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Search Results: 1 - 10 of 26194 matches for " mimo control "
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H2 and H Controller Design of Twin Rotor System (TRS)  [PDF]
Usman Ahmad, Waqas Anjum, Syed Mahad Ali Bukhari
Intelligent Control and Automation (ICA) , 2013, DOI: 10.4236/ica.2013.41008
Abstract:

Control engineering had been the core of all engineering fields all the time. As the name depicts, control of different parameters of various industrial or commercial equipment like plants, vehicles, aircrafts and etc is obtained. Robust and optimal control of these equipments plays a vital role. This paper presents a design of H2 and H control for a Twin Rotor System (TRS). TRS is a multi input multi output (MIMO) nonlinear system. The main objective is to control the angular position of the lever bar of TRS. It is having strong coupling between inputs and outputs. The model is first linearized and then controllers are designed to control the positions of lever bar. Simulations are made in MAT- LAB/SIMULINK. Model parameters are also provided in the end.

Vibration Annihilation of Sandwiched Beam with MROF DTSMC  [PDF]
Vivek Rathi, Ahmad Ali Khan
Engineering (ENG) , 2017, DOI: 10.4236/eng.2017.99046
Abstract: In the present paper, an analytical model of a flexible beam fixed at an end with embedded shear sensors and actuators is developed. The smart cantilever beam model is evolved using a piezoelectric sandwich beam element, which accommodates sensor and actuator embedded at distinct locations and a regular sandwiched beam element, having rigid foam at the core. A FE model of a piezoelectric sandwich beam is evolved using laminated beam theory in MATLAB?. Each layer behaves as a Timoshenko beam and the cross-section of the beam remains plane and rotates about the neutral axis of the beam, but it does not remain normal to the deformed longitudinal axis. Keeping the sensor and actuator location fixed in a MIMO system, state space models of the smart cantilever beam is obtained. The proper selection of control strategy is very crucial in order to obtain the better control. In this paper a DSM controller designed to control the first three modes of vibration of the smart cantilever beam and their performances are represented on the basis of control signal input, sensor output and sliding functions. It is found that DSM controller provides superior control than other conventional controllers and also MROF DSM controller is much better than SISO DSM controller.
Sliding Mode Control, with Integrator, for a Class of Mimo Nonlinear Systems  [PDF]
Anouar Benamor, Larbi Chrifi-alaui, Hassani Messaoud, Mohamed Chaabane
Engineering (ENG) , 2011, DOI: 10.4236/eng.2011.35050
Abstract: In this paper, the robust control problem of general nonlinear multi-input multi-output (MIMO) systems is proposed. The robustness against unknown disturbances is considered. Two algorithms based on the Sliding Mode Control (SMC) for nonlinear coupled multi-input multi-output (MIMO) systems are proposed: the first order sliding mode control (FOSMC) with saturation (sat) function and the FOSMC with sat combined with integrator controller. Those algorithms were simulated and implemented on the three tanks test-bed system and the exprimental results confirm the effectiveness of our control design.
Self-Tuning Control for MIMO Network Systems  [PDF]
Magdi S. Mahmoud, Matasm M. Hassan Hamid
Journal of Signal and Information Processing (JSIP) , 2012, DOI: 10.4236/jsip.2012.32020
Abstract: The advances in MIMO systems and networking technologies introduced a revolution in recent times, especially in wireless and wired multi-cast (multi-point-to-multi-point) transmission field. In this work, the distributed versions of self-tuning proportional integral plus derivative (SPID) controller and self-tuning proportional plus integral (SPI) controller are described. An explicit rate feedback mechanism is used to design a controller for regulating the source rates in wireless and wired multi-cast networks. The control parameters of the SPID and SPI controllers are determined to ensure the stability of the control loop. Simulations are carried out with wireless and wired multi-cast models, to evaluate the performance of the SPID and SPI controllers and the ensuing results show that SPID scheme yields better performance than SPI scheme; however, it requires more computing time and central processing unit (CPU) resources.
Comments on "Design of Fault-Tolerant Mimo System From LQR Theory"
一种从LQR理论设计容错MIMO系统方法的非普适性

Huang Xianqing,
黄献青

自动化学报 , 1995,
Abstract: 一种从LQR理论设计容错MIMO系统方法的非普适性黄献青(华中理工大学自动控制工程系武汉430074)关键词MIMO系统,容错控制,LQR理论.1引言对于MIMO系统的容错控制,已有许多的研究“,‘’.文[3]提出一种从LQR理论出发设计稳定容错MI...
Filtrado digital neuronal difuso: caso MIMO
García Infante,Juan Carlos; Medel Juárez,José de J; Sánchez García,Juan Carlos;
Ingeniería e Investigación , 2011,
Abstract: multivariate identifier filters (multiple inputs and multiple outputs - mimo) are adaptive digital systems having a loop in accordance with an objective function to adjust matrix parameter convergence to observable reference system dynamics. one way of complying with this condition is to use fuzzy logic inference mechanisms which interpret and select the best matrix parameter from a knowledge base. such selection mechanisms with neural networks can provide a response from the best operational level for each change in state (shannon, 1948). this paper considers the mimo digital filter model using neuro fuzzy digital filtering to find an adaptive parameter matrix which is integrated into the kalman filter by the transition matrix. the filter uses the neural network as backpropagation into the fuzzy mechanism to do this, interpreting its variables and its respective levels and selecting the best values for automatically adjusting transition matrix values. the matlab simulation describes the neural fuzzy digital filter giving an approximation of exponential convergence seen in functional error.
Filtrado digital neuronal difuso: caso MIMO Neural fuzzy digital filtering: multivariate identifier filters involving multiple inputs and multiple outputs (MIMO)
García Infante Juan Carlos,Medel Juárez José de J.,Sánchez García Juan Carlos
Ingeniería e Investigación , 2011,
Abstract: Los filtros identificadores multivariables (MIMO) son sistemas digitales adaptivos que cuentan con retroalimentación para que, de acuerdo a una función objetivo, ajusten su matriz de parámetros con la que se aproximan a la di-námica observable del sistema de referencia. Una forma de que un identificador cumpla con esas condiciones, es la de la lógica difusa por medio de sus mecanismos de in-ferencia que interpretan y seleccionan en una base de co-nocimiento la mejor matriz de parámetros. Estos mecanismos de selección mediante las redes neuronales permiten encontrar la respuesta con el mejor nivel de operación para cada cambio de estado (Shannon, 1948). En este artículo se considera en el modelo MIMO del filtrado digital, el proceso neuronal difuso para la estimación matricial de parámetros adaptiva, que se integra en el filtro de Kalman a través de la matriz de transición. Para ello se utilizó la red neuronal del tipo retropropagación en el mecanismo difuso, interpretando sus variables y sus respectivos niveles, seleccionando los mejores valores para ajustar automáticamente los valores de la matriz de transición. La simulación en Matlab presenta al filtrado digital neuronal difuso dando el seguimiento, observándose un funcional de error decreciente exponencialmente. Multivariate identifier filters (multiple inputs and multiple outputs - MIMO) are adaptive digital systems having a loop in accordance with an objective function to adjust matrix parameter convergence to observable reference system dynamics. One way of complying with this condition is to use fuzzy logic inference mechanisms which interpret and select the best matrix parameter from a knowledge base. Such selection mechanisms with neural networks can provide a response from the best operational level for each change in state (Shannon, 1948). This paper considers the MIMO digital filter model using neuro fuzzy digital filtering to find an adaptive parameter matrix which is integrated into the Kalman filter by the transition matrix. The filter uses the neural network as back-propagation into the fuzzy mechanism to do this, interpreting its variables and its respective levels and selecting the best values for automatically adjusting transition matrix values. The Matlab simulation describes the neural fuzzy digital filter giving an approximation of exponential convergence seen in functional error.
Reinforcement Learning with FCMAC for TRMS Control
Jih-Gau Juang,Yi-Chong Chiang
Research Journal of Applied Sciences, Engineering and Technology , 2013,
Abstract: This study proposes an intelligent control scheme that integrate reinforcement learning in Fuzzy CMAC (FCMAC) for a Twin Rotor Multi-input and multi-output System (TRMS). In the control design, fuzzy CMAC controller is utilized to compensate for PID control signal and the reinforcement learning refines the compensation to the control signal. CMAC with fuzzy system has better performance than the conventional CMAC in TRMS attitude tracking control. With reinforcement learning, the proposed control scheme provides even better performance and control for the TRMS.
Direct adaptive fuzzy robust control for a class ofnonlinear MIMO systems
一类非线性MIMO系统的直接自适应模糊鲁棒控制

LIU Guo-rong,WAN Bai-wu,
刘国荣
,万百五

控制理论与应用 , 2002,
Abstract: The direct adaptive fuzzy robust control scheme is proposed for a class of unknown nonlinear MIMO systems in this paper.It has been shown by theory analysis and digital simulation that the scheme guarantees the close-loop system is globally stable and achieves H-infinity traking performance idex,and the influence of external disturbances and fuzzy logic approximation errors and the cross-coupling of inputs to outputs on the tracking error is attenuated to a prescribed level,and robustness of the system is good.
Design of Fault-Tolerant MIMO System From LQR Theory
从LQR理论设计容错MIMO系统的方法

Ye Yinzhong,Li Sanguang,Jiang Weisun,
叶银忠
,李三广,蒋慰孙

自动化学报 , 1993,
Abstract: In this paper a new design procedure is proposed. This procedure can lead to a stable fault-tolerant MIMO system from LQR theory. It is shown that, in the sense of system stability, a state feedback MIMO system capable of tolerating either the actuator or the sensor failure or even both can grow out of modification of the quadratic weights in the LQ cost function. Such a modification procedure is given for the design of a stable fault-tolerant MIMO system.
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