Explore the vast range of titles available.

This paper concerns with the problem of robust event-triggered data-driven control (DDC) considering control input and rate control constraints, simultaneously for discrete-time multi-input multi-output (MIMO) linear systems such that only the noisy data are measurable. Firstly, the data-dependent representation of the closed-loop system controlled by an event-triggered-based feedback control law is obtained. More precisely, to reduce the unnecessary communication resources, the control input updates and consequently, improve the system performance, event-triggered mechanism is utilized to design a stabilizing controller. Under a decreasing triggering threshold and a quadratic Lyapunov function, the ultimate boundedness stability (UBS) of the closed-loop system is ensured and the bounded region is expressed. Sufficient conditions for the UBS of the system are derived in terms of data-dependent linear matrix inequalities (LIMs). To meet the practical problems such as inherent limitations of the practical systems and to maximize the life-time of the actuators, the control input and rate control constraints are considered, simultaneously in the design procedure. In this scenario, the sufficient conditions are also obtained based on data-dependent LMIs. Finally, to demonstrate the effectiveness of the proposed control method, the recommended robust constrained event-triggered DDC is implemented to a numerical example and the simulation results demonstrate the validity of the proposed control approach. Moreover, a table is presented to compare the practical metrics such as robustness, necessities of the model plant identification, computational burden and control input constraints to verify the superiorities of the proposed method despite the existing results.

Soft robotics is an attractive and rapidly emerging field, in which actuation is coupled with the elastic response of the robot's structure to achieve complex deformation patterns. A crucial challenge is the need for multiple control inputs, which adds significant complication to the system. A novel concept of single‐input control of an actuator is proposed, which composes of interconnected bistable elements. Dynamic response of the actuator and predesigned differences between the elements are exploited to facilitate any desired multistate transition using a single dynamic input. Formulation and analysis of the control system's dynamics and pre‐design of its multiple equilibrium states, as well as their stability, are shown. Then, fabrication and demonstration are done experimentally on single‐input control of two‐ and four‐element actuators, where the latter can achieve transitions between up to 48 desired states. This work paves the way for next‐generation soft robotic actuators with minimal actuation and maximal dexterity. A concept for reducing the number of control inputs to one in a system with N degrees of freedom, is presented. Incorporating structural instabilities, cleverly, enables choosing any desired trajectory out of (N!)2 with only one input. The concept is demonstrated experimentally, along with analytical insights and numerical simulations. Such actuation ability will enable simpler, smaller, and cheaper robots.

Intraplatform competition has received scant attention in prior studies, which predominantly study interplatform competition. We develop a middle-range theory of how complementarity between input control and a platform extension’s modularization—by inducing evolution—influences its performance in a platform market. Primary and archival data spanning five years from 342 Firefox extensions show that such complementarity fosters performance by accelerating an extension’s perpetual evolution.

The paper presents four solutions to the voltage source inverter (VSI) control system with existing delays in the measurement channels and the middle switching frequency (25,600 Hz): Single-Input Single-Output Coefficient Diagram Method (SISO-CDM), Multi-Input Multi-Output Passivity-Based Control (MISO-PBC), Multi-Input Multi-Output One-Sample-Ahead Preview Controller (MISO-OSAP), and MISO-OSAP with Luenberger Observer (MISO-OSAP-LO). The theory, including adjustments to controller gains or to the coefficients of the characteristic equation of the closed-loop system, is presented. Simulations of the VSI operation with these control systems for the nonlinear load and the dynamic resistive load (per the requirements of the EN 62040-3 standard) are presented. The SISO-CDM and MISO-PBC are finally selected for experimental verification of the simulations. The results of the tests enable the selection of the control type for a particular VSI design based on its cost and an estimation of the advantages of the more expensive solution. The paper should help in engineering design according to the remarks in the paper.

As an underactuated system, the overhead crane is widely used to transport cargoes in industry according to its flexibility and lifting capacity. Many control strategies are designed based on single pendulum crane models, which ignore the hook’s mass and treat the payload as a mass point. However, the payload will swing around the hook when the payload is too large or the hook mass cannot be directly ignored, which is called double pendulum effects, making the dynamic more complex. In practical applications, input saturation and energy consumption should also be considered. To this end, we design an input-limited optimal controller for double pendulum cranes. Specifically, based on the defined performance index function and by solving the Hamilton–Jacobi–Bellman (HJB) equation, we can get an optimal controller satisfying the saturation constraint. In addition, the neural network is utilized to estimate the optimal performance index function. Furthermore, the convergence of state variables is proved theoretically, i.e. the trolley/rope length can converge to corresponding desired positions. Meanwhile, the hook’s swing and payload’s swing can also be eliminated. Finally, the simulation results are utilized to illustrate the performance of the designed optimal controller.

In this paper, the concentration is on researching a neural adaptive prescribed finite-time constraint quantized tracking control strategy for a class of stochastic nonlinear systems with external disturbances, input quantization and unknown initial conditions. In this control strategy, two designs are considered, namely, the performance constraint control design circumventing system initial condition and the control design in which the control input has a zero initial value. To achieve the two designs simultaneously, a class of mapping functions, input tuning functions, and a piecewise indirect constraint performance function are proposed. In addition, a new prescribed finite-time performance function is also given to guarantee better tracking error convergence. To address the stability analysis problem of the system under the new control strategy, a new proposition is presented as a supplement to the Lyapunov stability criterion in this paper. Based on these findings, a neural adaptive finite-time performance constraint quantized controller with an initial value of zero is obtained. The proposed controller guarantees that the constrained variable enters a prescribed region within a preset time, regardless of its initial condition. All the signals in the closed-loop system are bounded in probability. The simulation results demonstrate the effectiveness and the superiority of the proposed strategy.

Digitally controlled Dual-Input Doherty Power Amplifiers (DIDPAs) are becoming increasingly popular due to the flexible input signal splitting between the main and auxiliary stages. Nevertheless, the presence of many degrees of freedom, e.g., input amplitude split and phase displacement as well as biasing for multiple stages, often involves inefficient trial-and-error procedures to reach a suitable PA performance. This article presents automated parameter setting based on coordinate descent or Bayesian optimizations, demonstrating an improvement in the performance in terms of RF output power and power-added efficiency (PAE) in the presence of broadband-modulated signals, yet maintaining suitable linear behavior for, e.g., communications applications.

The high-order fully actuated system (HOFAS) approach has recently been proposed, aiming at establishing a unified architecture for control of general nonlinear systems. Its core idea is to firstly obtain a HOFAS model for a dynamical system, and then to cancel the nonlinearity using the full-actuation property. Based on this, the control problem of both linear and many types of nonlinear systems is finally turned into a specific eigenstructure assignment problem of a particular matrix pair. Because of this, the specific eigenstructure assignment problem is considered as the fundamental problem of the HOFAS approach, and is investigated in detail in this paper. A general parametric solution is established in an iterative form with all the degrees of freedom provided, and special solutions for some commonly used cases are also given. These form a database for various design problems and provide some ready-to-use results. Finally, illustrative examples demonstrate the usage of the database.

Firm participation in open source software (OSS) development is a noteworthy phenomenon and includes two types of firm-participating OSS projects: community founded (developed from an open project) and spinout (spun out from an information technology firm’s internal project). OSS project leaders implement quality controls to improve the quality of developed products. They may not be aware that their implementation of quality controls produces a side effect—quality controls signal unobservable project quality to volunteers and promote volunteers’ continued participation intentions (VCPI). We focus on two quality controls— accreditation and code acceptance , which, respectively, map to the input and output quality of an OSS project—and compare their respective effects on VCPI in community-founded and spinout projects. We propose that accreditation and code acceptance influence VCPI by signaling unobservable input and output quality to volunteers. As we focus on continued participation, we theorize as to how volunteers’ tenure in OSS projects moderates the relationships between the signaling effects of input and output quality controls and VCPI. Furthermore, we theorize as to how the OSS project type moderates the effects of quality controls on VCPI. We surveyed 304 volunteers from 40 OSS projects and constructed a two-level model of project and developer factors to explain VCPI. Our findings indicate that both accreditation and code acceptance enhance VCPI. The signaling effects on VCPI associated with accreditation decline with volunteer tenure, but those associated with code acceptance do not. Accreditation and code acceptance influence VCPI, with community-founded projects exhibiting weaker direct positive effects and spinout projects exhibiting stronger direct positive effects. We discuss the theoretical and practical implications of these findings.

This paper investigates the optimal sliding mode control (SMC) of modular multilevel converters (MMCs) by considering control input constraints. Conventional SMC methods for MMCs typically overlook the system’s constraints. To address this, an optimal SMC approach that incorporates control input constraints through quadratic programming (QP) is proposed. The control design problem is formulated in a constrained optimization framework and solved using the infeasible active-set (IAS) method to efficiently achieve the optimal solution. By applying optimal SMC, this work contributes to the advancement of SMC strategies for MMCs by addressing both constraints and performance optimization in a systematic way. This is particularly relevant for real-world applications, where controllers may temporarily exceed their limits before enforcing constraints. To validate the proposed approach, a comparative analysis with conventional SMC methods is performed, and simulation results confirm that the proposed approach provides improved performance.