Simultaneous Estimation of Digit Tip Forces and Hand Postures in a Simulated Real-Life Condition With High-Density Electromyography and Deep Learning.

In myoelectric control, continuous estimation of multiple degrees of freedom has an important role. Most studies have focused on estimating discrete postures or forces of the human hand but for a practical prosthetic system, both should be considered. In daily life activities, hand postures vary for grasping different objects and the amount of force exerted on each fingertip depends on the shape and weight of the object.

Reduced order state estimation for a class of impulsive switched systems with unknown inputs.

This paper introduces a robust method for estimating states and switching signals in impulsive switched systems with unknown inputs. It uses a reduced-order estimator to handle inaccessible states and an output derivative-based method to address the effects of unknown inputs, even though this adds some impulsive effects. The method is divided into two main steps: first, dedicated estimators determine the switching signal and identify the active subsystem; then, state estimation is carried out.

A new integrated fault detection and control scheme of islanded DC microgrids: A resilient approach.

This paper presents a new resilient integrated fault detection and control module for a DC microgrid operating in islanded mode. The proposed design is unique in its ability to simultaneously improve microgrid reliability and mitigate variations through a multi-objective approach that considers both control and diagnosis objectives in the form of Linear Matrix Inequalities through a presented algorithm. The module is designed by setting out desired performance indices to ensure system stability, mitigate disturbances and uncertainties, and detect faults while controlling the DC-link voltage.

Adaptive super-twisting control for leader-following consensus of second-order multi-agent systems based on time-varying gains.

In this paper, robust distributed consensus control is designed based on adaptive time-varying gains for a class of nonlinear multi-agent systems (MAS) in the presence of uncertain parameters and external disturbances with unknown upper bounds. Due to various conditions and constraints, different dynamical models for the agents can be considered in practice. On the basis of a continuous homogeneous consensus method which has been proposed for the nominal nonlinear MAS, the discontinuous and continuous adaptive integral sliding mode control strategies are particularly designed and extended to accomplish exact and precise consensus for non-identical MASs influenced by imposed perturbations.

Current sharing and voltage regulation of parallel DC-DC buck converters: Switching control approach.

In this paper, a new framework for distributed switching control of parallel DC-DC buck converters is investigated, which represents voltage regulation and current sharing as two decoupled control design problems. The problem is described as a cascaded switched affine system with the new variables output voltage, total current, and current difference of the load, and by employing distributed min-projection switching technique, switching control signals are provided to achieve both voltage regulation and current sharing control objectives. Stability analysis based on relay control is carried out to guarantee the asymptotic stability of the error signals.

Fuzzy-SIRD model: Forecasting COVID-19 death tolls considering governments intervention.

Modeling the trend of contagious diseases has particular importance for managing them and reducing the side effects on society. In this regard, researchers have proposed compartmental models for modeling the spread of diseases. However, these models suffer from a lack of adaptability to variations of parameters over time.

Adaptive backstepping quantized control for a class of unknown nonlinear systems.

In this paper, the stability problem for a class of nonlinear systems in the form of strict-feedback with applying input quantization has been addressed. By considering a sector-bounded hysteresis quantizer, signal quantization has been achieved. The employed quantizer can reduce the potential chattering which can occur in some approaches.

Exponential stability of bilateral sampled-data teleoperation systems using multirate approach.

This paper develops the stability analysis for linear bilateral teleoperation systems exposed to communication constraints and multirate samplers. Dynamics of the master and slave robots are assumed to be continuous-time with discrete-time controllers. The proposed multirate design guarantees the exponential stability of the teleoperation system over a communication networks.

Interconnection and damping assignment control based on modified actor-critic algorithm with wavelet function approximation.

Passivity-based control (PBC) is model-based, and as a result, it is affected by uncertainties. Besides, for some PBC designs, partial differential equations (PDEs) should be solved in order to obtain the parameters of the controller. Actor-critic (AC) algorithm has been used to regulate PBC parameters instantaneously and solve PDEs online.

Adaptive synchronization of chaotic systems with hysteresis quantizer input.

This paper proposes two new designing methods of adaptive controllers in order to synchronize uncertain nonlinear chaotic systems with input quantization. The hysteresis quantizer, which is a class of sector-bounded quantizers, has been used to quantize the control signal. This can avoid the possible chattering caused by some conventional controllers.

EEG Artifacts Handling in a Real Practical Brain-Computer Interface Controlled Vehicle.

One of the main issues restricting the practical efficiency of brain-computer interface (BCI) systems is the inevitable occurrence of physiological artifacts during electroencephalography (EEG) recordings. The effects of the artifacts are, however, mostly discarded in practical BCI systems, due to the time-consuming and complicated computational processes. This paper presents the influences of the artifacts and the efficiency of reducing these influences in a practical BCI.

Synchronization of different fractional order chaotic systems with time-varying parameter and orders.

In this paper, synchronization of time-varying fractional order chaotic systems, is introduced. Parameters of system play an important role in chaotic systems. A time-varying parameter is selected for chaotic systems, also orders of systems are considered as time-varying orders.

Indirect predictive type-2 fuzzy neural network controller for a class of nonlinear input - delay systems.

In this paper a new indirect type-2 fuzzy neural network predictive (T2FNNP) controller has been proposed for a class of nonlinear systems with input-delay in presence of unknown disturbance and uncertainties. In this method, the predictor has been utilized to estimate the future state variables of the controlled system to compensate for the time-varying delay. The T2FNN is used to estimate some unknown nonlinear functions to construct the controller.