmonics measurement method based on the mSDFT (Modulated Sliding Discrete Fourier Transform) and a variable sampling period technique. The proposal allows measuring the harmonic components of a three-phase signal and computes the corresponding imbalance by estimating its positive, negative and zero sequence. In addition, an adaptive variable sampling period is used in order to obtain a sampling frequency multiple of the main frequency. mSDFT high rejection to distortions in the electrical network and flexibility of proposed method makes it an interesting alternative for the design of grid power monitors.

Reliable Guaranteed Cost Control of Networked Control System with Variable Sampling Period

Reliable Guaranteed Cost Control of Networked Control System with Variable Sampling Period

Empirical relationships among money, output and consumer prices in nine Muslim-majority countries

This paper highlights the role of price stability in the integrity and sustainability of Islamic banking and finance (IBF) while investigating the sources of inflation and its volatility in nine Muslim-majority countries which have introduced IBF since the late 1970s. The empirical results, obtained by the Engle–Granger, Johansen and autoregressive distributed lag (ARDL) bounds tests with data extending back as far as the 1950s, suggest the presence of those cointegral and causal relations among money, output and prices that are implied by classical monetary theory. Balanced-panel results obtained by analysis of the same data-set over the shorter period 1975–2010 reinforce the results obtained for the individual countries for the varying sample periods.

Harmonics Measurement With a Modulated Sliding Discrete Fourier Transform Algorithm

Accurate harmonics estimation has become a key issue in power quality assessment. This paper deals with a discrete Fourier transform (DFT)-based measurement technique, which can be easily employed to accurately determine the harmonic components of a distorted signal, i.e., voltage or current. The proposed method is based on a modulated sliding DFT algorithm, which is unconditionally stable and does not accumulate errors due to finite precision representation, and a variable sampling period technique (VSPT) to achieve a frequency adaptive mechanism. It is worth noting that the VSPT changes the sampling period for a variable grid frequency condition, leading to a constant sampling frequency under steady-state conditions. The proposed method provides: 1) high degree of accuracy; 2) structural/performance robustness; and 3) frequency adaptability. Given the modular nature of the method, it is implemented on a field programmable gate array. Simulations and experimental tests are shown to verify the performance of the proposed method.

Repetitive Control With Adaptive Sampling Frequency for Wind Power Generation Systems

This paper presents a novel repetitive control (RC) for wind power generation systems (WPGS), which achieves optimal performance in steady-state conditions due to a variable sampling/switching period technique (VSPT). The main objective of VSPT is to obtain an integer number of samples per grid period, which solves the main problem of RC, i.e., the loss of rejection to periodic disturbances due to grid frequency drift. The sampling/switching frequency is adjusted with a variable sampling period filter phase-locked loop, which also adds robustness to the system due to its inherent tolerance to grid voltage distortion and unbalances, and events such as frequency steps and faults. The control and synchronism subsystems are described, designed, and verified experimentally in a 10-kW WPGS. The results obtained prove the accuracy of the proposed control even under severe disturbances, typical in grids with high WPGS penetration, providing ancillary functions to enhance reliability and reduce operational costs.

Sampled-data H∞ filtering of Takagi–Sugeno fuzzy systems with interval time-varying delays

The sampled-data H∞ filtering for a continuous-time Takagi–Sugeno fuzzy system with an interval time-varying state delay is investigated, where the measurement outputs from the plant to the filter are assumed to be sampled at discrete instants with a variable period. Firstly, by means of a newly proposed inequality bounding technique and a new Lyapunov–Krasovskii functional, the fuzzy sampled-data H∞ filtering performance analysis is carried out such that the resultant filter error system is asymptotically stable with a prescribed H∞ attenuation performance index. Secondly, sufficient conditions on the existence of fuzzy sampled-data H∞ filters are derived in the simultaneous presence of the time-varying state delay and the variable sampling period. The proposed bounding inequality lies in its more tightness and alleviates the enlargement of some inverse “coefficients” resulting from the utilization of the well-known Jensen integral inequality. Compared with some existing Lyapunov–Krasovskii functionals, more information about the relationship among the current state and its delayed state is considered. The upper bound of the derivative of the time-varying state delay is not required to be less than one. Different from some existing results in the literature, by applying the proposed results, each different value of such an upper bound (greater than one) leads to a different H∞ disturbance attenuation level. Finally, a numerical example and a modified continuous stirred tank reactor system are given to show the effectiveness of the proposed results.

Mixed H_/H<SUB align="right">∞ fault detection observer design for networked control system with variable sampling period

For networked control system (NCS) with time-varying sampling period and time-delay, a discrete-time model with parameter uncertainties lying inside a polytopic framework is proposed. Based on the finite frequency parameter dependent quadratic H∞ index performance for minimising the disturbance and the corresponding H– index performance for maximising the worst-case fault sensitivity, a fault detection observer is designed for residual generation. By the aid of the generalised Kalman-Yakubovich-Popov (GKYP) lemma, the existence conditions of such an observer are given in terms of linear matrix inequalities (LMIs). A numerical example is given to illustrate the effectiveness of the proposed approach.

Iterative Learning Control for Periodic Systems using Model Predictive Methods with adaptive sampling rates

This paper addresses iterative learning control (ILC) for periodic systems using model predictive and optimization methods to redesign trajectories and reject periodic disturbances. Stability and optimality of these optimization methods is analysed and illustrated on simulations. The additional prospects of the optimization formulation (e.g. including energy costs, system identification) referred to the trajectory planning are accentuated. To reduce the calculation effort of the optimization algorithm a variable and adaptive sampling period is introduced. The advantages compared to classical ILC methods especially in consideration of constraints are presented.

Remote physiological and GPS data processing in evaluation of physical activities

The monitoring of data from global positioning system (GPS) receivers and remote sensors of physiological and environmental data allow forming an information database for observed data processing. In this paper, we propose the use of such a database for the analysis of physical activities during cycling. The main idea of the proposed algorithm is to use cross-correlations between the heart rate and the altitude gradient to evaluate the delay between these variables and to study its time evolution. The data acquired during 22 identical cycling routes, each about 130km long, include more than 6,700 segments of length 60s recorded with varying sampling periods. General statistical and digital signal processing methods used include mathematical tools to reject gross errors, resampling using selected interpolation methods, digital filtering of noise signal components, and estimating cross-correlations between the position data and the physiological signals. The results of a regression between GPS and physiological data include the estimate of the time delay between the heart rate change and gradient altitude of about 7.5s and its decrease during each training route.

Design of An Advanced Time Delay Measurement and A Smart Adaptive Unequal Interval Grey Predictor for Real-Time Nonlinear Control Systems

This paper is a generation step for developing a novel control methodology based on a variable sampling period (VSP) approach to deal with nonlinear systems containing random delays. The proposed VSP is constructed from an advanced time delay measurement (TDM) method and a novel time delay prediction (TDP) method. The TDM is built to measure real working time of the controlled system, consequently observing a set of actual system delays. Next, the TDP is based on a so-called Smart Adaptive Unequal Interval Grey Model with single-variable first-order—SAUIGM(1,1) to forecast the system delay in the next working step for adjusting the sampling period in order to eliminate bad effects of time delays on the control performance. The SAUIGM(1,1) model was developed from the GM(1,1) model with four significant improvements. It can be easily applied to any practical prediction problem and achieve high prediction accuracy even in case of sparse or largely noisy data. Real-time delay measurements and predictions have been carried out with several examples to verify the proposed TDM and TDP methods. The results indicate that the designed TDM and TDP have strong potential to be applied to the suggested VSP methodology for nonlinear control systems.

Frequency Adaptive PLL for Polluted Single-Phase Grids

This paper proposes a frequency adaptive phase-locked loop (PLL) for use in single-phase systems. The main objective is to obtain a reliable synchronization signal even in polluted grids, where the fundamental frequency is contaminated with harmonics, or present variations in phase, amplitude, and/or frequency. The proposed PLL is based on the concept of a variable sampling period technique, already implemented in a three-phase digital synchronization method proposed by the authors. This single-phase method allows us to automatically adjust the sampling frequency to be an integer multiple of the line frequency. In this case, the phase error is calculated just by one multiplication, thereby reducing implementation. A sliding Goertzel transform-based filter is also used in the loop to reject the undesired effects of this phase error detector and line disturbances, such as harmonics. To stabilize the loop, a controller that maximizes the bandwidth with an acceptable transient is introduced. The characteristics of the proposed single-phase PLL are described and the experimental results obtained from a DSP implementation are presented. A set of comparative simulations between the proposed PLL and some single-phase PLL described in the literature are conducted to validate the method. The advantages of the proposed system over other methods analyzed are also dealt with. The robustness of the system is verified by the experimental tests conducted as well as by the harmonic filtering properties. The system is also characterized by its simple architecture, which allows us to provide a high dynamic response with a very much reduced number of calculations.