Dynamic Gain Research Articles

Fixed-Time Stabilization of a Class of Strict-Feedback Nonlinear Systems via Dynamic Gain Feedback Control

This paper presents a novel fixed-time stabilization control (FSC) method for a class of strict-feedback nonlinear systems involving unmodelled system dynamics. The key feature of the proposed method is the design of two dynamic parameters. Specifically, a set of auxiliary variables is first introduced through state transformation. These variables combine the original system states and the two introduced dynamic parameters, facilitating the closed-loop system stability analyses. Then, the two dynamic parameters are delicately designed by utilizing the Lyapunov method, ensuring that all the closed-loop system states are globally fixed-time stable. Compared with existing results, the “explosion of complexity” problem of backstepping control is avoided. Moreover, the two designed dynamic parameters are dependent on system states rather than a time-varying function, thus the proposed controller is still valid beyond the given fixed-time convergence instant. The effectiveness of the proposed method is demonstrated through two practical systems.

Velocity-Oriented Dynamic Control–Display Gain for Kinesthetic Interaction with a Grounded Force-Feedback Device

Kinesthetic interaction is an important interaction method for virtual reality. Current kinesthetic interaction using a grounded force-feedback device, however, is still considered difficult and time-consuming because of the interaction difficulty in a three-dimensional space. Velocity-oriented dynamic control–display (CD) gain has been used to improve user task performance with pointing devices, such as the mouse. In this study, we extended the application of this technique to kinesthetic interaction and examined its effects on interaction speed, positioning accuracy and touch perception. The results showed that using this technique could improve interaction speed without affecting positioning accuracy in kinesthetic interaction. Velocity-oriented dynamic CD gain could negatively affect touch perception in softness while using large gains. However, it is promising and particularly suitable for kinesthetic tasks that do not require high accuracy in touch perception.

Global output feedback control for large‐scale time‐delay systems with inherent nonlinearities and measurement uncertainty

AbstractThis paper investigates the problem of global state regulation by output feedback for a class of large‐scale nonlinear time‐delay systems with inherent nonlinearities and unknown measurement sensitivity. The uncertain nonlinearities are bounded by nonlinear growth of lower triangular unmeasurable (delayed) states multiplied by the unknown constant, polynomial‐of‐output and polynomial‐of‐input. Different from closely related works, the simultaneous existence of complicated nonlinearities and unknown measurement sensitivity makes the problem more involved and complex. Based on the dynamic gain scaling technique, we design a set of new adaptive output feedback controllers with a simpler structure by constructing two Lyapunov–Krasovskii functionals appropriately, which can globally regulate all states of the large‐scale systems. An illustrative example is proposed to demonstrate the validity of the presented control scheme.

Global Stabilization for Uncertain Nonlinear Time-Delay Systems With Saturated Input

In this article, global stabilization for a class of nonlinear uncertain time-delay systems with saturated input is considered. The saturated input is handled by a new auxiliary system with dynamic gain and the linear growth condition with unknown growth rates is removed. A novel adaptive observer-controller coupling design framework is put forward, under which the closed-loop system is globally bounded. Finally, a simulation shows that the proposed technique is effective.

Output Feedback Tracking Control for a Class of Nonlinear Systems With Sensor Uncertainties

In this article, we consider adaptive output feedback tracking for a class of nonlinear systems with uncertain parameters, multiplicative and additive sensor uncertainties, and external disturbances. A state observer and an adaptive controller are constructed based on gain scaling technique by which a dynamic gain is designed to compensate for the effects of the sensor uncertainties. The adaptive controller is linear-like and, therefore, is simple and easy to implement. It is shown that with this proposed scheme, all states of the closed-loop system are bounded and the real tracking error can converge to an arbitrarily small residual set. Simulation and experiment are presented to illustrate the effectiveness of the proposed scheme.

Connectivity-Preserving Formation Tracking for Multiple Double Integrators by a Self-Tuning Adaptive Distributed Observer

In this letter, we study the distributed formation tracking problem for multiple double-integrator systems with connectivity preservation over a state-dependent communication network. In particular, we employ an adaptive distributed observer for the leader system that can estimate both the state and the system matrix of the leader. As a result, unlike the existing results, we do not require all vehicles to know the system matrix of the leader. Furthermore, the adaptive distributed observer incorporates a self-tuning dynamic observer gain, which eliminates the need of computing the observer gain in advance. The effectiveness of our approach is illustrated by an example.

Data-Driven Learning Extended State Observers for Nonlinear Systems: Design, Analysis and Hardware-in-Loop Simulations

This paper considers the disturbance/uncertainty estimation of first-order nonlinear system subject to fully unknown internal dynamic, external disturbance, and unknown control input gain. Compared with existing extended state observer (ESO) where priori knowledge of model parameter such as nominal input gain should be known as a priori, reducedand full-order data-driven learning ESOs are developed for estimating the lumped disturbance and control input gain. A salient feature of the proposed data-driven learning ESOs is that the unknown input gain and lumped disturbance can be estimated synchronously, in the meantime, the estimation convergence is guaranteed benefiting from the data-driven approach. Hardware-in-loop simulation is carried out to substantiate the performance of the proposed data-driven learning ESO for surge speed tracking of a robotic marine vehicle without knowing the model parameter in advance.

Electrical Performance Enhancement and Low-Frequency Noise Estimation of In2O3-Based Thin Film Transistor Based on Doping Engineering

In this work, solution-derived InErO thin films were deposited to act as the channel layers of thin film transistors (TFTs). The effect of Er doping content on the morphology, oxygen defects, optical properties of indium oxide (In2O3) films, and electrical performance of InErO/Al2O3 TFTs was systematically investigated. Based on experimental results, it can be inferred that InErO-TFTs with 5% Er doping content has demonstrated improved electrical performance, including field effect mobility ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu _{\text {FE}}$ </tex-math></inline-formula> ) of 17.55 cm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{{2}}\,\,\cdot \,\,\text{V}^{-{1}}\,\,\cdot \,\,\text{s}^{-{1}}$ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${I} _{\text{ON}}/{I} _{\text{OFF}}$ </tex-math></inline-formula> of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.70\times 10^{{7}}$ </tex-math></inline-formula> , a subthreshold swing (SS) of 0.16 V/dec and threshold voltage shift of 0.10 and 0.09 V under positive bias stress (PBS) and negative bias stress (NBS) for 1800 s, respectively. The illumination NBS (NBIS) measurements have indicated the degraded device stability by reducing the light wavelength, which can be due to the ionization of oxygen vacancies. Low-frequency noise (LFN) characterizations on devices have shown that the interfacial density of states of In2O3-based TFTs decreases after Er doping. To demonstrate the potential applications of InErO-TFTs in logic circuits, a resistor-loaded unipolar inverter based on InErO/Al2O3 has been integrated, demonstrating good dynamic response behavior and high gain of 10. These results have indicated the great potential of solution-driven InErO-based TFTs for future applications in low-cost and high-performance electronics.

A Global Control Strategy to Remove Slow Delay Conditions for Delayed Systems with Complicated Polynomial Terms

Nonlinear systems constantly suffer from time‐varying delays, which cover slow delays and nonslow delays. The existing results were used to impose slow delay conditions and were used to study the control problems, but few pieces of research studies have discussed the case of systems with nonslow delay. In this work, we remove the slow time‐delay condition and consider the nonlinear delayed system with complicated polynomial terms. By proposing a dynamic gain method and constructing a new Lyapunov–Razumikhin (L‐R) function, we successfully construct a stable controller, which guarantees that the plant is globally asymptotically stable (GAS). An example is utilized to verify the raised control scheme.

Distributed Adaptive Leader-Following Consensus for Nonlinear Multiagent Systems With Actuator Failures Under Directed Switching Graphs.

This article studies the distributed adaptive failures compensation output-feedback consensus for a class of nonlinear multiagent systems (MASs) with multiactuator failures allowing unmatched redundancy under directed switching graphs. With estimated information of neighbors, a novel distributed reference generator is designed. To compensate the unmeasured state variables of each agent, a reduced-order dynamic gain filter is constructed. Based on the generator and filter, and using the recursive design method, a distributed adaptive protocol is designed, where the adaptive technique is used to compensate the actuator failures. The proposed scheme can significantly relax conditions on the communication graph, which allows the graph to be disconnected at any time instant. The number of introduced variables in the filter and its dimension is greatly reduced and, thus, reduces the numerical challenge. The output-feedback consensus for nonlinear MASs with actuator failures and possible unmatched actuator redundancy is addressed for the first time. The consensus error can converge to an arbitrarily small set not affected by actuator failures, and the resulting closed-loop system is semiglobally stable. Finally, simulation results are given to illustrate the effectiveness of the proposed method.

Dynamic Gain Adaptation in Linear Quadratic Regulators

Dynamic Gain Adaptation in Linear Quadratic Regulators

Asymptotic Tracking Control of Nonlinear Time-Delay Systems With Mismatched Disturbances

This brief considers the asymptotic tracking control problem of nonlinear time-delay system in the presence of mismatched disturbances. By using dynamic gain based design method, a delay-independent dynamic tracking controller is constructed. Besides, a smooth function is introduced into the virtual controller to compensate the mismatched disturbances. By choosing appropriate Lyapunov-Krasovskii functionals, it is shown that the closed-loop system signals are bounded, and the system output can asymptotically track the desired signal. Finally, a simulation example is conducted to show the effectiveness of the proposed control scheme.

Dynamic accentuated antagonism of heart rate control during different levels of vagal nerve stimulation intensity in rats.

Accentuated antagonism refers to a phenomenon in which the vagal effect on heart rate (HR) is augmented by background sympathetic tone. The dynamic aspect of accentuated antagonism remains to be elucidated during different levels of vagal nerve stimulation (VNS) intensity. We performed VNS on anesthetized rats (n = 8) according to a binary white noise signal with a switching interval of 500 ms at three different stimulation rates (low-intensity: 0-10 Hz, moderate-intensity: 0-20 Hz, and high-intensity: 0-40 Hz). The transfer function from VNS to HR was estimated with and without concomitant tonic sympathetic nerve stimulation (SNS) at 5 Hz. The asymptotic low-frequency (LF) gain (in beats/min/Hz) of the transfer function increased with SNS regardless of the VNS rate [low-intensity: 3.93 ± 0.70 vs. 5.82 ± 0.65 (P = 0.021), moderate-intensity: 3.87 ± 0.62 vs. 5.36 ± 0.53 (P = 0.018), high-intensity: 4.77 ± 0.85 vs. 7.39 ± 1.36 (P = 0.011)]. Moreover, SNS slightly increased the ratio of high-frequency (HF) gain to the LF gain. These effects of SNS were canceled by the pretreatment of ivabradine, an inhibitor of hyperpolarization-activated cyclic nucleotide-gated channels, in another group of rats (n = 6). Although background sympathetic tone antagonizes the vagal effect on mean HR, it enables finer HR control by increasing the dynamic gain of the vagal HR transfer function regardless of VNS intensity. When interpreting the HF component of HR variability, the augmenting effect from background sympathetic tone needs to be considered.

Global adaptive event-triggered output feedback controller design for high-order nonlinear systems

This article focuses on the adaptive event-triggered output feedback stabilization problem for a class of high-order systems with uncertain output function. Firstly, an adaptive event-triggered mechanism with a dynamic gain is designed for the nominal system. Then the gain is employed into the observer and event-triggered controller to dominate the nonlinearities. Thirdly, it is proved that all system states converge to zero and the Zeno-behavior is excluded. Finally, a numerical example reveals the effectiveness of the proposed event-triggered control strategy.

Modified [formula omitted]-law Root Companding for PAPR reduction in GFDM signals

Generalized Frequency Division Multiplexing (GFDM) is a multicarrier modulation technique and able to meet the requirements of next generation wireless systems. But it exhibits high peak to average power ratio (PAPR), which degrades the efficiency of the power amplifier (PA). In this work, modified Root Companding and modified μ-law Root Companding are proposed to reduce PAPR in GFDM signals. The existing methods alter the average power due to expansion of small signals, whereas the proposed method keeps the average power as constant by adjusting both small and large signals. Therefore, the adjustment of dynamic gain in PA is not required. Transform gain and achievable PAPR reduction of the proposed methods are compared by varying companding metrics such as companding root R and companding parameter μ. Also, bit error rate (BER) performance is analysed over AWGN channel and the value of R, μ is chosen such that companding distortion is small. The theoretical PAPR distribution of the proposed methods are derived and validated with Monte-Carlo simulations. The BER performance over multipath fading channel is also analysed. Further, the BER, PAPR and power spectral density performance of the proposed methods are compared with conventional OFDM, GFDM and existing PAPR reduction methods. The computational complexity is also analysed.

Output feedback neural adaptive control design for nonlinear time-delay systems

This paper addresses the adaptive output feedback control design problem for a class of nonlinear systems with unknown state time delays by combining the dynamic gain and neural network. A novel reduced-order dynamic gain observer is introduced to estimate the unmeasured system states. Radial basis function neural networks (RBF NNs) are used to approximate unknown functions. An adaptive NN output feedback controller is designed based on the backstepping technique. By arranging the proper Lyapunov–Krasovskii functional, we prove that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded. Finally, a physical example and a numerical example are given to prove the effectiveness of the proposed control scheme.

FLS-based AHOSM control for driverless vehicle steering system with parameter uncertainty

This paper aims to address the tracking control problem for the steer-by-wire (SbW) system with uncertain nonlinearity and parameter uncertainty. First, the adaptive fuzzy logic system (FLS) is constructed to realize the intelligent modeling of the SbW system. In addition, an adaptive higher-order sliding mode (AHOSM) control with dynamic gain is designed to overcome the lumped uncertainties including inaccurate model-parameter and fuzzy logic system approximation error, and has the advantage of eliminating the gain-overestimation phenomenon effectively without the prior knowledge about the bounds of approximation error and parameter uncertainty. Furthermore, theoretical analysis based on Lyapunov stability theory is provided to verify that the real sliding mode can be established. Finally, simulations and vehicle experiments are given to evaluate the effectiveness and superiority of the proposed methods.

A Common-Ground-Type Five-Level Inverter with Dynamic Voltage Boost

Today, transformerless inverters (TIs) are widely applicable in different solar photovoltaic (PV) grid-connected applications owing to their promising features, such as higher efficiency and power density. However, high-frequency common-mode voltage (CMV) in these topologies can result in high leakage current, electromagnetic interference, and lack of safety, reducing the whole system’s reliability. To resolve the problems associated with TIs, this paper proposes a novel hybrid switched capacitor (SC)-based common-ground (CG) transformerless inverter (TI) topology, which can be applied in grid-connected photovoltaic (PV) applications. The boost inductor is integrated to achieve continuous input current and dynamic voltage gain. In addition, the proposed circuit comprises nine switches and two SCs with a single input DC source. It can generate five-level AC voltage with voltage boosting within a single-stage DC–AC power conversion. The working principles of the proposed topology, circuit description, and control technique are presented. Furthermore, the proposed inverter is comprehensively compared with other five-level TIs to show its superiority. Finally, a laboratory prototype is developed and tested to validate the practical viability of the proposed configuration.

Adaptive output-feedback control for exponential regulation

To date, most schemes of adaptive stabilization are confined to convergence, and cannot specify the convergence rate. As such, the possibility of excessively slow convergence could not be ruled out, which undermines the application scope of adaptive schemes. Such imperfection is mainly due to the limited capability of compensation/learning mechanisms which lack the ingredients affording specific convergence rate. For stronger applicability, more comprehensive compensation/learning mechanisms need to be exploited, inevitably aggravating control synthesis and analysis. This paper aims to enhance adaptive control in terms of convergence rate, and particularly, seeks exponential regulation via adaptive output feedback for stochastic nonlinear systems allowing large uncertainties coupling to unmeasurable states and dynamic uncertainties. To this end, a refined adaptive output-feedback scheme is established in the stochastic framework, though no non-stochastic counterpart exists. Critically, a novel dynamic high gain is introduced in a universal manner, with its updating law delicately incorporating the gain-dependent time-varying information in exponential form. The dynamic gain would not only become sufficiently large to capture the large uncertainties, but also render the desired convergence with the rate online regulated to match the dynamic uncertainties. In this way, an adaptive output-feedback controller based on dynamic-gain observer is designed, which guarantees the system and observer states to almost surely converge to zero at an exponential rate. The stochastic framework complicates the validity verification of the established scheme, entailing subtle martingale-based analysis. Correspondingly, a distinctive analysis pattern is developed for the resulting closed-loop system, to attain expected stochastic convergence and boundedness.

Common-Ground Grid-Connected Five-Level Transformerless Inverter With Integrated Dynamic Voltage Boosting Feature

A single-phase common-ground five-level (5L) inverter with a dynamic voltage conversion gain and capability of operating in a wide input voltage range and a single-stage energy conversion configuration is presented in this article. The proposed topology requires nine active power switches and is comprised of an integrated switched-boost (SB) module connected in series to a switched-flying-capacitor (SFC) cell. Two self-balanced capacitors with a single boost inductor in the integrated SB module are employed to generate a 5L output voltage waveform with a dynamic voltage conversion gain. The current stress profile of all the active and passive elements is kept within a permissible input current range. By adopting an extra diode-capacitor-inductor network into the integrated SB module and with the utilization of the same SFC cell, the proposed topology is extended to achieve a quadratic voltage conversion gain while retaining the quality of ac voltage waveform. Theoretical analysis, closed-loop control/modulation principles, design guidance, comparative study, and relevant experimental results obtained from a 1.5-kW laboratory-built prototype are presented to ascertain the operation and feasibility of the proposed system.