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This review paper introduces the modeling, measurement, identification and control of direct current motors based on the state space modeling and the transfer function representation. These models are identified by real laboratory measurements, and the simulated results are compared with the measurements. Continuous-time and discrete-time PID (Proportional-Integral-Derivative) controllers, discrete-time state feedback and linear quadratic controllers are designed mathematically. The designed controllers are realized by the microcontroller Arduino UNO, and the behavior of the controllers is compared and analyzed. The noisy current signal has been measured by a discrete-time observer, steady-state Kalman filtering is also studied. The practical results of the implemented controllers support the theoretical results very well. [ABSTRACT FROM AUTHOR]

The state feedback controller design for a class of Generalized Proportional Fractional Order (GPFO) Nonlinear Systems is presented in this paper. The design is based on the combination of the One-Sided Lipschitz (OSL) system class with GPFO modeling. The main contribution of this study is that, to the best of the authors' knowledge, this work presents the first state feedback control design for GPFO systems. The suggested state feedback controller is intended to ensure the system's generalized Mittag Leffler (GML) stability and to deliver optimal performance. The findings of this paper show that the proposed strategy is effective in stabilizing Generalized Proportional Fractional Order Nonlinear Systems. A numerical example is presented to demonstrate the usefulness of the stated theoretical conclusions. [ABSTRACT FROM AUTHOR]

In this paper, robust H ∞ control for fractional-order switched systems (FOSSs) with uncertainty is studied. Firstly, the fractional-order switching law for FOSSs is proposed. Then, H ∞ control for FOSSs is proven based on the switching law and linear matrix inequalities (LMIs). Moreover, H ∞ control for FOSSs with a state feedback controller is extended. Furthermore, the LMI-based condition of robust H ∞ control for FOSSs with uncertainty is proven. Furthermore, the condition of robust H ∞ control is proposed to design the state feedback controller. Finally, four simulation examples verified the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper describes a method for the control of transient exhaust gas recirculation (EGR) systems. Firstly, a state space model of the air system is developed by simplifying a mean value model. The state space model is linearized by using linearization theory and validated by the GT-Power data with an operating point of the diesel engine. Secondly, a state feedback controller based on the intake oxygen mass fraction is designed for EGR control. Since direct measurement of the intake oxygen mass fraction is unavailable on the engine, the estimation method for intake oxygen mass fraction has been proposed in this paper. The control strategy is analyzed by using co-simulation with the Matlab/Simulink and GT-Powers software. Finally, the whole control system is experimentally validated against experimental data of a turbocharged diesel engine. The control effect of the state feedback controller compared with PID controller proved to be further verify the feasibility and advantages of the proposed state feedback controller. [ABSTRACT FROM AUTHOR]

The state feedback controller is increasingly applied in electrical drive systems due to robustness and good disturbance compensation, however its main drawback is related to complex and time consuming tuning process. It is particularly troublesome for designer, if the plant is compound, nonlinear elements are taken into account, measurement noise is considered, etc. In this paper the application of nature-inspired optimization algorithm to automatic tuning of state feedback speed controller (SFC) for two-mass system (TMS) is proposed. In order to obtain optimal coefficients of SFC, the Artificial Bee Colony algorithm (ABC) is used. The objective function is described and discussed in details. Comparison with analytical tuning method of SFC is also included. Additionally, the stability analysis for the control system, optimized using the ABC algorithm, is presented. Synthesis procedure of the controller is utilized in Matlab/Simulink from MathWorks. Next, obtained coefficients of the controller are examined on the laboratory stand, also with variable moment of inertia values, to indicate robustness of the controller with optimal coefficients. [ABSTRACT FROM AUTHOR]

In order to precisely control the wind power generation systems under nonlinear variable wind velocity, this paper proposes a novel maximum power tracking (MPPT) strategy for wind turbine systems based on a hybrid wind velocity forecasting algorithm. The proposed algorithm adapts the bat algorithm and improved extreme learning machine (BA-ELM) for forecasting wind speed to alleviate the slow response of anemometers and sensors, considering that the change of wind speed requires a very short response time. In the controlling strategy, to optimize the output power, a state feedback control technique is proposed to achieve the rotor flux and rotor speed tracking purpose based on MPPT algorithm. This method could decouple the current and voltage of induction generator to track the reference of stator current and flux linkage. By adjusting the wind turbine mechanical speed, the wind energy system could operate at the optimal rotational speed and achieve the maximal power. Simulation results verified the effectiveness of the proposed technique. [ABSTRACT FROM AUTHOR]