AIMC Topic: Nonlinear Dynamics

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Secure predictor-based neural dynamic surface control of nonlinear cyber-physical systems against sensor and actuator attacks.

ISA transactions
This paper addresses a secure predictor-based neural dynamic surface control (SPNDSC) issue for a cyber-physical system in a nontriangular form suffering from both sensor and actuator deception attacks. To avoid the algebraic loop problem, only parti...

Neural Network Modeling and Dynamic Analysis of Different Types of Engine Mounts for Internal Combustion Engines.

Sensors (Basel, Switzerland)
This paper presents the results of studies on reducing the amount of vibrations in different frequency ranges generated by a combustion engine through the use of different types of engine mounts. Three different types of engine supports are experimen...

Adaptive Fuzzy Control for Nontriangular Stochastic High-Order Nonlinear Systems Subject to Asymmetric Output Constraints.

IEEE transactions on cybernetics
In this article, an adaptive fuzzy control design strategy is presented for p -norm nontriangular stochastic high-order nonlinear systems with asymmetric output constraints and unknown nonlinearities. To prevent the violation of the asymmetric output...

Asynchronous learning for actor-critic neural networks and synchronous triggering for multiplayer system.

ISA transactions
In this paper, based on actor-critic neural network structure and reinforcement learning scheme, a novel asynchronous learning algorithm with event communication is developed, so as to solve Nash equilibrium of multiplayer nonzero-sum differential ga...

Design of a Regional Economic Forecasting Model Using Optimal Nonlinear Support Vector Machines.

Computational intelligence and neuroscience
Forecasting regional economic activity is a progressively significant element of regional economic research. Regional economic prediction can directly assist local, national, and subnational policymakers. Regional economic activity forecast can be em...

Granger causality test with nonlinear neural-network-based methods: Python package and simulation study.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Causality defined by Granger in 1969 is a widely used concept, particularly in neuroscience and economics. As there is an increasing interest in nonlinear causality research, a Python package with a neural-network-based caus...

Discrete-time practical robotic control for human-robot interaction with state constraint and sensorless force estimation.

ISA transactions
Employing a continuous-time control algorithm to control the practical system based on discrete-time digital computer will lead to the cost of performance degeneration. To address this issue, this paper proposes a discrete-time barrier Lyapunov funct...

Adaptive Finite-Time Containment Control of Uncertain Multiple Manipulator Systems.

IEEE transactions on cybernetics
This article is concerned with the containment control of multiple manipulators with uncertain parameters. A novel distributed adaptive backstepping strategy is given in the finite-time control framework. The finite-time command filters (FTCFs) used ...

Dissipativity-Based Disturbance Attenuation Control for T-S Fuzzy Markov Jumping Systems With Nonlinear Multisource Uncertainties and Partly Unknown Transition Probabilities.

IEEE transactions on cybernetics
This article is concerned with the dissipativity-based disturbance attenuation control for a class of Takagi-Sugeno (T-S) fuzzy Markov jump systems (FMJSs) suffering from nonlinear multisource disturbances. The considered system possesses nonlinear a...

Self-Learning Robust Control Synthesis and Trajectory Tracking of Uncertain Dynamics.

IEEE transactions on cybernetics
In this article, we investigate the self-learning robust control synthesis and tracking design of general uncertain dynamical systems. Based on the adaptive critic learning, the robust stabilization method is developed with the help of conducting pro...