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Continuous sliding mode controllers for multi-input multi-output systems

NONLINEAR DYNAMICS 2018年第4期94卷 2727-2747页

作者： Cho, Hancheol Wanichanon, Thanapat Udwadia, Firdaus E. Sandia Natl Labs Water Power Technol Program Albuquerque NM 87123 USA Mahidol Univ Dept Mech Engn 25-25 Phutthamonthon Nakhon Pathom 73170 Thailand Univ Southern Calif Dept Aerosp & Mech Engn Los Angeles CA 90089 USA Univ Southern Calif Dept Civil Engn Los Angeles CA 90089 USA Univ Southern Calif Dept Math Los Angeles CA 90089 USA Univ Southern Calif Dept Informat & Operat Management Los Angeles CA 90089 USA

This paper develops new continuous sliding mode controllers for multi-input multi-output mechanical systems in the presence of unknown, but bounded uncertainties in the given forces and in the masses. Assuming the absence of the uncertainties, a reference control input is first calculated using the fundamental equation of constrained motion that causes the system trajectories to exactly track the reference while minimizing a weighted norm of the control effort. Next, in the presence of realistic uncertainties in the given forces and in the masses, two continuous sliding mode controllers are derived according to whether the mass matrix is diagonal or not. In the diagonal case, each element of the control vector is independently designed, while in the nondiagonal case the control vector is handled as a whole because its elements are coupled to one another. The two controllers are continuous because no signum functions are used. It is also shown that various forms of control input are possible depending on the control requirements among which a simple proportional-integral-derivative-type controller is exemplified in this paper. Two numerical examples serve to demonstrate the accuracy and robustness of the control methodology suggested herein.

关键词： Sliding mode control Chattering alleviation Fundamental equation of constrained motion multi-input multi-output systems

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A multi-input multi-output Model Predictive Direct Torque Control for Dual Mechanical Port Machine

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IEEE ACCESS 2023年 11卷 133730-133743页

作者： Bizhani, Hamed Ben-Brahim, Lazhar Gastli, Adel Al-Emadi, Nasser Djemai, Mohamed Qatar Univ Dept Elect Engn Doha Qatar Warsaw Univ Technol Inst Control & Ind Elect Fac Elect Engn PL-00665 Warsaw Poland UPHF LAMIH INSA HdF F-59313 Valenciennes France ENSEA Quartz F-95000 Valenciennes France

In this paper, a multi-input multi-output (MIMO) model predictive direct torque control (MPDTC) strategy for a dual mechanical port machine (DMPM) is proposed. A MIMO state space model is developed, incorporating the electromagnetic interaction between the stator, inner rotor, and outer rotor of the DMPM. The prediction model is then derived to adjust the currents of stator and inner rotor windings, enabling independent control of the electromagnetic torques of the mechanical ports. Compared to single-input single-output based MPC and PI-based field-oriented control strategies, the proposed approach effectively mitigates the undesired electromagnetic interactions, guaranteeing smooth speed control of both mechanical ports. The simulation results carried out by MATLAB/Simulink verify the precise performance of the DMPM in different operating modes. The Hardware-in-the-Loop results further confirm that the proposed direct torque control not only regulates the inner and outer rotor independently, but can also be executed in real-time without posing any computational burden on the processor. A sensitivity analysis for evaluating the performance of the proposed strategy in the presence of variations in the electrical parameters of the DMPM is also provided.

关键词： Rotors Stator windings Inverters Electromagnetics Predictive models Mathematical models Couplings Dual mechanical port machine model predictive control direct torque control multi-input multi-output systems hardware in the loop

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Maximum likelihood stochastic gradient parameter estimation algorithm for multi-input multi-output systems

Maximum likelihood stochastic gradient parameter estimation ...

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26th Chinese Control and Decision Conference (CCDC)

作者： Li, Junhong Jiang, Ping Yang, Yi Nantong Univ Sch Elect Engn Nantong 226019 Peoples R China

This paper discusses parameter estimation problems of the multi-input multi-output systems described by input-output difference equation models. A maximum likelihood stochastic gradient algorithm with a forgetting fac... 详细信息

ISBN: (纸本)9781479937066

关键词： Parameter estimation multi-input multi-output systems Maximum likelihood Stochastic gradient

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Model Order Reduction Strategy for LTI systems and Application to PID Controller Design

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CIRCUITS systems AND SIGNAL PROCESSING 2025年第1期44卷 88-127页

作者： Duddeti, Bala Bhaskar NIT Dept Elect Engn Rourkela 769008 Orissa India SASI Inst Technol & Engn A EEE Res Ctr Dept Elect & Elect Engn Tadepalligudem 534101 Andhra Pradesh India

The mathematical modeling of the real-time system results in large-dimensional ordinary or partial differential equations, which are challenging to employ for investigation and control synthesis. Finding a comparable system of the same kind in a lower-order dimension that can maintain the core characteristics of the higher-order system (HOS) is essential. This article discusses a novel technique for HOS's reduced order approximation and control design. The proposed method modifies the Schur method for balanced truncation. The method circumvents the requirement of balancing transformation and steady-state gain (SSG) deviation as required in the truncated model reduction algorithm. The offered technique eliminates the SSG deviation without altering the dynamical behavior compared to the HOS by appending a gain enhancement factor to the numerator polynomial of the reduced system transfer matrix. The offered technique ensures that the reduced system retains the HOS stability, passivity, SSG, and all critical characteristics. The recommended method's findings are compared to the outcomes of recently published work's lower-order models. Further, using the proposed method, the reduced model has been used to design a PID controller for the flexible-missile control model and an automatic voltage regulator system. The controller produced using the simplified model provides almost the exact time domain specifications (TDS) as the controller made using the HOS, and its design is also relatively more straightforward. Step response and TDS assess lower- and higher-order controller performance.

关键词： multi-input multi-output systems High order systems Order reduction Single-input single-output systems Schur decomposition Controller design

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Optimized beamforming vector and antenna selection using autoencoder with Bayesian RNN and hybrid heuristic algorithm for MIMO systems

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INTERNATIONAL JOURNAL OF COMMUNICATION systems 2025年第3期38卷

作者： Thirupathi, Sivakumar Ranganathan, Kavitha Krishnasamy Sona Coll Technol ECE Salem 636005 Tamil Nadu India

Wireless communication systems depend on channel state information (CSI). However, the CSI collection is a significant barrier to achieving high performance. Present wireless communication models mainly rely on many antennas and related signal dispensation for increasing effectiveness. User mobility, the usage of greater frequencies, and a better number of antennas contribute to beamforming and beam management in these networks. Therefore, an improved hybrid heuristic algorithm is proposed here for providing optimized Joint beam forming and antenna selection (JBAS) in a multi-input multi-output (MIMO) model. The major novelty of the research work is to jointly perform the beam forming and antenna selection in MIMO that effectively enhanced the performance of the wireless transmission system. The major intention of this paper is to optimize the beamforming vectors and antennae by using the designed algorithm, where the spectral efficiency gets maximized. Initially, the data is collected by varying the number of users, locations, and sampling points, which is optimally selected by developing the hybrid reptile search-based lion optimization algorithm (HRS-LOA). Once it is collected, the relevant CSI is considered. This state of information is fed as input to the Auto Encoder with Bayesian Recurrent Neural Network (AE-BRNN). Finally, through the network, the optimized value of the beamforming vector and antenna is obtained, which is useful to increase the sum rate/spectral efficiency. From the numerical results, the recommended model attained a spectral efficiency of 30 bits/s/Hz, which is higher than the BWO-AE-BRNN with 13%, RSO-AE-BRNN with 16%, RSA-AE-BRNN with 17%, and LA-AE-BRNN with 40% respectively. A newly optimized beamforming vector and antenna selection using deep learning is utilized to improve the range of capacity in MIMO wireless communication models. The suggested HRS-LOA is employed to optimize the vector of beamforming from the channel state informat

关键词： auto encoder with Bayesian recurrent neural network hybrid reptile search-based lion optimization algorithm multi-input multi-output systems optimized beamforming vector and antenna selection

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Predictive Control of Nonlinear MIMO System Modelled by Fractional Hammerstein Structure Using New Optimisation Method NMHBA

Predictive Control of Nonlinear MIMO System Modelled by Frac...

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International Conference on Advanced systems and Emergent Technologies (ICASET)

作者： Chouaibi, Dhouha Chagra, Wassila Univ Tunis El Manar Natl Engn Sch Tunis Anal Concept & Control Syst Lab BP 37 Belvedere Tunis 1002 Tunisia

ISBN: (纸本)9798350384901;9798350384895

This work is dealing with the predictive control of nonlinear muti-input multi-output systems (MIMO) based on the fractional Hammerstein model. In order to compute the predictive control sequence minimizing a criterion based on the squared tracking error, we propose a new stochastic optimization method. It combines Nelder Mead and Honey Badger methods. Then, the optimization algorithm is analysed in tracking performances and computing times through MIMO fractional Hammerstein models.

关键词： fractional Hammerstein model optimization methods predictive control multi-input multi-output systems

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Improved Likelihood Probability in MIMO systems Using One-Bit ADCs

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SENSORS 2023年第12期23卷 5542-5542页

作者： Kim, Tae-Kyoung Gachon Univ Dept Elect Engn Seongnam 13120 South Korea

This study considers an improved likelihood probability in multi-input multi-output (MIMO) systems using one-bit analog-to-digital converters (ADCs). MIMO systems using one-bit ADCs are known to exhibit from performance degradation because of inaccurate likelihood probabilities. To overcome this degradation, the proposed method leverages the detected symbols to estimate the true likelihood probability by combining the initial likelihood probability. An optimization problem is formulated to minimize the mean-squared error between the true and combined likelihood probabilities, and a solution is derived using the least-squares method. Simulation results show that the proposed method obtains a signal-to-noise gain of approximately 0.3 dB to achieve a frame error rate of 10(-1) compared to conventional methods. This improvement in performance is attributed to the enhanced reliability of the likelihood probability.

关键词： multi-input multi-output systems one-bit analog-to-digital converters maximum likelihood probability weighted combining

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Adversarial Machine Learning in MIMO Wireless Communications systems

Adversarial Machine Learning in MIMO Wireless Communications...

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作者： Nasta, Michael John Northeastern University

学位级别：M.S., Master of Science/Master of Surgery

As the Internet-of-Things (IoT) increases in size, so does competition for access to the wireless channel. As a result, various researchers have determined methods to reduce channel overhead and reduce competition by developing various Convolutional Neural Network (CNN) models that compress Channel State Information (CSI). In doing so, devices need only send compressed versions of CSI to each other in order to perform beamforming. However, the use of machine learning (ML) models by devices opens a new vulnerability in that these models can be strategically attacked to reduce their accuracy. Although adversarial machine learning (AML) techniques have been applied to wireless communication systems in various forms, the topic of attacking models that estimate CSI in multi-input multi-output (MIMO) systems has remained largely unexplored. In this thesis, we explore the topic of AML in MIMO systems and develop a model which demonstrates that adversarial attacks in this domain can reduce theoretical channel capacity. Additionally, we develop a novel attack strategy that requires only access to the compressed CSI broadcast over the channel, as opposed to the full set of training data used to train the transmitter's and receiver's autoencoder. This attack strategy introduces an adversarial device to a network of a transmitter and receiver, then has the adversary run a neural network model that estimates the optimal adversarial perturbation corresponding to the compressed CSI to degrade the performance of the wireless system. In doing so, we open various new avenues for future work and improvement in the domain of AML in MIMO systems.

关键词： Adversarial machine learning Communications MIMO Wireless networks Channel State Information multi-input multi-output systems

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On strong stabilizability of MIMO infinite-dimensional systems

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AUTOMATICA 2020年 121卷 109178-109178页

作者： Unal, Hakki Ulas Iftar, Altug Eskisehir Tech Univ Dept Elect & Elect Engn TR-26555 Eskisehir Turkey

The strong stabilization problem, i.e., the problem of designing a real stable stabilizing controller, is considered for multi-input multi-output infinite-dimensional real linear systems. The considered systems may have infinitely many poles and zeros in the open right-half-plane, as well as on the imaginary axis. It is shown that the well-known parity interlacing property (pip) for real-rational systems is also a necessary condition in the most general case as long as the plant has coprime factorizations over H-infinity. which is a necessary condition for stabilizability. Furthermore, it is shown that pip is also sufficient under some additional mild assumptions. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Stabilization Stable controllers Infinite-dimensional systems multi-input multi-output systems Parity interlacing property

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Impact of Partial Band Jammer in Cognitive Radio Networks with Interference Alignment 27

Impact of Partial Band Jammer in Cognitive Radio Networks wi...

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27th Signal Processing and Communications Applications Conference (SIU)

作者： Erdogan, Eylem Aldirmaz-Colak, Sultan Namdar, Mustafa Basgumus, Arif Alakoca, Hakan Durak-Ata, Lutfiye Istanbul Medeniyet Univ Elekt & Elekt Muhendisligi Bolumu Istanbul Turkey Kocaeli Univ Elekt & Haberlesme Muhendisligi Bolumu Kocaeli Turkey Dumlupinar Univ Elekt & Elekt Muhendisligi Bolumu Kutahya Turkey Istanbul Tech Univ Bilisim Uygulamalari Anabilim Dali Bilisim Enstitusu Istanbul Turkey

ISBN: (纸本)9781728119045

In this work, the adverse effects of a partial band jammer on a multi-user, multi-input multi-output cognitive radio networks are analyzed. In the proposed model, primary user transmits its information to the receiver with the aid of linear interference alignment method which uses a precoder and an interference suppression matrix. In this network, it is assumed that a partial band jammer adversely affects the transmission quality of the primary network. The analysis starts with the derivation of end-to-end signal to jammer noise ratio. Then, with the aid of probability density function and cumulative distribution functions, symbol error probability and outage probability are derived.

关键词： Cognitive radio K-user interference alignment multi-input multi-output systems partial band jammer outage probability symbol error probability

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