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 …

Networked Digital Predictive Control For Modular Dc-Dc Converters, Castulo Aaron De La O Pérez

Theses and Dissertations

The concept of power electronics building blocks (PEBB) has driven advancements in highly modularized converter systems with many identical subsystems. PEBBs are distributed subsets of converter systems and thus require communication with a control system for their coordination. For this type of system, the communication latency with hard deterministic deadlines is the driving attribute of communication system requirements. However, inherent communication requirements for PEBB-based converter systems also provide opportunities for coordination of energy flow.

Leveraging developments in Gigabit serial communication channels, a control and communication platform architecture for distributed control schemes based on the 2D-Torus communication network topology was developed …

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.

Performance Improvement Of Induction Motor Drives With Model-Based Predictive Torque Control, Fati̇h Korkmaz

Turkish Journal of Electrical Engineering and Computer Sciences

One of the most important advantages of using modeling and simulation software in design and control engineering is the ability to predict system behavior within specified conditions. This paper presents a novel error vector-based control algorithm that aims to reduce torque ripples predicting flux and torque errors in a conventional vector-controlled induction motor. For this purpose, a new control model has been developed that envisages flux change by applying probabilistic space vectors' torque and flux control. In the proposed predictive control algorithm, flux and torque errors are calculated for each candidate voltage vector. Thus, the optimal output voltage vector that …

Simplified Model Predictive Current Control Of Non-Sinusoidal Low Power Brushlessdc Machines, Alireza Lahooti Eshkevari, Hossein Torkaman

Turkish Journal of Electrical Engineering and Computer Sciences

Several strategies have been proposed to control nonsinusoidal brushless DC machines (BLDCMs). However, high electromagnetic torque ripple and current overshoots occur in commutation times, which are significant problems of those strategies such as for hysteresis current controllers. This paper proposes a model predictive strategy to solve the above issues. It is simple and straightforward. Moreover, it reduces the motor torque ripple significantly and improves the response rate of the control system to the load torque variation in comparison with the conventional technique. The torque varies smoothly, and the performance of the system at commutation time is improved by eliminating the …

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 …

Sensorless Second-Order Switching Surface For A Three-Level Boost Converter, Tarek Messikh, Nasrudin Abd Rahim, Saad Mekhilef

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a sensorless second-order switching surface to control a three-level boost converter (TLBC). A predictive current method is proposed to reduce the number of sensors in the normal second-order switching surface method. Based on a developed model of the TLBC, the current is estimated and a switching surface is formulated in the state-energy plane. Simulation and hardware tests are carried out to verify the viability and the effectiveness of the proposed control technique. Results obtained show a good performance of the converter in term of DC-bus balancing and fast dynamic response under sudden load change.

Supervised Learning-Based Explicit Nonlinear Model Predictive Control And Unknown Input Estimation In Biomedical Systems, Ankush Chakrabarty

Open Access Dissertations

Application of nonlinear control theory to biomedical systems involves tackling some unique and challenging problems. The mathematical models that describe biomedical systems are typically large and nonlinear. In addition, biological systems exhibit dynamics which are not reflected in the model (so-called 'un-modeled dynamics') and hard constraints on the states and control actions, which exacerbate the difficulties in designing model-based controllers or observers.

This thesis investigates the design of scalable fast explicit nonlinear model predictive controllers (ENMPCs). The design involves (i) the estimation of a feasible region using Lyapunov stability methods and support vector machines; and (ii) within the estimated feasible …

Experimental Validation Of Minimum Cost Function-Based Model Predictive Converter Control With Efficient Reference Tracking

Faculty of Engineering University of Malaya

This study proposes a robust and powerful finite control set-model predictive control (MPC) algorithm to control the load current with lower total harmonic distortion and efficient reference tracking. In this control, the cost functions are determined for all the possible switching states of the converter and a switching state is selected corresponding to the minimum cost function for actuating the converter in the next sampling time period. To justify the performance of the proposed MPC scheme, a comprehensive study with the carrier-based pulse-width modulation, hysteresis current control and proposed minimum cost function-based MPC of the three-phase load current has been …

Imposed Weighting Factor Optimization Method For Torque Ripple Reduction Of Im Fed By Indirect Matrix Converter With Predictive Control Algorithm

Faculty of Engineering University of Malaya

This paper proposes a weighting factor optimization method in predictive control algorithm for torque ripple reduction in an induction motor fed by an indirect matrix converter (IMC). In this paper, the torque ripple behavior is analyzed to validate the proposed weighting factor optimization method in the predictive control platform and shows the effectiveness of the system. Therefore, an optimization method is adopted here to calculate the optimum weighting factor corresponds to minimum torque ripple and is compared with the results of conventional weighting factor based predictive control algorithm. The predictive control algorithm selects the optimum switching state that minimizes a …

Predictive Control Of A Constrained Pressure And Level System, Erkan Kaplanoğlu, Taner Arsan, Hüseyi̇n Selçuk Varol

Turkish Journal of Electrical Engineering and Computer Sciences

The focus of this paper is the implementation of a constrained predictive control algorithm implemented in Multi-Parametric Toolbox (MPT), which is a free MATLAB toolbox for design, analysis, and implementation of controllers for constrained linear, nonlinear, and hybrid systems. In general, MPT is used for modeling systems offline. The novelty of this study is that real-time mode MPT is used in process control. We also combined the Model Predictive Control Toolbox with MPT. This novel controller is considered a real-time controller of level-pressure systems. In this study, a special type of model predictive control algorithm, the constrained continuous-time generalized control, …

Terminal Guidance Of Autonomous Parafoils In High Wind-To-Airspeed Ratios, Nathan Slegers, O A. Yakimenko

Faculty Publications - Biomedical, Mechanical, and Civil Engineering

Autonomous precision placement of parafoils is challenging because of their limited control authority and sensitivity to winds. In particular, when wind speed is near the airspeed, guidance is further complicated by the parafoils inability to penetrate the wind. This article specifically addresses the terminal phase and develops an approach for generating optimal trajectories in real-time based on the inverse dynamics in the virtual domain. The method results in efficient solution of a two-point boundary-value problem using only a single optimization parameter allowing the trajectory to be generated at a high rate, mitigating effects of the unknown winds. It is shown …

A Feasibility Study Of Model-Based Natural Ventilation Control In A Midrise Student Dormitory Building, Steven James Gross

Dissertations and Theses

Past research has shown that natural ventilation can be used to satisfy upwards of 98% of the yearly cooling demand when utilized in the appropriate climate zone. Yet widespread implementation of natural ventilation has been limited in practice. This delay in market adoption is mainly due to lack of effective and reliable control. Historically, control of natural ventilation was left to the occupant (i.e. they are responsible for opening and closing their windows) because occupants are more readily satisfied when given control of the indoor environment. This strategy has been shown to be effective during summer months, but can lead …

Creating Insanity In Learning Systems: Addressing Ambiguity Effects Of Predicting Non-Linear Continuous Valued Functions With Reconstructabilty Analysis From Large Categorically Valued Input Data Sets, William D. Eisenhauer

Systems Science Friday Noon Seminar Series

Being told to give two different, and potentially counter, responses to the same stimulus can set up a double bind in humans, leading to a type of insanity. So what how do you deal with it when it comes up quite frequently in modeling through simplification and removal of predictive variables?

In his current dissertation research Ike Eisenhauer is using reconstructability analysis to implement K-System, U-System, and B-System approaches to predict a continuously valued function through discrete categorically valued input variables [e.g. textual data]. One of the key issues is how to address the inability of K-Systems and U-Systems to …

Beyond Biobricks: Synthesizing Synergistic Biochemical Systems From The Bottom-Up, Mark A. Bedau

Systems Science Friday Noon Seminar Series

Engineers who attempt to discover and optimize the behavior of complex biochemical systems face a dauntingly difficult task. This is especially true if the systems are governed by multiple qualitative and quantitative variables that have non-linear response functions and that interact synergistically. The synthetic biology community has responded to this difficulty by promoting the use of "standard biological parts" called "BioBricks", which are supposed to make biology into traditional engineering and enable engineers to "program living organisms in the same way a computer scientists can program a computer". But the BioBricks research program faces daunting hurdles, because the nonlinearity and …

Predictive Control For Dynamic Systems To Track Unknown Input In The Presence Of Time Delay, Yulan Li

Electronic Theses and Dissertations

This study investigated a tracking system to trace unknown signal in the presence oftime delay. A predictive control method is proposed in order to compensate the time delay. Root locus method is applied when designing the controller, parameter setting is carried out through error and trail technique in w-plane. State space equation is derived for the system, with special state chose of tracking error. To analyze the asymptotic stability of the proposed predictive control system, the Lyapunov function is constructed. It is shown that the designed system is asymptotically stable when input signal is rather low frequency signal. In order …

An Evaluation Of Model-Based Predictive Control, Daniel Czarkowski

Theses

This thesis attempts to determine whether advanced control algorithms offer any real benefits to the process industry in terms of optimising single-input single output process units. To establish this, an ideal PID controller, Two Degree of Freedom (2 DOF) PID Controller and the Generalised Predictive Controller (GPC) are compared. A common design philosophy is applied based on optimising performance subject to constraints on robustness. Specifically, three different designs are examined; minimum subject to constraints on the gain and phase margin, minimum lAE subject to constraints on the modulus margin and minimum lAE subject to constraints on the input sensitivity function. …

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. …

Generalized Predictive Control Of Ship Coupling Motions Using Active Flume Tanks, Abdulkarim Mohammed Alotaiwi

Mechanical & Aerospace Engineering Theses & Dissertations

This dissertation uses the Generalized Predictive Control (GPC) approach to design a control system for a ship rolling motion coupled with the sway and yaw using an activated flume tank. GPC is a strategy based on system output prediction over finite horizon known as the prediction horizon. GPC controller is designed from the coefficients of the Autoregressive model with exogenous input (ARX) that are computed directly from input and output data. It computes the future control input based on the cost function with weighted input and output. System identification approach is implemented on the system to find the ARX coefficients …

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 …