Equivalent Input Disturbance-Based Control: Analysis, Development, and Applications.

This article reviews the concept, analysis, development, and applications of the equivalent-input-disturbance (EID) approach. First, the definition and existence of the EID are given, and the configuration of the EID estimator is provided. Next, estimation errors in the conventional EID approach are explained, and error-suppression methods are exhibited, which improve the disturbance-rejection performance. Then, this article describes how to apply the EID approach and associate challenges in dealing with nonlinearities, time delays, and uncertainties. Moreover, this article reviews some additional meaningful studies that cannot be categorized into the above-mentioned classes. Finally, some conclusions and future directions are given. The EID approach has been successfully used to suppress the influences of exogenous disturbances, nonlinearities, time delays, and uncertainties in many control systems to improve control performance and robustness. Studies can further rich the theory of the EID approach in the future, such as designing evaluation index, improving disturbance-rejection performance, developing new applications, and combining with other control theory.

Nonlinear swing-down control of the Acrobot: Analysis and optimal gain design.

In this paper, we address the swing-down control of the Acrobot, a two-link planar robot operating in a vertical plane with only the second joint being actuated. The control objective is to rapidly stabilize the Acrobot around the downward equilibrium point, with both links in the downward position, from almost all initial states. Under the conditions of no friction and measurability of only the angle and angular velocity of the actuated joint, we present a sinusoidal-derivative (SD) controller. This controller consists of a linear feedback of the sinusoidal function of the angle of the actuated joint and a linear feedback of its angular velocity. We prove that the control objective is achieved if the sinusoidal gain is greater than a negative constant and the derivative gain is positive. We establish crucial relationships between the relative stability of the Acrobot under the SD controller and its physical parameters, presenting analytically all optimal control gains. These gains minimize the real parts of the dominant poles of the linearized model of the resulting closed-loop system around the downward equilibrium point. We demonstrate that the resulting dominant closed-loop poles can be double complex conjugate poles, or a quadruple real pole, or a triple real pole, depending on the Acrobot's physical parameters. Simulation studies indicate that the proposed SD controller outperforms the derivative (D) controller in rapidly stabilizing the Acrobot at the downward equilibrium point.

Deep optimization design of 2D repetitive control systems with saturating actuators: An adaptive multi-population PSO algorithm.

This paper presents an optimization design method for a two-dimensional (2D) modified repetitive control system (MRCS) with an anti-windup compensator. Using lifting technology, a 2D hybrid model of the MRCS considering actuator saturation is established to describe the control and learning of the repetitive control. A linear-matrix-inequality (LMI)-based sufficient condition is derived to ensure the stability of the MRCS. Two tuning parameters, the selection of which is critical to the system design, are used in the LMI to adjust the control and learning, and hence the reference-tracking performance. A new cost function, developed through time domain analysis, directly evaluates the control performance of the system without calculating control errors, thus reducing the optimization time. Based on this cost function, an adaptive multi-population particle swarm optimization algorithm is presented to select an optimal pair of tuning parameters in which multiple populations cooperatively search in non-intersecting search intervals. An anti-windup term is added between the low-pass filter and the time delay in the modified repetitive controller to mitigate the undesirable effect of actuator saturation on system performance and stability. Simulations and experiments on the speed control of a rotation control system demonstrate the validity of the approach.

Suppression of Packet Losses and Disturbances in Networked Control Systems Based on Equivalent-Input-Disturbance Approach.

This article presents a method of suppressing packet losses and exogenous disturbances for a networked control system (NCS) subject to network-introduced delays. The NCS has two feedback loops: 1) a local one and 2) a main one. The local feedback loop contains a state observer, an equivalent-input-disturbance (EID) estimator, and state feedback. It is used to ensure prompt disturbance suppression. The controller in the main feedback loop contains an internal model to track a reference input. The system is divided into two subsystems for the design of controllers. The state-observer gain is designed for one subsystem using the concept of perfect regulation to ensure disturbance estimation performance. The state-feedback gains of the other subsystem are designed based on a stability condition in the form of a linear matrix inequality (LMI). A tracking specification is embedded in the LMI-based stability condition to ensure satisfactory tracking performance. A case study on a two-finger robot hand control system and a comparison with a Smith-EID and H∞ controller approach validate the effectiveness and superiority of the presented method.

On convergence of extended state observers for nonlinear systems with non-differentiable uncertainties.

The analysis of convergence of extended state observers (ESOs) requires the total disturbance to be differentiable. However, this requirement is not satisfied in many control engineering practices. In this paper, we attempt to analyze the convergence of ESOs for nonlinear systems with non-differentiable uncertainties. A decomposition method is first presented to divide the non-differentiable total disturbance into a differentiable signal and a bounded but non-differentiable signal. Based on this decomposition, we give out the convergence of both nonlinear and linear ESOs (NLESO/LESO), low- and high-power ESOs (LPESO/HPESO), and fixed-time ESO (FxESO). We also derive the explicit formulas for the estimation errors of these ESOs. Simulations and experiments demonstrate the correctness of the analysis results.

Designing low-pass filter in equivalent-input-disturbance compensator for improving disturbance-rejection performance.

This paper presents a high-order low-pass filter for the equivalent-input-disturbance (EID) approach to improving the disturbance-rejection performance. The configuration characteristic of the presented filter clearly explains the reason why the disturbance-rejection performance is improved and provides a guideline to design it. Using the presented filter to replace the conventional filter derives a high-order EID (HEID) approach. It is easy to apply the small-gain theorem in deriving stability conditions of the HEID-based control system. Moreover, the presented filter is proved to be better than the conventional one. Finally, a comparison shows the validity and superiority of the presented method. And a simulation result shows that the HEID approach is easily extended in a multiple-input, multiple-output system even with effects of a white noise and parameter uncertainties.

Disturbance Rejection and Robustness of Improved Equivalent-Input-Disturbance-Based System.

This article presents an improved equivalent-input-disturbance (EID) approach to handle unknown disturbances and plant uncertainties. The disturbances and uncertainties are treated as a lumped disturbance in an EID-based control system. The effect of the lumped disturbance is compensated by an EID estimator. A constraint between design parameters and uncertainties is imposed on the design of the estimator. In addition, there are insufficient analyses of the influence of uncertainties on the control performance and the stability of the system. A new filter is devised for an improved EID estimator in this article to remove the constraint. This ensures that the sensitivity of the system to disturbances at low frequencies can be freely decreased. An analysis of the system reveals that uncertainties not only influence disturbance-rejection and reference-tracking performance but also affect system stability. A sufficient stability criterion is derived with consideration of uncertainties. The validity of the presented method is demonstrated by simulation and experimental results.

Active disturbance rejection for time-varying state-delay systems based on equivalent-input-disturbance approach.

Exogenous disturbances largely affect the control performance of systems with time delays. This study considers a control problem of rejecting a disturbance in a PI control system for a time-varying state-delay plant. The equivalent-input-disturbance (EID) approach is integrated in a PI control system. An EID estimator estimates the overall effects of a time-varying delay and a disturbance. An EID estimate is combined into a PI control law to improve control performance. A less-conservative stability condition of the control system is derived using a Lyapunov-Krasovskii functional together with the Jensen's integral inequality and the reciprocally convex combination lemma. Parameters of the controllers in the system are calculated using the condition. Engine idle speed control is used to verify the effectiveness of this approach. Compared with the generalized extended-state observer and the sliding-mode control methods, our method reduced the tracking error to about one third and one sixth, respectively. This demonstrates the validity and superiority of our method.

Muscle Fatigue Analysis With Optimized Complementary Ensemble Empirical Mode Decomposition and Multi-Scale Envelope Spectral Entropy.

The preprocessing of surface electromyography (sEMG) signals with complementary ensemble empirical mode decomposition (CEEMD) improves frequency identification precision and temporal resolution, and lays a good foundation for feature extraction. However, a mode-mixing problem often occurs when the CEEMD decomposes an sEMG signal that exhibits intermittency and contains components with a near-by spectrum into intrinsic mode functions (IMFs). This paper presents a method called optimized CEEMD (OCEEMD) to solve this problem. The method integrates the least-squares mutual information (LSMI) and the chaotic quantum particle swarm optimization (CQPSO) algorithm in signal decomposition. It uses the LSMI to calculate the correlation between IMFs so as to reduce mode mixing and uses the CQPSO to optimize the standard deviation of Gaussian white noise so as to improve iteration efficiency. Then, useful IMFs are selected and added to reconstruct a de-noised signal. Finally, considering that the IMFs contain abundant frequency and envelope information, this paper extracts the multi-scale envelope spectral entropy (MSESEn) from the reconstructed sEMG signal. Some original sEMG signals, which were collected from experiments, were used to validate the methods. Compared with the CEEMD and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), the OCEEMD effectively suppresses mode mixing between IMFs with rapid iteration. Compared with approximate entropy (ApEn) and sample entropy (SampEn), the MSESEn clearly shows a declining tendency with time and is sensitive to muscle fatigue. This suggests a potential use of this approach for sEMG signal preprocessing and the analysis of muscle fatigue.

Disturbance suppression for quadrotor UAV using sliding-mode-observer-based equivalent-input-disturbance approach.

This paper presents a new control scheme for quadrotor unmanned aerial vehicle attitude control and disturbance suppression. A quadrotor dynamic model is divided into two subsystems: fully-actuated and under-actuated. While the PID method is used to control the fully-actuated subsystem, a sliding-mode-observer-based equivalent-input-disturbance approach is used to control the under-actuated subsystem. The system design is simple, and it is globally uniformly ultimately bounded. Simulations and comparisons demonstrate the effectiveness of the method.

A New Unsupervised Detector of High-Frequency Oscillations in Accurate Localization of Epileptic Seizure Onset Zones.

This paper presents a new unsupervised detector for automatically detecting high-frequency oscillations (HFOs) using intracranial electroencephalogram (iEEG) signals. This detector does not presuppose a specific number of clusters and has a good performance. First, the HFO candidates are detected by an initial detection method which distinguishes HFOs from background activities. Then, as significant features, fuzzy entropy, short-time energy, power ratio, and spectral centroid of the HFO candidates are investigated and constructed as a feature vector. Finally, the feature vector is used as the input of the fuzzy- -means-quantization-error-modeling-based expectation-maximization-Gaussian mixture model clustering algorithm. This algorithm has the advantages of detecting HFOs and avoiding false detection caused by artifacts. The concentrations of detected HFOs are used to localize epileptic seizure onset zones in epileptic iEEG signal analysis. A comparison shows that our detector provides better localization performance in terms of sensitivity and specificity than five existing detectors.

Fast, Accurate Localization of Epileptic Seizure Onset Zones Based on Detection of High-Frequency Oscillations Using Improved Wavelet Transform and Matching Pursuit Methods.

This letter describes the improvement of two methods of detecting high-frequency oscillations (HFOs) and their use to localize epileptic seizure onset zones (SOZs). The wavelet transform (WT) method was improved by combining the complex Morlet WT with Shannon entropy to enhance the temporal-frequency resolution during HFO detection. And the matching pursuit (MP) method was improved by combining it with an adaptive genetic algorithm to improve the speed and accuracy of the calculations for HFO detection. The HFOs detected by these two methods were used to localize SOZs in five patients. A comparison shows that the improved WT method provides high specificity and quick localization and that the improved MP method provides high sensitivity.

Delay-dependent guaranteed-cost control based on combination of Smith predictor and equivalent-input-disturbance approach.

This paper presents a new system configuration and a design method to improve control performance for a system with an input time delay and disturbances. The equivalent-input-disturbance approach is extended to handle a time-delay system. It is combined with the Smith predictor to reject disturbances. A delay-dependent stability condition is devised in terms of a matrix inequality by using the free-weighting matrix approach. The gain of the observer is designed by applying the cone complementary linearization method to the matrix inequality. A numerical example demonstrates the validity of the method.

A novel resource management method of providing operating system as a service for mobile transparent computing.

This paper presents a framework for mobile transparent computing. It extends the PC transparent computing to mobile terminals. Since resources contain different kinds of operating systems and user data that are stored in a remote server, how to manage the network resources is essential. In this paper, we apply the technologies of quick emulator (QEMU) virtualization and mobile agent for mobile transparent computing (MTC) to devise a method of managing shared resources and services management (SRSM). It has three layers: a user layer, a manage layer, and a resource layer. A mobile virtual terminal in the user layer and virtual resource management in the manage layer cooperate to maintain the SRSM function accurately according to the user's requirements. An example of SRSM is used to validate this method. Experiment results show that the strategy is effective and stable.

Existence and global exponential stability of periodic solution for high-order discrete-time BAM neural networks.

This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young's inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks.

Design of a robust observer-based modified repetitive-control system.

This paper concerns the design of a robust observer-based modified repetitive-control system for a class of strictly proper plants with periodic time-varying uncertainties. It exploits the inherent structure characteristics of repetitive control to convert the design problem to a robust stabilization problem for a continuous-discrete two-dimensional system. The singular-value decomposition and Lyapunov stability theory are used to derive a linear-matrix-inequality-based design algorithm for the parameters of control and state-observer gains. Two tuning parameters are introduced to perform the preferential adjustment of control and learning. A numerical example illustrates the adjusting procedure and demonstrates the validity of the method.

Comprehensive unified control strategy for underactuated two-link manipulators.

This paper presents a unified treatment of the motion control of underactuated two-link manipulators, including acrobots and pendubots. The motion space is divided into two areas: swing-up and attractive; and control laws are designed for each. First, a control law based on a weak-control Lyapunov function (WCLF) is employed to increase the energy of and control the posture of the actuated link in the swing-up area. Next, one parameter of the WCLF is chosen to be a nonlinear function of the state to avoid singularities. Then, another parameter of the control law is adjusted based on the state to improve the control performance. Finally, an optimal control law is designed for the attractive area. Stability is guaranteed in the swing-up area by the use of a WCLF based on LaSalle's invariance principle. Moreover, the global stability of the control system is guaranteed by integrating the WCLF and a nonsmooth Lyapunov function.

Di-µ-sulfato-bis-[diaqua-(1H-imidazo[4,5-f][1,10]phenanthroline)nickel(II)] dihydrate.

In the title compound, [Ni(2)(SO(4))(2)(C(13)H(8)N(4))(2)(H(2)O)(4)]·2H(2)O, the complete dimeric complex is generated by an inversion center. The Ni(II) atoms are octa-hedrally coordinated by two N atoms from one 1H-imidazo[4,5-f][1,10]phenanthroline (IP) ligand and two O atoms from two adjacent sulfate ions forming the equatorial plane, with two coordinated water mol-ecules in the axial sites. Both of the sulfate ions act as bidentate-bridging ligands connecting the two Ni(II) ions, thus generating a binuclear complex. In the crystal structure, O-H⋯O and O-H⋯N hydrogen bonds involving the coordinated and uncoordinated water mol-ecules and N-H⋯O links lead to the formation of a two-dimensional sheet structure developing parallel to (010). Weak π-π stacking inter-actions [centroid-centroid separation = 3.613 (2) Å] between the IP ligands also occur.

An improved global asymptotic stability criterion for delayed cellular neural networks.

A new Lyapunov-Krasovskii functional is constructed for delayed cellular neural networks, and the S-procedure is employed to handle the nonlinearities. An improved global asymptotic stability criterion is also derived that is a generalization of, and an improvement over, previous results. Numerical examples demonstrate the effectiveness of the criterion.