4.7 Article

Analytical Design of Optimal Model Predictive Control and Its Application in Small-Scale Helicopters

Related references

Note: Only part of the references are listed.
Article Engineering, Electrical & Electronic

A Practical Feeder Planning Model for Urban Distribution System

Mingqiang Wang et al.

Summary: There is a significant gap between academic research and practical application in power distribution system planning (PDSP). Existing PDSP models in academic research mainly focus on cost as the objective function and have constraints such as power flow equality, voltage limits, and capacity limits. However, these models are rarely used in real distribution system companies. This paper proposes a new feeder planning model for urban distribution networks, considering practical requirements such as load moment, block loads, street layout, network configuration, and the crossing requirement of feeders. The model is solved using mixed integer linear programming and is demonstrated on test and real distribution systems.

IEEE TRANSACTIONS ON POWER SYSTEMS (2023)

Article Engineering, Marine

Improved LVS guidance and path-following control for unmanned sailboat robot with the minimum triggered setting

Guoqing Zhang et al.

Summary: This paper presents a dynamic event-triggered control algorithm for the unmanned sailboat robot (USR) to carry out the waypoints-based path-following mission. The proposed scheme consists of the guidance module and control one. For the guidance module, the improved logic virtual ship (LVS) guidance law is proposed to plan the reference route for the USR considering the marine environment with time-varying wind direction. As for the control part, the dynamic event-triggered control is proposed by setting tuning threshold parameter, which is advantageous in decreasing the resource waste and channel occupancy compared with the existing event-triggered control with a static threshold parameter.

OCEAN ENGINEERING (2023)

Article Automation & Control Systems

Adaptive Neural Self-Triggered Bipartite Fault-Tolerant Control for Nonlinear MASs With Dead-Zone Constraints

Fabin Cheng et al.

Summary: An adaptive neural bipartite tracking control approach is proposed for nonlinear multi-agent systems in this article. The paper considers a cooperative-competitive relationship in multi-agent systems and designs a distributed self-triggered communication strategy to improve system efficiency. The designed controller can compensate for actuator failure and nonlinearity, increasing system fault-tolerance.

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING (2023)

Article Biochemistry & Molecular Biology

webTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study

Chen Cao et al.

Summary: webTWAS is a new resource that combines comprehensive disease GWAS datasets with information on potential causal genes, allowing researchers to explore gene-disease associations. With data from 1298 high-quality GWAS summary statistics, a total of 235,064 gene-disease associations can be accessed, and custom TWAS analyses can be run on a user-friendly web server.

NUCLEIC ACIDS RESEARCH (2022)

Article Automation & Control Systems

Chaos control of small-scale UAV helicopter based on high order differential feedback controller

Xitong Guo et al.

Summary: The small-scale UAV helicopter has a complex structure and can be stabilized in chaotic oscillations using different controllers, with the HODFC showing the best control performance.

INTERNATIONAL JOURNAL OF CONTROL (2022)

Article Engineering, Marine

Robust Adaptive Neural Cooperative Control for the USV-UAV Based on the LVS-LVA Guidance Principle

Jiqiang Li et al.

Summary: A logic virtual ship-logic virtual aircraft (LVS-LVA) guidance principle is developed to generate reference heading signals for the cooperative path-following control of an underactuated surface vessel (USV) and an unmanned aerial vehicle (UAV). A robust adaptive neural cooperative control algorithm is designed using dynamic surface control, radial basic function neural networks, and event-triggered technique. The proposed algorithm achieves concise form, low transmission burden, and robustness for the control of the USV-UAV system.

JOURNAL OF MARINE SCIENCE AND ENGINEERING (2022)

Article Energy & Fuels

Modeling the Price of Emergency Power Transmission Lines in the Reserve Market Due to the Influence of Renewable Energies

Hamid Iranmehr et al.

Summary: This paper focuses on the pricing of emergency power transmission lines in reserve markets. A method is proposed to calculate the reference price for transmission line owners when bidding for prices exceeding the nominal capacity. The study finds that the use of renewable energy reduces energy costs, but uncertainties increase the costs of reserve markets.

FRONTIERS IN ENERGY RESEARCH (2022)

Article Biochemical Research Methods

Distance-based Support Vector Machine to Predict DNA N6-methyladenine Modification

Haoyu Zhang et al.

Summary: This study presents a novel model based on sequence distance matrix and support vector machine (SVM) for predicting DNA 6mA modification. The model achieved high accuracy rates and correlation coefficients on rice and mouse data, showing significant advantages over traditional machine learning methods.

CURRENT BIOINFORMATICS (2022)

Article Automation & Control Systems

Command filter-based adaptive neural finite-time control for stochastic nonlinear systems with time-varying full-state constraints and asymmetric input saturation

Yulin Li et al.

Summary: This article proposes an adaptive neural finite-time control strategy for stochastic nonlinear systems, which combines neural network approximation and backstepping technique, constructs a time-varying barrier Lyapunov function, and solves the difficulty arising from saturation nonlinearity. With the proposed control strategy, it is guaranteed that system signals are bounded, the reference signal is tracked within a finite time, and system states do not violate constraints.

INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE (2022)

Article Automation & Control Systems

Trajectory tracking of redundantly actuated mobile robot by MPC velocity control under steering strategy constraint

Tao Ding et al.

Summary: This paper focuses on the control problem of four-wheel independent-steering redundantly-actuated omnidirectional mobile robot (FIR-OMR) and proposes an optimal velocity model predictive control method under steering strategy constraint. The method combines pose correction by local micro error for independent wheel angle feedback control. Simulations and experiments are conducted to validate the feasibility and superiority of the proposed method.

MECHATRONICS (2022)

Article Green & Sustainable Science & Technology

Optimal Control of an Energy-Storage System in a Microgrid for Reducing Wind-Power Fluctuations

Rahmat Aazami et al.

Summary: This paper investigates the development of microgrids and energy-storage systems, focusing on wind power and photovoltaic systems, and proposes a control method to optimize the capacity of energy-storage devices in order to reduce power fluctuations in the microgrid.

SUSTAINABILITY (2022)

Article Mathematics

A New Intelligent Dynamic Control Method for a Class of Stochastic Nonlinear Systems

Haifeng Huang et al.

Summary: This paper presents a new method for comprehensive stabilization and control system design for stochastic nonlinear systems using a type-3 fuzzy neural network to estimate parameters. Simulation results show that the proposed method has a good performance and can be applied to systems in this class.

MATHEMATICS (2022)

Article Computer Science, Information Systems

Robust Control Strategies for Microgrids: A Review

Fazel Mohammadi et al.

Summary: This article provides a comprehensive review of robust control methods for microgrids, including AC, DC, and hybrid microgrids with various topologies and connections to conventional power systems. It discusses control objectives and methods, as well as research gaps related to scalability, robustness assessment, and evaluation approach in this area. Recommendations for future research to enhance the effectiveness of robust controllers for microgrids are also discussed.

IEEE SYSTEMS JOURNAL (2022)

Article Automation & Control Systems

Adaptive tracking control for nonlinear system in pure-feedback form with prescribed performance and unknown hysteresis

Y. CHANG et al.

Summary: This work investigates the finite-time tracking control issue for a class of nonlinear pure-feedback system with prescribed performance and unknown hysteresis. The Nussbaum function and auxiliary virtual control function are used to solve the Bouc-Wen hysteresis with unknown parameters and direction conditions. A finite-time performance function is applied to limit the tracking error within a pre-given boundary in finite time. An adaptive tracking control scheme is designed using backstepping technique to ensure bounded closed-loop signals and convergence of the tracking error to a pro-given boundary. A simulation example is provided to demonstrate the effectiveness of the proposed control scheme.

IMA JOURNAL OF MATHEMATICAL CONTROL AND INFORMATION (2022)

Article Automation & Control Systems

Observer-based adaptive fuzzy hierarchical sliding mode control of uncertain under-actuated switched nonlinear systems with input quantization

Haoyan Zhang et al.

Summary: In this article, an observer-based adaptive fuzzy hierarchical sliding mode control scheme is proposed for uncertain under-actuated switched nonlinear systems with quantized input signals. The problems of quantized input signals, external disturbances, unmeasured system states, and unknown nonlinear functions are considered. The proposed control scheme effectively avoids chattering phenomena and utilizes fuzzy logic systems and a switched fuzzy state observer for approximation and estimation. Based on Lyapunov stability theory, the scheme ensures boundedness of all signals and good tracking performance. A numerical simulation example is provided to verify its effectiveness.

INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL (2022)

Article Engineering, Electrical & Electronic

A hybrid approach for fault location in power distributed networks: Impedance-based and machine learning technique

Jafar Tavoosi et al.

Summary: This paper proposes a new fault location method using impedance method and deep neural network. The method is able to accurately determine the fault location in less than 6 seconds with a 99% accuracy rate. The validity of the proposed method is confirmed through simulations.

ELECTRIC POWER SYSTEMS RESEARCH (2022)

Article Automation & Control Systems

Linear Tracking MPC for Nonlinear Systems-Part II: The Data-Driven Case

Julian Berberich et al.

Summary: In this article, a novel data-driven model predictive control (MPC) approach is presented for controlling unknown nonlinear systems using measured input-output data with closed-loop stability guarantees. The proposed scheme utilizes the data-driven system parameterization provided by the fundamental lemma of Willems et al. By updating the data with new input-output measurements online and exploiting local linear approximations of the underlying system, the MPC scheme ensures that the closed loop converges to the optimal reachable equilibrium while satisfying input constraints. The study also extends the fundamental lemma to affine systems and derives robustness bounds for the open-loop optimal control problem under noisy data, which can be applied to other data-driven MPC schemes.

IEEE TRANSACTIONS ON AUTOMATIC CONTROL (2022)

Article Automation & Control Systems

Adaptive command filtered control for switched multi-input multi-output nonlinear systems with hysteresis inputs

Yuanqing Wang et al.

Summary: This article presents an adaptive command filtered control scheme for a class of multiple-input multiple-output switched nonlinear systems with backlash-like hysteresis. By using command filter technique and error compensation mechanism, the proposed controller overcomes the complexity issue and design difficulty caused by system nonlinearity. Simulation results demonstrate the effectiveness of the scheme in ensuring system outputs track desired trajectories while keeping all signals bounded.

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING (2022)

Article Green & Sustainable Science & Technology

Sustainable building climate control with renewable energy sources using nonlinear model predictive control

Wei-Han Chen et al.

Summary: Sustainable energy sources and the use of model predictive control method are promising solutions for reducing energy consumption and carbon footprint in the building sector. This study develops a nonlinear model predictive control framework for building climate control with renewable energy systems, and simulation results demonstrate the effectiveness of the framework in minimizing electricity costs and improving sustainability.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2022)

Article Green & Sustainable Science & Technology

A New Model Predictive Control Method for Buck-Boost Inverter-Based Photovoltaic Systems

Saeed Danyali et al.

Summary: This study proposes a system composed of a photovoltaic system and a DC-DC boost converter with a buck-boost inverter. A multi-error method based on model predictive control (MPC) is used to control the inverter, while incremental conductivity and predictive control methods are employed to track the maximum power of the photovoltaic system. By reducing the total harmonic distortion (THD) and achieving fast voltage adjustment, this control method demonstrates its advantage in accurately following reference signals.

SUSTAINABILITY (2022)

Article Computer Science, Information Systems

Minimal-Approximation-Based Adaptive Event-Triggered Control of Switched Nonlinear Systems with Unknown Control Direction

Yumeng Cao et al.

Summary: This paper investigates an adaptive neural network event-triggered tracking problem for uncertain switched nonlinear systems. A triggering mechanism based on tracking error and minimal approximation technology are introduced to reduce complexity in controller design. Simulation results validate the effectiveness of the proposed strategy in saving communication resources.

ELECTRONICS (2022)

Article Mathematics

Machine-Learning-Based Improved Smith Predictive Control for MIMO Processes

Xinlan Guo et al.

Summary: This paper presents a new method based on Smith's predictive method and a type-2 fuzzy system to control the delay problem in dynamically coupled multi-input/multi-output systems. By using computational intelligence to update the control system parameters and adapt to system changes, the best performance is achieved.

MATHEMATICS (2022)

Article Mathematics

An Improvement of Model Predictive for Aircraft Longitudinal Flight Control Based on Intelligent Technique

Mohamed El-Sayed M. Essa et al.

Summary: This paper presents a new intelligent tuning method for model predictive control (MPC) in aircraft longitudinal flight using a bat-inspired algorithm (BIA). The BIA algorithm is adopted to overcome the challenges of tuning MPC parameters and achieve better system performance compared to conventional methods. The proposed method considers the dynamics and constraints of the aircraft, and utilizes various objective functions to find the best MPC parameters. The results show that the BIA-based MPC outperforms the NARMA-L2 and traditional PI controllers in terms of cross-correlation criteria, ITAE, system overshoot, response settling time, and system robustness.

MATHEMATICS (2022)

Article Mathematics

A Numerical Algorithm for Self-Learning Model Predictive Control in Servo Systems

Hengzhan Yang et al.

Summary: This paper focuses on stochastic systems with unknown parameters, proposing a model predictive control strategy with machine learning characteristics to optimize control system performance through parameter estimation and uncertainty reduction.

MATHEMATICS (2022)

Article Mathematics, Applied

Adaptive fixed-time hierarchical sliding mode control for switched under-actuated systems with dead-zone constraints via event-triggered strategy

Shanlin Liu et al.

Summary: This article investigates the event-triggered-based adaptive fixed-time control problem for switched under-actuated nonlinear systems subject to dead-zone constraints. An efficient control method combining hierarchical sliding mode technique and event-triggered mechanism is proposed to improve the utilization of communication resources, robustness, and response rate of the system. A new fixed-time stability criterion is developed to ensure the designed controller can achieve fixed-time stability and independently control the settling time regardless of initial conditions. The singularity problem of the designed controller is successfully solved using a projection algorithm. The effectiveness of the proposed method is demonstrated through rigorous theoretical derivations and simulation results.

APPLIED MATHEMATICS AND COMPUTATION (2022)

Article Automation & Control Systems

A novel event-triggered strategy for networked switched control systems

Hui Gao et al.

Summary: This paper proposes a novel event-triggered method and discusses finite-time extended dissipative analysis of closed-loop networked switched systems. The controller gains and event-triggered parameters are obtained by solving LMIs. Numerical examples are provided to demonstrate the effectiveness of the proposed method.

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS (2021)

Article Energy & Fuels

Photovoltaic power forecast based on satellite images considering effects of solar position

Zhiyuan Si et al.

Summary: This paper proposes a novel method based on satellite images to accurately forecast photovoltaic power by predicting cloud movement and dynamically selecting cloud regions. By utilizing the XGBoost algorithm and considering multiple factors, the accuracy of the forecast can be improved, as demonstrated through testing the effectiveness of the method compared to other benchmarks.

APPLIED ENERGY (2021)

Article Green & Sustainable Science & Technology

Confidence Interval Based Distributionally Robust Real-Time Economic Dispatch Approach Considering Wind Power Accommodation Risk

Peng Li et al.

Summary: This article introduces a confidence interval based distributionally robust real-time economic dispatch (CI-DRED) approach, which addresses the risk associated with accommodating wind power. By developing a novel ambiguity set based on imprecise probability theory and transforming the original nonlinear dispatch problem into a determined mixed integer linear programming problem, the proposed method effectively balances operational costs and risks. Numerical results on both the IEEE 118-bus system and a real 445-bus system demonstrate the efficiency and effectiveness of the approach.

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2021)

Article Chemistry, Multidisciplinary

A New General Type-2 Fuzzy Predictive Scheme for PID Tuning

Jafar Tavoosi et al.

Summary: A novel method for adjusting proportional-integral-derivative parameters through model predictive control and generalized type-2 fuzzy-logic systems was introduced. The designed controller was applied on a continuous stirred tank reactor and showed improved performance compared to traditional approaches.

APPLIED SCIENCES-BASEL (2021)

Article Computer Science, Information Systems

Sliding-mode surface-based adaptive actor-critic optimal control for switched nonlinear systems with average dwell time

Haoyan Zhang et al.

Summary: This paper studies adaptive optimal control based on sliding-mode surface (SMS) for a class of continuous-time switched nonlinear systems with average dwell time (ADT) using actor-critic reinforcement learning strategy. By developing a specific cost function related to SMS, the original control problem is transformed into finding a series of optimal control policies through AC neural networks. The proposed method is shown to ensure the boundedness of all signals in the considered closed-loop switched nonlinear systems through Lyapunov stability theory.

INFORMATION SCIENCES (2021)

Article Chemistry, Multidisciplinary

Backstepping Control of an Unmanned Helicopter Subjected to External Disturbance and Model Uncertainty

Wenlong Zhao et al.

Summary: This paper proposes a composite control scheme for helicopters, including a nonlinear backstepping controller and an extended state observer (ESO) to handle the complicated flapping dynamics and external disturbances. By estimating and compensating the lumped disturbance in real-time, the algorithm can achieve accurate and agile attitude tracking under external wind gust disturbances.

APPLIED SCIENCES-BASEL (2021)

Article Engineering, Electrical & Electronic

Guidelines for the Design of Finite Control Set Model Predictive Controllers

Petros Karamanakos et al.

IEEE TRANSACTIONS ON POWER ELECTRONICS (2020)

Article Computer Science, Artificial Intelligence

Robust model predictive control for constrained networked nonlinear systems: An approximation-based approach

Tao Wang et al.

NEUROCOMPUTING (2020)

Article Mathematics, Applied

Direct transcription methods based on fractional integral approximation formulas for solving nonlinear fractional optimal control problems

Abubakar Bello Salati et al.

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION (2019)

Article Automation & Control Systems

Guaranteed Constraint Satisfaction in Continuous-Time Control Problems

Fernando A. C. C. Fontes et al.

IEEE CONTROL SYSTEMS LETTERS (2019)

Article Engineering, Aerospace

Continuous-Time Predictive Control-Based Integrated Guidance and Control

Bhavnesh Panchal et al.

JOURNAL OF GUIDANCE CONTROL AND DYNAMICS (2017)

Article Automation & Control Systems

Optimal control, MPC and MPC-like algorithms for wave energy systems: An overview

Nicolas Faedo et al.

IFAC JOURNAL OF SYSTEMS AND CONTROL (2017)

Article Automation & Control Systems

Robust control of small-scale unmanned helicopter with matched and mismatched disturbances

Xing Fang et al.

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS (2016)