The increasing integration of electric vehicle(EV)loads into power systems necessitates understanding their impact on stability.Small-magnitude perturbations,if persistent,can cause low-frequency oscillations,leading ...The increasing integration of electric vehicle(EV)loads into power systems necessitates understanding their impact on stability.Small-magnitude perturbations,if persistent,can cause low-frequency oscillations,leading to synchronism loss and mechanical stress.This work analyzes the effect of voltage-dependent EV loads on this small-signal stability.The study models an EV load within a Single-Machine Infinite Bus(SMIB)system.It specifically evaluates the influence of EV charging through the DC link capacitor of a Unified Power Flow Controller(UPFC),a key device for damping oscillations.The system’s performance is compared to a modified version equipped with both a UPFC and a Linear Quadratic Regulator(LQR)controller.Results confirm the significant influence of EV charging on the power network.The analysis demonstrates that the best performance is achieved with the SMIB system utilizing the combined UPFC and LQR controller.This configuration effectively dampens low-frequency oscillations,yielding superior results by reducing the system’s rise time,settling time,and peak overshoot.展开更多
Excessive unbalanced vibrations of rotor-bearing systems significantly affect the stability and safety of high-end rotating machinery,such as aero engines,turbo-generators,and high-end machine tools.To realize the on-...Excessive unbalanced vibrations of rotor-bearing systems significantly affect the stability and safety of high-end rotating machinery,such as aero engines,turbo-generators,and high-end machine tools.To realize the on-line self-recovery of unbalanced vibration faults in a rotor system,a self-recovery regulation method based on the grey wolf optimization-adaptive linear quadratic regulator(GWO-ALQR)is proposed.First,a self-recovery regulation system for unbalanced vibrations was constructed,with the state-space equation of the control system obtained and discretized based on the dynamic equation of the rotor-bearing system.Subsequently,a self-recovery regulation method for unbalanced vi-brations based on GWO-ALQR was designed based on the state-space equation.In this method,the parameters of the control system are optimized using grey wolf optimization(GwO),with the working conditions identified on-line.The optimization parameters were selected independently,while the control commands were generated through a linear quadratic regulator(LQR)to control the action of the actuator to achieve self-recovery of the unbalanced vibration.The experimental results indicate that the unbalanced vibration of the rotor system can be restrained below the expected vibration threshold by the self-recovery regulation system based on GWO-ALQR and the final vibration suppression effect can exceed 70%.展开更多
Linear quadratic regulator(LQR) and proportional-integral-derivative(PID) control methods, which are generally used for control of linear dynamical systems, are used in this paper to control the nonlinear dynamical sy...Linear quadratic regulator(LQR) and proportional-integral-derivative(PID) control methods, which are generally used for control of linear dynamical systems, are used in this paper to control the nonlinear dynamical system. LQR is one of the optimal control techniques, which takes into account the states of the dynamical system and control input to make the optimal control decisions.The nonlinear system states are fed to LQR which is designed using a linear state-space model. This is simple as well as robust. The inverted pendulum, a highly nonlinear unstable system, is used as a benchmark for implementing the control methods. Here the control objective is to control the system such that the cart reaches a desired position and the inverted pendulum stabilizes in the upright position. In this paper, the modeling and simulation for optimal control design of nonlinear inverted pendulum-cart dynamic system using PID controller and LQR have been presented for both cases of without and with disturbance input. The Matlab-Simulink models have been developed for simulation and performance analysis of the control schemes. The simulation results justify the comparative advantage of LQR control method.展开更多
This paper designs a novel controller to improve the path-tracking performance of articulated dump truck(ADT). By combining linear quadratic regulator(LQR) with genetic algorithm(GA), the designed controller is used t...This paper designs a novel controller to improve the path-tracking performance of articulated dump truck(ADT). By combining linear quadratic regulator(LQR) with genetic algorithm(GA), the designed controller is used to control linear and angular velocities on the midpoint of the front frame. The novel controller based on the error dynamics model is eventually realized to track the path high-precisely with constant speed. The results of simulation and experiment show that the LQR-GA controller has a better tracking performance than the existing methods under a low speed of 3 m/s. In this paper, kinematics model and simulation control models based on co-simulation of ADAMS and Matlab/Simulink are established to verify the proposed strategy. In addition, a real vehicle experiment is designed to further more correctness of the conclusion. With the proposed controller and considering the steering model in the simulation, the control performance is improved and matches the actual situation better. The research results contribute to the development of automation of ADT.展开更多
Selection of better optimized unified power flow controller （UPFC） control inputs along with simultaneous coordinated design of power system stabilizer （PSS） is a challenge in the present scenario of power systems...Selection of better optimized unified power flow controller （UPFC） control inputs along with simultaneous coordinated design of power system stabilizer （PSS） is a challenge in the present scenario of power systems. Hence, in this paper, four sets of experiments performed are presented. First set of experiments are without disturbance scenario where switching is done using linear quadratic regulators （LQR＇s）. Second set is for power systems with disturbances using linear quadratic gaussian （LQG）. Switching control algorithms presented here are tested on the single machine infinite bus （SMIB） linearised Phillips Heffron model of power system using MATLAB/SIMULINK~ platform.展开更多
The arm driven inverted pendulum system is a highly nonlinear model, muhivariable and absolutely unstable dynamic system so it is very difficult to obtain exact mathematical model and balance the inverted pendulum wit...The arm driven inverted pendulum system is a highly nonlinear model, muhivariable and absolutely unstable dynamic system so it is very difficult to obtain exact mathematical model and balance the inverted pendulum with variable position of the ann. To solve this problem, this paper presents a mathematical model for arm driven inverted pendulum in mid-position configuration and an adaptive gain scheduling linear quadratic regulator control method for the stabilizing the inverted pendulum. The proposed controllers for arm driven inverted pendulum are simulated using MATLAB-SIMULINK and implemented on an experiment system using PIC 18F4431 mieroeontroller. The result of experiment system shows the control performance to be very good in a wide range stabilization of the arm position.展开更多
The main idea behind the present research is to design a state-feedback controller for an underactuated nonlinear rotary inverted pendulum module by employing the linear quadratic regulator(LQR)technique using local a...The main idea behind the present research is to design a state-feedback controller for an underactuated nonlinear rotary inverted pendulum module by employing the linear quadratic regulator(LQR)technique using local approximation.The LQR is an excellent method for developing a controller for nonlinear systems.It provides optimal feedback to make the closed-loop system robust and stable,rejecting external disturbances.Model-based optimal controller for a nonlinear system such as a rotatory inverted pendulum has not been designed and implemented using Newton-Euler,Lagrange method,and local approximation.Therefore,implementing LQR to an underactuated nonlinear system was vital to design a stable controller.A mathematical model has been developed for the controller design by utilizing the Newton-Euler,Lagrange method.The nonlinear model has been linearized around an equilibrium point.Linear and nonlinear models have been compared to find the range in which linear and nonlinear models’behaviour is similar.MATLAB LQR function and system dynamics have been used to estimate the controller parameters.For the performance evaluation of the designed controller,Simulink has been used.Linear and nonlinear models have been simulated along with the designed controller.Simulations have been performed for the designed controller over the linear and nonlinear system under different conditions through varying system variables.The results show that the system is stable and robust enough to act against external disturbances.The controller maintains the rotary inverted pendulum in an upright position and rejects disruptions like falling under gravitational force or any external disturbance by adjusting the rotation of the horizontal link in both linear and nonlinear environments in a specific range.The controller has been practically designed and implemented.It is vivid from the results that the controller is robust enough to reject the disturbances in milliseconds and keeps the pendulum arm deflection angle to zero degrees.展开更多
文摘The increasing integration of electric vehicle(EV)loads into power systems necessitates understanding their impact on stability.Small-magnitude perturbations,if persistent,can cause low-frequency oscillations,leading to synchronism loss and mechanical stress.This work analyzes the effect of voltage-dependent EV loads on this small-signal stability.The study models an EV load within a Single-Machine Infinite Bus(SMIB)system.It specifically evaluates the influence of EV charging through the DC link capacitor of a Unified Power Flow Controller(UPFC),a key device for damping oscillations.The system’s performance is compared to a modified version equipped with both a UPFC and a Linear Quadratic Regulator(LQR)controller.Results confirm the significant influence of EV charging on the power network.The analysis demonstrates that the best performance is achieved with the SMIB system utilizing the combined UPFC and LQR controller.This configuration effectively dampens low-frequency oscillations,yielding superior results by reducing the system’s rise time,settling time,and peak overshoot.
基金Supported by National Natural Science Foundation of China(Grant No.51875031)Beijing Municipal Natural Science Foundation of China(Grant No.3212010).
文摘Excessive unbalanced vibrations of rotor-bearing systems significantly affect the stability and safety of high-end rotating machinery,such as aero engines,turbo-generators,and high-end machine tools.To realize the on-line self-recovery of unbalanced vibration faults in a rotor system,a self-recovery regulation method based on the grey wolf optimization-adaptive linear quadratic regulator(GWO-ALQR)is proposed.First,a self-recovery regulation system for unbalanced vibrations was constructed,with the state-space equation of the control system obtained and discretized based on the dynamic equation of the rotor-bearing system.Subsequently,a self-recovery regulation method for unbalanced vi-brations based on GWO-ALQR was designed based on the state-space equation.In this method,the parameters of the control system are optimized using grey wolf optimization(GwO),with the working conditions identified on-line.The optimization parameters were selected independently,while the control commands were generated through a linear quadratic regulator(LQR)to control the action of the actuator to achieve self-recovery of the unbalanced vibration.The experimental results indicate that the unbalanced vibration of the rotor system can be restrained below the expected vibration threshold by the self-recovery regulation system based on GWO-ALQR and the final vibration suppression effect can exceed 70%.
文摘Linear quadratic regulator(LQR) and proportional-integral-derivative(PID) control methods, which are generally used for control of linear dynamical systems, are used in this paper to control the nonlinear dynamical system. LQR is one of the optimal control techniques, which takes into account the states of the dynamical system and control input to make the optimal control decisions.The nonlinear system states are fed to LQR which is designed using a linear state-space model. This is simple as well as robust. The inverted pendulum, a highly nonlinear unstable system, is used as a benchmark for implementing the control methods. Here the control objective is to control the system such that the cart reaches a desired position and the inverted pendulum stabilizes in the upright position. In this paper, the modeling and simulation for optimal control design of nonlinear inverted pendulum-cart dynamic system using PID controller and LQR have been presented for both cases of without and with disturbance input. The Matlab-Simulink models have been developed for simulation and performance analysis of the control schemes. The simulation results justify the comparative advantage of LQR control method.
基金the Fundamental Research Funds for the Central Universities of China(No.FRF-TP-15-023A1)the National Key R&D Program Project(Nos.2016YFC0802905 and 2018YFC0604403)
文摘This paper designs a novel controller to improve the path-tracking performance of articulated dump truck(ADT). By combining linear quadratic regulator(LQR) with genetic algorithm(GA), the designed controller is used to control linear and angular velocities on the midpoint of the front frame. The novel controller based on the error dynamics model is eventually realized to track the path high-precisely with constant speed. The results of simulation and experiment show that the LQR-GA controller has a better tracking performance than the existing methods under a low speed of 3 m/s. In this paper, kinematics model and simulation control models based on co-simulation of ADAMS and Matlab/Simulink are established to verify the proposed strategy. In addition, a real vehicle experiment is designed to further more correctness of the conclusion. With the proposed controller and considering the steering model in the simulation, the control performance is improved and matches the actual situation better. The research results contribute to the development of automation of ADT.
文摘Selection of better optimized unified power flow controller （UPFC） control inputs along with simultaneous coordinated design of power system stabilizer （PSS） is a challenge in the present scenario of power systems. Hence, in this paper, four sets of experiments performed are presented. First set of experiments are without disturbance scenario where switching is done using linear quadratic regulators （LQR＇s）. Second set is for power systems with disturbances using linear quadratic gaussian （LQG）. Switching control algorithms presented here are tested on the single machine infinite bus （SMIB） linearised Phillips Heffron model of power system using MATLAB/SIMULINK~ platform.
文摘The arm driven inverted pendulum system is a highly nonlinear model, muhivariable and absolutely unstable dynamic system so it is very difficult to obtain exact mathematical model and balance the inverted pendulum with variable position of the ann. To solve this problem, this paper presents a mathematical model for arm driven inverted pendulum in mid-position configuration and an adaptive gain scheduling linear quadratic regulator control method for the stabilizing the inverted pendulum. The proposed controllers for arm driven inverted pendulum are simulated using MATLAB-SIMULINK and implemented on an experiment system using PIC 18F4431 mieroeontroller. The result of experiment system shows the control performance to be very good in a wide range stabilization of the arm position.
文摘The main idea behind the present research is to design a state-feedback controller for an underactuated nonlinear rotary inverted pendulum module by employing the linear quadratic regulator(LQR)technique using local approximation.The LQR is an excellent method for developing a controller for nonlinear systems.It provides optimal feedback to make the closed-loop system robust and stable,rejecting external disturbances.Model-based optimal controller for a nonlinear system such as a rotatory inverted pendulum has not been designed and implemented using Newton-Euler,Lagrange method,and local approximation.Therefore,implementing LQR to an underactuated nonlinear system was vital to design a stable controller.A mathematical model has been developed for the controller design by utilizing the Newton-Euler,Lagrange method.The nonlinear model has been linearized around an equilibrium point.Linear and nonlinear models have been compared to find the range in which linear and nonlinear models’behaviour is similar.MATLAB LQR function and system dynamics have been used to estimate the controller parameters.For the performance evaluation of the designed controller,Simulink has been used.Linear and nonlinear models have been simulated along with the designed controller.Simulations have been performed for the designed controller over the linear and nonlinear system under different conditions through varying system variables.The results show that the system is stable and robust enough to act against external disturbances.The controller maintains the rotary inverted pendulum in an upright position and rejects disruptions like falling under gravitational force or any external disturbance by adjusting the rotation of the horizontal link in both linear and nonlinear environments in a specific range.The controller has been practically designed and implemented.It is vivid from the results that the controller is robust enough to reject the disturbances in milliseconds and keeps the pendulum arm deflection angle to zero degrees.
