A5014744998- Adaptive Control of Nonlinear Systems
- Neural Networks Stability and Synchronization
- Neural Networks and Applications
- Advanced Control Systems Design
- Chaos control and synchronization
- Advanced Algorithms and Applications
- Matrix Theory and Algorithms
- Energy and Environment Impacts
- Cooperative Communication and Network Coding
- Integrated Energy Systems Optimization
- Teleoperation and Haptic Systems
- stochastic dynamics and bifurcation
- Elasticity and Wave Propagation
- Advanced Sensor and Control Systems
- Fish Ecology and Management Studies
- Stability and Control of Uncertain Systems
- Fuzzy Logic and Control Systems
- Cellular Automata and Applications
- Robot Manipulation and Learning
- Adaptive Dynamic Programming Control
- Photovoltaic Systems and Sustainability
- Soft Robotics and Applications
- Advanced Memory and Neural Computing
- Marine Bivalve and Aquaculture Studies
- Distributed Control Multi-Agent Systems
Sichuan University
2021-2024
Tokyo University of Marine Science and Technology
2019
Chongqing Jiaotong University
2018-2019
In this article, we focus on the issue of adaptive fuzzy finite-time tracking control for a class uncertain fractional-order nonlinear systems with external disturbance. A new command filtered implementation scheme is presented backstepping method. approach, analytical computation fractional derivatives stabilizing functions not necessary. Therefore, controller and law are easier to derive implement. Based proposed filter, technique, Lyapunov's direct method, novel designed, which can...
Abstract This article addresses the robust fixed‐time synchronization of fuzzy shunting‐inhibitory cellular neural networks (FSICNNs) with delays by utilizing two different types control strategies. First, a feedback controller is proposed to achieve FSICNNs. Secondly, novel adaptive designed guarantee FSICNNs, automatically adjusting all gains without need for advanced settings. The use differential inequality techniques and Lyapunov function method yields several sufficient conditions...
Abstract This study investigated the observer design schemes for interconnected nonlinear systems with actuator faults, sensor external disturbances, and limited measured resources. A novel effective distributed estimation scheme is presented system to estimate states, lumped simultaneously. To save communication resources improve information utilization, an adaptive event condition designed in channel, triggered values are utilized observer. Especially, handle fault, output separated into...
Abstract This paper is concerned with the finite‐time tracking control problem of fractional‐order nonlinear systems (FONSs) uncertainty and external disturbance. A novel design scheme adaptive neural network controller (ANNFTC) developed by utilizing theory stability dynamic surface (DSC) combined backstepping method. Radial basis function networks (RBF NNs) are employed to estimate unknown function. Furthermore, an auxiliary introduced approximate upper bounds approximation error in RBF...
This work investigates the adaptive neural networks (NNs) control for non-strict feedback fractional-order nonlinear systems (FONSs) while considering presence of external disturbance and uncertainty. To address issue "explosion terms", an controller is devised utilizing command filter, backstepping method Lyapunov stability theory. The NNs can not only ensure closed-loop FONSs but also drive tracking error to converge a neighborhood near origin. Simulation example demonstrates effectiveness...
The Mittag-Leffler stability of a class discrete-time fractional-order neural networks was studied. Based on the discrete fractional calculus theory and network theory, were proposed. By means inequality techniques Laplace transform, through construction appropriate Lyapunov function, sufficient criteria for global obtained. Finally, numerical simulation example verifies validity proposed theory.
This work presents a proposed controller based on generalized linear extended state observer (GLESO) for continuum robots (CR) facing unmatched uncertainties in trajectory tracking. The complex structure of CRs makes accurate modeling difficult, especially when operating unknown environments. Internal and external further impact the control performance, particularly uncertainties. To address this, GLESO is employed to observe compensate Additionally, tailored slide mode (SMC) introduced...
This paper is devoted to addressing the issue of adaptive fuzzy control for single-input single-output (SISO) fractional-order nonlinear systems with uncertainty. In order avoid "explosion terms" caused by solving fractional derivative virtual signal, a new dynamic surface (DSC) method proposed systems. Based on backstepping technique and Lyapunov direct derivatives, stability closed-loop system proved, which can ensure that tracking error converge small region. Finally, simulation example...
In this paper, the global Mittag-Leffler synchronization of discrete-time fractional-order complex-valued neural networks with time delay is investigated. First all, a new lemma for Caputo fractional difference derived in complex field. Then, by constructing appropriate Lyapunov function and designing novel linear feedback controller, LMI-based sufficient criterion provided to ensure proposed networks. A simulation example given show effectiveness control scheme.