Current Issue : October-December Volume : 2022 Issue Number : 4 Articles : 5 Articles
In this work, novel stability results for load frequency control (LFC) system considering time-varying delays, nonlinearly perturbed load, and time-varying disturbance of system parameters are proposed by using proportional-integral control strategy. Considering the nonlinearly exogenous load disturbance and system parameters disturbance, an improved stability criterion in the form of linear matrix inequalities (LMIs) is derived by novel simple Lyapunov–Krasovskii functionals (LKFs). The delaydependent matrix in quadratic term, cross terms of variables, and quadratic terms multiplied by 1st, 2nd, and 3rd degrees of scalar functions are included in the new simple LKF. Taking the single-area and two-area LFC system installed with proportionalintegral (PI) controller as example, our results surpass the previous maximum allowable size of time delay. Meanwhile, the relationship between time delay varying rate, load disturbance degree, gains of PI controller, and delay margin of the LFC system is researched separately. The results can provide guidance to tune the PI controller for achieving maximum delay margin, in which the LFC system can withstand without losing stability. At last, the simulation results verify the effectiveness and superiority of the proposed stability criterion....
Active magnetic bearings, which are open-loop and unstable, require a feedback control system to ensure stable operation of the rotating machines that they support. Proportional-integralderivative (PID) controllers are widely used in field applications of these bearings for this purpose. PID controllers are designed to work effectively within the linear region of operation of the rotating machines. Due to the inherent nonlinearity of the active magnetic bearings, large unbalance forces that may occur in these machines result in nonlinear vibration responses. Therefore, the PID controller’s effectiveness to control the vibration of the rotating machines is considerably reduced when the unbalance forces in these machines become large. Other control strategies, such as the fuzzy logic and the sliding mode control schemes, are more apt to deal with the nonlinear responses of the rotating machines supported by active magnetic bearings. The present work proposes an integrated fuzzy bang-bang relay controller for a rigid rotor mounted on active magnetic bearings. The effectiveness of this controller to suppress rotor vibrations is examined numerically. Performance comparison of this controller with the conventional fuzzy logic and PD controllers are made for different initial conditions, rotor imbalance magnitudes, and rotor angular speeds. At extreme operating conditions due to large rotor unbalance forces, where the magnetic bearings are highly nonlinear, the proposed integrated fuzzy bang-bang relay controller proved to be more superior over the conventional fuzzy logic and PD controllers....
In order to enable the driverless vehicle formation controller to automatically control the driving of the fleet, an intelligent driverless vehicle control system based on the CAN controller is proposed. Expansion convolution of different expansion rates is used to obtain multi-scale target information and to fuse the feature information at different scales during upsampling to enrich the semantic information. Finally, the driverless CAN bus communication platform was established, the driverless monitoring interface was developed, and the software program was written; experiments on the steering control, speed control, voltage, current, speed, and angular speed acquisition, respectively, were performed. The experimental results show that the average semantic segmentation accuracy of the obstacles in concentrated vehicles, pedestrians, and bicycles reached 84.6%, and the detection and segmentation accuracy of the models was good. Therefore, the unmanned intelligent vehicle control system designed in this paper can meet the performance requirements of the vehicle control. No matter whether the given desired path is a straight line or a curve, the unmanned car can complete the path tracking control quickly, stably, and accurately....
Aiming at the influence of friction, leakage, noise and other nonlinear factors on the performance of the electro-hydraulic servo system of a continuous rotary motor, a finite-time composite controller for the aforementioned servo system is proposed. First, a mathematical model of the electro-hydraulic servo system was analyzed, and the input and output angle data of the motor were collected for system identification. Subsequently, the ARMAX identification model of the continuous rotary motor system was obtained. Then, according to the observed advantages, namely faster capability of the finite-time controller (FTC) to converge the system, and ability of the finite-time observer to reduce the steady-state error of the system, the finite-time controller and finite-time state observer of a continuous rotary electro-hydraulic servo motor were respectively designed. Finally, comparison with PID control simulation shows that the compound controller could effectively improve the control accuracy and performance of the system....
Iterative Learning Control is an effective way of controlling the errors which act directly on the repetitive system. The stability of the system is the main objective in designing. The Small Gain Theorem is used in the design process of State Feedback ILC. The feedback controller along with the Iterative Learning Control adds an advantage in producing a system with minimal error. The past error and current error feedback Iterative control system are studied with reference to the region of disturbance at the output. This paper mainly focuses on comparing the region of disturbance at the output end. The past error feed forward and current error feedback systems are developed on the singular values. Hence, we use the singular values to set an output disturbance limit for the past error and current error feedback ILC system. Thus, we obtain a result of past error feed forward performing better than the current error feedback system. This implies greater region of disturbance suppression to past error feed forward than the other....
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