scholarly journals Design Low-Order Robust Controller for Self-Balancing Two-Wheel Vehicle

2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Ngoc Kien Vu ◽  
Hong Quang Nguyen

When there is no driver, balancing the two-wheel vehicle is a challenging but fascinating problem. There are various solutions for maintaining the balance of a two-wheel vehicle. This article presents a solution for balancing a two-wheel vehicle using a flywheel according to the inverted pendulum principle. Since uncertainties influence the actual operating environment of the vehicle, we have designed a robust controller RH∞ to maintain the vehicle equilibrium. Robust controllers often have a high order that can affect the actual control performance; therefore, order reduction algorithms are proposed. Using Matlab/Simulink, we compared the performance of the control system with different reduced-order controllers to choose a suitable low-order controller. Finally, experimental results using a low-order robust controller show that the vehicle balances steadily in different scenarios: no-load, variable load, stationary, and moving.

2021 ◽  
Vol 5 (5) ◽  
pp. 598-618
Author(s):  
Vu Ngoc Kien ◽  
Nguyen Hien Trung ◽  
Nguyen Hong Quang

The electrical system's problem stabilizes the electrical system with three primary parameters: rotor angle stability, frequency stability, and voltage stability. This paper focuses on the problem of designing a low-order stable optimal controller for the generator rotor angle (load angle) stabilization system with minor disturbances. These minor disturbances are caused by lack of damping torque, change in load, or change in a generator during operation. Using the RH∞optimal robust design method for the Power System Stabilizer (PSS) to stabilize the generator’s load angle will help the PSS system work sustainably under disturbance. However, this technique's disadvantage is that the controller often has a high order, causing many difficulties in practical application. To overcome this disadvantage, we propose to reduce the order of the higher-order optimal robust controller. There are two solutions to reduce order for high-order optimal robust controller: optimal order reduction according to the given controller structure and order reduction according to model order reduction algorithms. This study selects the order reduction of the controller according to the model order reduction algorithms. In order to choose the most suitable low-order optimal robust controller that can replace the high-order optimal robust controller, we have compared and evaluated the order-reducing controllers according to many model order reduction algorithms. Using robust low-order controllers to control the generator’s rotor angle completely meets the stabilization requirements. The research results of the paper show the correctness of the controller order reduction solution according to the model order reduction algorithms and open the possibility of application in practice. Doi: 10.28991/esj-2021-01299 Full Text: PDF


2019 ◽  
Vol 37 (3) ◽  
pp. 953-986
Author(s):  
Salim Ibrir

Abstract Efficient numerical procedures are developed for model-order reduction of a class of discrete-time nonlinear systems. Based on the solution of a set of linear-matrix inequalities, the Petrov–Galerkin projection concept is utilized to set up the structure of the reduced-order nonlinear model that preserves the input-to-state stability while ensuring an acceptable approximation error. The first numerical algorithm is based on the construction of a constant optimal projection matrix and a constant Lyapunov matrix to form the reduced-order dynamics. The second proposed algorithm aims to incorporate the output of the original system to correct the instantaneous value of the truncation matrix and maintain an acceptable approximation error even with low-order systems. An extension to uncertain systems is provided. The usefulness and the efficacy of the developed procedures are approved by the consideration of two numerical examples treating a nonlinear low-order system and a high-dimensional system, issued from the discretization of the damped heat-transfer partial-differential equation.


Author(s):  
Tobias Hummel ◽  
Constanze Temmler ◽  
Bruno Schuermans ◽  
Thomas Sattelmayer

A methodology is presented to model non-compact thermoacoustic phenomena using Reduced Order Models (ROM) based on the Linearized Navier-Stokes Equations (LNSE). The method is applicable to geometries with a complex flow field as in a gas turbine combustion chamber. The LNSE, and thus the resulting ROM, include coupling effects between acoustics and mean fluid flow, and are hence capable of describing propagation and (e.g. vortical) damping of the acoustic fluctuations within the considered volume. Such a ROM then constitutes the main building block for a novel thermoacoustic stability analysis method via a low-order hybrid approach. This method presents an expansion to state-of-the-art low-order stability tools, and is conceptually based on three core features: Firstly, the multi-dimensional and volumetric nature of the ROM establishes access to account spatial variability and non-compact effects on heat release fluctuations. As a result, it is particularly useful for high frequency phenomena such as screech. Secondly, the LNSE basis grants the ROM the capability to reconstruct complex acoustic performances physically accurate. Thirdly, the formulation of the ROM in state-space allows convenient access to the frequency and time domain. In the time domain, non-linear saturation mechanisms can be included, which reproduce the non-linear stochastic limit cycle behavior of thermoacoustic oscillations. In order to demonstrate and verify the ROM’s underlying methodology, a test case using an orifice-tube geometry as the acoustic volume is performed. The generation of the ROM of the orifice-tube is conducted in a two-step procedure. As the first step, the geometrical domain is aeroacoustically characterized through the LNSE in frequency domain, and discretized via the Finite Element Method (FEM). The second step concerns the actual derivation of the ROM. The high-order dynamical system from the LNSE discretization is subjected to a modal reduction as order reduction technique. Mathematically, this modal reduction is the projection of the high-order (N ∼200,000) system into its truncated left eigenspace. An order reduction of several magnitudes (ROM order: Nr ∼100) is achieved. The resulting ROM contains all essential information about propagation and damping of the acoustic variables, and efficiently reproduces the aeroacoustic performance of the orifice-tube. Validation is achieved by comparing ROM results against numerical and experimental benchmarks from LNSE-FEM simulations and test rig measurements, respectively. Excellent agreement is found, which grants the ROM modeling approach full eligibility for further usage in the context of thermoacoustic stability modeling. This work is concluded by a methodological demonstration of performing stability analyses of non-compact thermoacoustic systems using the herein presented ROMs.


Author(s):  
Tobias Hummel ◽  
Constanze Temmler ◽  
Bruno Schuermans ◽  
Thomas Sattelmayer

A methodology is presented to model noncompact thermoacoustic phenomena using reduced-order models (ROMs) based on the linearized Navier–Stokes equations (LNSEs). The method is applicable to geometries with a complex flow field as in a gas turbine combustion chamber. The LNSEs, and thus the resulting ROM, include coupling effects between acoustics and mean fluid flow and are hence capable of describing propagation and (e.g., vortical) damping of the acoustic fluctuations within the considered volume. Such an ROM then constitutes the main building block for a novel thermoacoustic stability analysis method via a low-order hybrid approach. This method presents an expansion to state-of-the-art low-order stability tools and is conceptually based on three core features: First, the multidimensional and volumetric nature of the ROM establishes access to account spatial variability and noncompact effects on heat-release fluctuations. As a result, it is particularly useful for high-frequency phenomena such as screech. Second, the LNSE basis grants the ROM the capability to reconstruct complex acoustic performances physically accurate. Third, the formulation of the ROM in state-space allows convenient access to the frequency and time domain. In the time domain, nonlinear saturation mechanisms can be included, which reproduce the nonlinear stochastic limit cycle behavior of thermoacoustic oscillations. In order to demonstrate and verify the ROM's underlying methodology, a test case using an orifice-tube geometry as the acoustic volume is performed. The generation of the ROM of the orifice tube is conducted in a two-step procedure. As the first step, the geometrical domain is aeroacoustically characterized through the LNSE in frequency domain and discretized via the finite element method (FEM). The second step concerns the actual derivation of the ROM. The high-order dynamical system from the LNSE discretization is subjected to a modal reduction as order reduction technique. Mathematically, this modal reduction is the projection of the high-order (N∼ 200,000) system into its truncated left eigenspace. An order reduction of several magnitudes (ROM order: Nr∼ 100) is achieved. The resulting ROM contains all essential information about propagation and damping of the acoustic variables, and efficiently reproduces the aeroacoustic performance of the orifice tube. Validation is achieved by comparing ROM results against numerical and experimental benchmarks from LNSE–FEM simulations and test rig measurements, respectively. Excellent agreement is found, which grants the ROM modeling approach full eligibility for further usage in the context of thermoacoustic stability modeling. This work is concluded by a methodological demonstration of performing stability analyses of noncompact thermoacoustic systems using the herein presented ROMs.


2020 ◽  
Vol 49 (4) ◽  
pp. 20200158
Author(s):  
V. G. Pratheep ◽  
E. B. Priyanka ◽  
S. Thangavel ◽  
K. Gomathi

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Ngoc Kien Vu ◽  
Hong Quang Nguyen

In recent years, more and more scientists have been interested in research on driving two-wheel bicycles. The problems in two-wheel bicycle control problem are self-balancing, uncertain models, and the impact of noise. In the paper, to solve the self-balancing problem, we use the flywheel method according to the inverted pendulum principle. To overcome the effects of the uncertain model, the impact of noise, we designed the vehicle balance controller according to the robust control algorithm. However, robust controllers often have a high order, which affects the quality during real control. To simplify the robust controller, we propose the use of a model order reduction algorithm. The simulation and experimental results have proved the correctness of the solutions given in the paper.


2019 ◽  
Vol 11 (01) ◽  
pp. 1950008
Author(s):  
Binwen Wang ◽  
Xueling Fan

Flutter is an aeroelastic phenomenon that may cause severe damage to aircraft. Traditional flutter evaluation methods have many disadvantages (e.g., complex, costly and time-consuming) which could be overcome by ground flutter test technique. In this study, an unsteady aerodynamic model is obtained using computational fluid dynamics (CFD) code according to the procedure of frequency domain aerodynamic calculation. Then, the genetic algorithm (GA) method is adopted to optimize interpolation points for both excitation and response. Furthermore, the minimum-state method is utilized for rational fitting so as to establish an aerodynamic model in time domain. The aerodynamic force is simulated through exciters and the precision of simulation is guaranteed by multi-input and multi-output robust controller. Finally, ground flutter simulation test system is employed to acquire the flutter boundary through response under a range of air speeds. A good agreement is observed for both velocity and frequency of flutter between the test and modeling results.


2021 ◽  
Author(s):  
Ram Kumar ◽  
Afzal Sikander

Abstract The Coulomb and Franklin laws (CFL) algorithm is used to construct a lower order model of higher-order continuous time linear time-invariant (LTI) systems in this study. CFL is quite easy to implement in obtaining reduced order model of large scale system in control engineering problem as it employs the combined effect of Coulomb’s and Franklin’s laws to find the best values in search space. The unknown coefficients are obtained using the CFLA methodology, which minimises the integral square error (ISE) between the original and proposed ROMs. To achieve the reduced order model, five practical systems of different orders are considered. Finally, multiple performance indicators such as the ISE, integral of absolute error (IAE), and integral of time multiplied by absolute error were calculated to determine the efficacy of the proposed methodology. The simulation results were compared to previously published well-known research.


2020 ◽  
Vol 26 (2) ◽  
pp. 24-31
Author(s):  
Omer Aydogdu ◽  
Mehmet Latif Levent

In this study, a new controller design was created to increase the control performance of a variable loaded time varying linear system. For this purpose, a state estimation with reduced order observer and adaptive-LQR (Linear–Quadratic Regulator) control structure was offered. Initially, to estimate the states of the system, a reduced-order observer was designed and used with LQR control method that is one of the optimal control techniques in the servo system with initial load. Subsequently, a Lyapunov-based adaptation mechanism was added to the LQR control to provide optimal control for varying loads as a new approach in design. Thus, it was aimed to eliminate the variable load effects and to increase the stability of the system. In order to demonstrate the effectiveness of the proposed method, a variable loaded rotary servo system was modelled as a time-varying linear system and used in simulations in Matlab-Simulink environment. Based on the simulation results and performance measurements, it was observed that the proposed method increases the system performance and stability by minimizing variable load effect.


Author(s):  
Yoram Halevi

Abstract A method of approximating the controllability gramian, observability gramian and the balancing transformation for lightly damped mechanical systems is presented, the approximation uses the special structure of the system and the fact that the damping is small to reduce the amount of computation considerably. Furthermore, one can avoid the calculation of the entire balancing transformation matrix and calculate only the parts that are required for order reduction. In cases where the reduced order is much smaller than the original that leads to another substantial reduction of computation effort.


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