Engineering Commons^™

Robust Predictive Control Of Nonplanar Fully-Actuated Uavs, Yun Ma, Yuan Wang, Meng Li, Peng Wang, Yanling Tang

Journal of System Simulation

Abstract: Targeting the problem that nonplanar fully-actuated unmanned aerial vehicles (UAVs) are susceptible to external winds and unmodeled dynamics, the predictive control system with good robustness is designed. A nonlinear motion model with six degrees of freedom is established through the Newton-Euler approach. A linear extended state observer is designed to estimate the state variables by transforming the system affected by matched and unmatched disturbances into an equivalent system only affected by the matched disturbances. A predictive controller is designed for the equivalent system to reduce the output oscillation and input surging and a disturbance compensator is also designed to …

Reinforcement-Learning-Based Adaptive Tracking Control For A Space Continuum Robot Based On Reinforcement Learning, Da Jiang, Zhiqin Cai, Zhongzhen Liu, Haijun Peng, Zhigang Wu

Journal of System Simulation

Abstract: Aiming at the tracking control for three-arm space continuum robot in space active debris removal manipulation, an adaptive sliding mode control algorithm based on deep reinforcement learning is proposed. Through BP network, a data-driven dynamic model is developed as the predictive model to guide the reinforcement learning to adjust the sliding mode controller's parameters online, and finally realize a real-time tracking control. Simulation results show that the proposed data-driven predictive model can accurately predict the robot's dynamic characteristics with the relative error within ±1% to random trajectories. Compared with the fixed-parameter sliding mode controller, the proposed adaptive controller …

Neuro-Fuzzy Modeling For Predictive Control Systems With Complex Technological Processes And Production, Yusupbekov Nodirbek, Shukhrat Gulyamov, Malika Doshchanova

Chemical Technology, Control and Management

The paper implements a modification of a fuzzy neural network, which is suitable for predictive control purposes. Adaptation of a multidimensional programmable controller based on a neural algorithm for the back propagation of forecasting errors is proposed, as well as neural parametric identification of a fuzzy mathematical model of complex technological processes and production based on experimental data and expert estimates.

Data Driven Pre Tuning Adaptive Subspace Model Predictive Control, Han Pu, Liu Miao, Jia Hao

Journal of System Simulation

Abstract: The problem of predictive control is investigated for power plant superheated steam temperature system with the characteristics of large delay, large inertia and time-varying. The data driven pre tuning adaptive subspace model predictive control (PTA-MPC) method, which combines the advantages of subspace identification and state space predictive control, is proposed. The state space models of multiple conditions are obtained by subspace identification with the input signal in persistent excitation. The predictive control law is derived with the state space models, and the controller parameters are optimized by using particle swarm optimization (PSO) algorithm. Based on the least square parameter …

Predictive Congestion Control Mac Protocol For Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Available congestion control schemes, for example transport control protocol (TCP), when applied to wireless networks results in a large number of packet drops, unfairness with a significant amount of wasted energy due to retransmissions. To fully utilize the hop by hop feedback information, a suite of novel, decentralized, predictive congestion control schemes are proposed for wireless sensor networks in concert with distributed power control (DPC). Besides providing energy efficient solution, embedded channel estimator in DPC predicts the channel quality. By using the channel quality and node queue utilizations, the onset of network congestion is predicted and congestion control is initiated. …

Setpoint Tracking Predictive Control In Chemical Processes Based On System Identification, Sinchai Chinvorarat

Mechanical & Aerospace Engineering Theses & Dissertations

A Kraft recovery boiler in a pulp-paper mill provides a means for recovery of the heat energy in spent liquor and recovery of inorganic chemicals while controlling emissions. These processes are carried out in a combined chemical recovery unit and steam boiler that is fired with concentrated black liquor and which produces molten smelt. Since the recovery boiler is considered to be an essential part of the pulp-paper mill in terms of energy resources, the performance of the recovery boiler has to be controlled to achieve the highest efficiency under unexpected disturbances.

This dissertation presents a new approach for combining …