Robust fractional-order fast terminal sliding mode control with fixed-time reaching law for high-performance nanopositioning

Open Access via the Wiley Agreement ACKNOWLEDGEMENTS This work is supported by the China Scholarship Council under Grant No. 201908410107 and by the National Natural Science Foundation of China under Grant No. 51505133. The authors also thank the anonymous reviewers for their insightful and constructive comments.Peer reviewedPublisher PD

Chaos Suppression of an Electrically Actuated Microresonator Based on Fractional-Order Nonsingular Fast Terminal Sliding Mode Control

This paper focuses on chaos suppression strategy of a microresonator actuated by two symmetrical electrodes. Dynamic behavior of this system under the case where the origin is the only stable equilibrium is investigated first. Numerical simulations reveal that system may exhibit chaotic motion under certain excitation conditions. Then, bifurcation diagrams versus amplitude or frequency of AC excitation are drawn to grasp system dynamics nearby its natural frequency. Results show that the vibration is complex and may exhibit period-doubling bifurcation, chaotic motion, or dynamic pull-in instability. For the suppression of chaos, a novel control algorithm, based on an integer-order nonsingular fast terminal sliding mode and a fractional-order switching law, is proposed. Fractional Lyapunov Stability Theorem is used to guarantee the asymptotic stability of the system. Finally, numerical results with both fractional-order and integer-order control laws show that our proposed control law is effective in controlling chaos with system uncertainties and external disturbances

Sensor Fault Detection and Compensation with Performance Prescription for Robotic Manipulators

This paper focuses on sensor fault detection and compensation for robotic manipulators. The proposed method features a new adaptive observer and a new terminal sliding mode control law established on a second-order integral sliding surface. The method enables sensor fault detection without the need to impose known bounds on fault value and/or its derivative. It also enables fast and fixed-time fault-tolerant control whose performance can be prescribed beforehand by defining funnel bounds on the tracking error. The ultimate boundedness of the estimation errors for the proposed observer and the fixed-time stability of the control system are shown using Lyapunov stability analysis. The effectiveness of the proposed method is verified using numerical simulations on two different robotic manipulators, and the results are compared with existing methods. Our results demonstrate performance gains obtained by the proposed method compared to the existing results

Multi-Machine Power Stabilization Controller (MMPSC) for Power Quality Applications

Abstract Power system stability control is a challenging task in power generation, transmission and distributions based applications and in many fields. Multi-machine power compensation control can achieve system stabilization within a prescribed time in conventional controller. However, limited time control cannot guarantee the system convergence within particular time independent on the initial condition, which makes illegal application into the practical system if the initial condition is unknown in advance. The proposed Multi-Machine Power System Compensation (MMPSC) control overcomes the issues in existing systems and limited time stability controller. Due to this attractive solution, multi-machine power compensation control stability has found applications in uniform exact differentiator design for the multi-agent system. The proposed multi-machine power compensation control reduces damping oscillation and improves the power system stability control. The main objective of proposed controller is to improve the stability of MMPSC limited time system stabilization independent of the initial state and ensure fast convergence both far away from and at a close range of the power monitoring system. This feature can reduce the loss caused by unwanted oscillation and avoid voltage collapse. To overcome the linearity problem of terminal mode control, saturation function is introduced to limit the amplitude of power input. In comparison with the existing results on stability control, the proposed MMPSC applies a simpler method to overcome stability problem and achieves higher efficiency

Fast fixed-time synchronization of T–S fuzzy complex networks

In this paper, fast fixed-time (FDT) synchronization of T–S fuzzy (TSF) complex networks (CNs) is considered. The given control schemes can make the CNs synchronize with the given isolated system more fleetly than the most of existing results. By constructing comparison system and applying new analytical techniques, sufficient conditions are established to derive fast FDT synchronization speedily. In order to give some comparisons, FDT synchronization of the considered CNs is also presented by designing FDT fuzzy controller. Numerical examples are given to illustrate our new results

Fixed-time control of delayed neural networks with impulsive perturbations

This paper is concerned with the fixed-time stability of delayed neural networks with impulsive perturbations. By means of inequality analysis technique and Lyapunov function method, some novel fixed-time stability criteria for the addressed neural networks are derived in terms of linear matrix inequalities (LMIs). The settling time can be estimated without depending on any initial conditions but only on the designed controllers. In addition, two different controllers are designed for the impulsive delayed neural networks. Moreover, each controller involves three parts, in which each part has different role in the stabilization of the addressed neural networks. Finally, two numerical examples are provided to illustrate the effectiveness of the theoretical analysis

Wind Estimation and Control of Unmanned Aerial Vehicles with Application to Forest Fire Surveillance

In recent years, there has been an increasing interest in the application of unmanned aerial vehicles in forest fire monitoring and detection systems. Armed with unmanned aerial vehicles (UAVs), firefighters on the ground can get a bird's-eye view of the terrain, respond to forest fires quickly, distribute resources, and ultimately save lives and properties. In practice, wind behaviors have significant impacts on both the performance of UAV and forest fire situations. However, current wind measurement and estimation relies on data gathered from ground weather stations that are often located several kilometers away from the forest fire regions. As a result, it is challenging to maintain the performance and assess the forest fire situations properly with the obtained wind information. This thesis investigates the problems of the wind estimation and control of unmanned aerial vehicles with application to forest fire surveillance. To develop UAVs as remote wind sensing platforms, a two-stage particle filter-based approach is proposed to estimate winds from quadrotor motion. Based on the estimated wind information, an active wind rejection control strategy is designed to maintain the performance of a quadrotor UAV in the presence of unknown winds. Then, the active wind rejection control strategy is developed for the formation control of multiple UAVs to ensure their cooperative tracking capability. Finally, based on the wind data and fire observations collected by UAVs, a forest fire monitoring scheme is designed to accurately estimate the situation of wind-affected forest fires