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Reinforcement learning-based control for waste biorefining processes under uncertainty
Waste biorefining processes face significant challenges related to the variability of feedstocks. The supply and composition of multiple feedstocks...
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Event-based neural learning for quadrotor control
The design of a simple and adaptive flight controller is a real challenge in aerial robotics. A simple flight controller often generates a poor...
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Neural networks-based iterative learning control consensus for periodically time-varying multi-agent systems
In this paper, the problem of adaptive iterative learning based consensus control for periodically time-varying multi-agent systems is studied, in...
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Q-learning Based Adaptive Optimal Control for Linear Quadratic Tracking Problem
This paper describes a Q-learning based algorithm to design the linear quadratic tracker (LQT) for linear time invariant (LTI) continuous-time...
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A learning-based control pipeline for generic motor skills for quadruped robots
Performing diverse motor skills with a universal controller has been a longstanding challenge for legged robots. While motion imitation-based...
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SAKMR: Industrial control anomaly detection based on semi-supervised hybrid deep learning
With the advent of Industry 4.0, industrial control systems (ICS) are more and more closely connected with the Internet, leading to a rapid increase...
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Dissolved oxygen concentration control in wastewater treatment process based on reinforcement learning
In this article, the dissolved oxygen (DO) concentration control problem in wastewater treatment process (WWTP) is studied. Unlike existing control...
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Optimal Incremental-containment Control of Two-order Swarm System Based on Reinforcement Learning
In this paper, the optimal incremental-containment control of two-order swarm system based on reinforcement learning (RL) is proposed to avoid the...
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Adaptive learning-based optimal tracking control system design and analysis of a disturbed nonlinear hypersonic vehicle model
We propose an adaptive learning-based optimal control scheme for height-velocity control models considering model uncertainties and external...
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A Learning-based Control Framework for Fast and Accurate Manipulation of a Flexible Object
This paper presents a learning-based control framework for fast (< 1.5 s ) and accurate manipulation of a flexible object, i.e., whip targeting. The...
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Estimator-based dynamic learning from neural control of discrete-time strict-feedback systems
The dynamic learning issue from adaptive neural control for a class of discrete-time strict-feedback nonlinear systems is the main topic of this...
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Deep Model-Based Reinforcement Learning for Predictive Control of Robotic Systems with Dense and Sparse Rewards
Sparse rewards and sample efficiency are open areas of research in the field of reinforcement learning. These problems are especially important when...
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Study on force control for robot massage with a model-based reinforcement learning algorithm
When a robot end-effector contacts human skin, it is difficult to adjust the contact force autonomously in an unknown environment. Therefore, a robot...
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4 Learning-based Control
Due to the complexity of the system, it is difficult for us to work out a “complete” analytical model of it. Therefore, in this chapter, we propose...
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Deep reinforcement learning-based drift parking control of automated vehicles
Drift parking usually requires precise control of a vehicle by a professional driver, which can reflect the performance of the vehicle under critical...
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Research on internet financial risk control based on deep learning algorithm
With the rapid development of Internet technology, Internet finance has entered thousands of households, bringing a lot of convenience to people’s...
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Reinforcement Q-learning and Optimal Tracking Control of Unknown Discrete-time Multi-player Systems Based on Game Theory
This paper studies the fully cooperative game tracking control problem (FCGTCP) for a class of discrete-time multi-player linear systems with unknown...
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Bionic Hand Motion Control Method Based on Imitation of Human Hand Movements and Reinforcement Learning
Bionic hands are promising devices for assisting individuals with hand disabilities in rehabilitation robotics. Controlled primarily by bioelectrical...
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Efficient learning control of uncertain nonlinear systems with input constraints: a disturbance observer-based neural network approach
To deal with the effects of the input saturation and time-varying input delay, this article presents a serial-parallel identifier-based composite...
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Exploration-based model learning with self-attention for risk-sensitive robot control
Model-based reinforcement learning for robot control offers the advantages of overcoming concerns on data collection and iterative processes for...
