Switching PDC control for discrete-time T–S fuzzy system: A membership function ranking approach

In this paper, a new type of switched parallel distributed compensation (PDC) controller is presented, in which a novel switching scheme, namely, membership function ranking (MFR) scheme is proposed. The MFR scheme can be viewed as an improvement and extension of previous results named largest membership function (LMF) scheme concerned with piece-wise quadratic Lyapunov function (PQLF) approach, since it provides a denser subdivision of normalized membership function space and therefore essentially yields less conservative results. Moreover, it shows that MFR scheme covers LMF scheme as a particular case. Based on MFR scheme, a family of _?∞${\mathbf{?}}_{\infty }$ controllers and a switching scheme is designed to ensure the closed-loop system asymptotically stable and has a required _?∞${\mathbf{?}}_{\infty }$ performance. A design example is presented to illustrate the advantages of MFR scheme.     

Event-driven fully distributed optimal coordinated control for Euler–Lagrange multi-agent systems with connectivity preservation

This paper studies the distributed optimal coordinated control problem for Euler–Lagrange multi-agent systems with connectivity preservation. The aim is to force agents to achieve the optimal solution minimizing the sum of the local objective functions while guaranteeing the connectivity of the communication graph. For practical purposes, the gradient vector of the local objective function is allowed to use only at the real-time generalized position instead of at the auxiliary system state. To make the control parameters independent of the global information and guarantee the fully distributed manner of controller, the adaptive control is introduced to update the coupling weights of the relative states among neighbors. Moreover, to reduce the resource for control updates, the event-driven communication is employed for the updates of both the relative states and the gradient of the connectivity-preserving potential function. Based on the Lyapunov analysis framework, it is proved that agents can converge to the optimal solution with connectivity preservation and Zeno behavior is excluded for the two event-triggering conditions. Finally, the effectiveness of the proposed method is verified by a numerical simulation example.     

Input–output finite-time stabilization for MJSs with time-varying delay: An observer-based approach

This paper deals with the input–output finite-time stabilization problem for Markovian jump systems (MJSs) with incompletely known transition rates. An observer-based output feedback controller is constructed to study the input–output finite-time stability (IO-FTS) problem. By using the mode-dependent Lyapunov–krasovskii functional method, a sufficient criterion checking the IO-FTS problem is provided. Then, an observer and a corresponding state feedback controller for the individual subsystem are respectively designed to solve the input–output finite-time stabilization problem for the systems. Finally, a numerical example on the mass-spring system model is investigated to bring out the advantages of the control scheme proposed in this paper.     

Output feedback robust H∞ control for spacecraft rendezvous system subject to input saturation: A gain scheduled approach

In this paper, the problem of output feedback robust H_∞ control for spacecraft rendezvous system with parameter uncertainties, disturbances and input saturation is investigated. Firstly, a full-order state observer is designed to reconstruct the full state information, whose gain matrix can be obtained by solving the linear matrix inequality (LMI). Subsequently, by combining the parametric Riccati equation approach and gain scheduled technique, an observer-based robust output feedback gain scheduled control scheme is proposed, which can make full use of the limited control capacity and improve the control performance by scheduling the control gain parameter increasingly. Rigorous stability analyses are shown that the designed discrete gain scheduled controller has faster convergence performance and better robustness than static gain controller. Finally, the performance and advantage of the proposed gain scheduled control scheme are demonstrated by numerical simulation.     

SmartRolling: A human–machine interface for wheelchair control using EEG and smart sensing techniques

Smart wheelchairs based on brain–computer interface (BCI) have been widely utilized recently to address certain mobility problems for people with disability. In this paper, we present SmartRolling, an intuitive human–machine interaction approach for the direct control of robotic wheelchair that jointly leverages EEG signals and motion sensing techniques. Specifically, SmartRolling offers two wheelchair-actuation modes for users with different physical conditions: (1) head motion only — people who are severely disabled but able to do basic tasks using eyes and head, and (2) head and hands motion — in addition to type 1, people who can use functioning hands/arms for extra tasks. The system issues operation commands by recognizing different EEG patterns elicited by motor execution (ME) tasks including eye blink, jaw clench, and fist open/close, while at the same time estimates users’ steering intentions based on their facing direction by leveraging inertial measurements and computer vision techniques. The experiment results demonstrate that the proposed system is robust and effective to meets the individual’s needs and has great potential to promote better health.     

Tran-Switch: A transfer learning approach for sentence level cross-genre author profiling on code-switched English–RomanUrdu Text

Cross-genre author profiling aims to build generalized models for predicting profile traits of authors that can be helpful across different text genres for computer forensics, marketing, and other applications. The cross-genre author profiling task becomes challenging when dealing with low-resourced languages due to the lack of availability of standard corpora and methods. The task becomes even more challenging when the data is code-switched, which is informal and unstructured. In previous studies, the problem of cross-genre author profiling has been mainly explored for mono-lingual texts in highly resourced languages (English, Spanish, etc.). However, it has not been thoroughly explored for the code-switched text which is widely used for communication over social media. To fulfill this gap, we propose a transfer learning-based solution for the cross-genre author profiling task on code-switched (English–RomanUrdu) text using three widely known genres, Facebook comments/posts, Tweets, and SMS messages. In this article, firstly, we experimented with the traditional machine learning, deep learning and pre-trained transfer learning models (MBERT, XLMRoBERTa, ULMFiT, and XLNET) for the same-genre and cross-genre gender identification task. We then propose a novel Trans-Switch approach that focuses on the code-switching nature of the text and trains on specialized language models. In addition, we developed three RomanUrdu to English translated corpora to study the impact of translation on author profiling tasks. The results show that the proposed Trans-Switch model outperforms the baseline deep learning and pre-trained transfer learning models for cross-genre author profiling task on code-switched text. Further, the experimentation also shows that the translation of RomanUrdu text does not improve results.     

Disturbance observer-based fixed-time leader-following consensus control for multiple Euler–Lagrange systems: A non-singular terminal sliding mode scheme

This paper focuses on the fixed-time leader-following consensus problem for multiple Euler–Lagrange (EL) systems via non-singular terminal sliding mode control under a directed graph. Firstly, for each EL system, a local fixed-time disturbance observer is introduced to estimate the compound disturbance (including uncertain parameters and external disturbances) within a fixed time under the assumption that the disturbance is bounded. Next, a distributed fixed-time observer is designed to estimate the leader’s position and velocity, and the consensus problem is transformed into a local tracking problem by introducing such an observer. On the basis of the two types of observers designed, a novel non-singular terminal sliding surface is proposed to guarantee that the tracking errors on the sliding surface converge to zero within a fixed time. Furthermore, the presented control algorithm also ensures the fixed-time reachability of the sliding surface, while avoiding the singularity problem. Finally, the effectiveness of the proposed observers and control protocol is further verified by a numerical simulation.