Row-column sparse linear quadratic controller design via Bi-linear rank penalty technique and non-fragility notion

2017 ◽  
Author(s):  
MirSaleh Bahavarnia ◽  
Nader Motee
Keyword(s):  
Controller Design ◽  
Linear Quadratic ◽  
Linear Rank ◽  
Penalty Technique

scholarly journals Simulation of a Steam Injected Gas Turbine Plant Control System

1997 ◽  
Author(s):  
Shusheng Zang ◽  
Jaqiang Pan
Keyword(s):  
Gas Turbine ◽  
Flow Rate ◽  
Controller Design ◽  
Dynamic Performance ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Turbine Plant ◽  
Fuel Flow ◽  
Lqr Controller ◽  
Gas Turbine Plant

The design of a modern Linear Quadratic Regulator (LQR) is described for a test steam injected gas turbine (STIG) unit. The LQR controller is obtained by using the fuel flow rate and the injected steam flow rate as the output parameters. To meet the goal of the shaft speed control, a classical Proportional Differential (PD) controller is compared to the LQR controller design. The control performance of the dynamic response of the STIG plant in the case of rejection of load is evaluated. The results of the computer simulation show a remarkable improvement on the dynamic performance of the STIG unit.

Robust Controller Design for Active Suspension Systems of Road Vehicles

2017 ◽  
Author(s):  
Shenjin Zhu ◽  
Yuping He
Keyword(s):  
Controller Design ◽  
Operating Conditions ◽  
Ride Quality ◽  
Vehicle Model ◽  
Linear Quadratic ◽  
Robust Controller ◽  
Baseline Design ◽  
Vehicle Suspensions ◽  
Suspension Systems ◽  
Active Suspension Systems

The Linear Quadratic Gaussian (LQG) technique has been applied to the design of active vehicle suspensions (AVSs) for improving ride quality and handling performance. LQG-based AVSs have achieved good performance if an accurate vehicle model is available. However, these AVSs exhibit poor robustness when the vehicle model is not accurate and vehicle operating conditions vary. The H∞ control theory, rooted in the LQG technique, specifically targets on robustness issues on models with parametric uncertainties and un-modelled dynamics. In this research, an AVS is designed using the H∞ loop-shaping control, design optimization, and parallel computing techniques. The resulting AVS is compared against the baseline design through numerical simulations.

scholarly journals Cross Regulation Reduced Optimal Multivariable Controller Design for Single Inductor DC-DC Converters

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 477 ◽  
Author(s):  
S. Augusti Lindiya ◽  
N. Subashini ◽  
K. Vijayarekha
Keyword(s):  
Pid Controller ◽  
Controller Design ◽  
Multiple Input Multiple Output ◽  
Linear Quadratic Regulator ◽  
Prototype Model ◽  
Linear Quadratic ◽  
Load Current ◽  
Practical Applications ◽  
Input Multiple Output ◽  
Single Input

Single Inductor (SI) converters with the advantage of using one inductor for any number of inputs/outputs find wide applications in portable electronic gadgets and electrical vehicles. SI converters can be used in Single Input Multiple Output (SIMO) and Multiple Input Multiple Output (MIMO) configurations but they need controllers to achieve good transient and steady state responses, to improve the stability against load and line disturbances and to reduce cross regulation. Cross regulation is the change in an output voltage due to change in the load current at another output and it is an added constraint in SI converters. In this paper, Single Input Dual Output (SIDO) and Dual Input Dual Output (DIDO) converters with applications capable of handling high load current working in Continuous Conduction Mode (CCM) of operation are taken under study. Conventional multivariable PID and optimal Linear Quadratic Regulator (LQR) controllers are developed and their performances are compared for the above configurations to meet the desired objectives. Generalized mathematical models for SIMO and MIMO are developed and a Genetic Algorithm (GA) is used to find the parameters of a multivariable PID controller and the weighting matrices of optimal LQR where the objective function includes cross regulation as a constraint. The simulated responses reveal that LQR controller performs well for both the systems over multivariable PID controller and they are validated by hardware prototype model with the help of DT9834® Data Acquisition Module (DAQ). The methodologies used here generate a fresh dimension for the case of such converters in practical applications.

Backstepping Controller Design for a 5 DOF Spherical Inverted Pendulum

2019 ◽  
Vol 41 ◽  
pp. 37-50 ◽  
Author(s):  
Soukaina Krafes ◽  
Zakaria Chalh ◽  
Abdelmjid Saka
Keyword(s):  
Degrees Of Freedom ◽  
Inverted Pendulum ◽  
Controller Design ◽  
Linear Quadratic Regulator ◽  
Performance Comparison ◽  
Virtual Reality Environment ◽  
Linear Quadratic ◽  
Control Scheme ◽  
Linearized System ◽  
Backstepping Controller

This paper presents a Backstepping controller for five degrees of freedom Spherical Inverted Pendulum. Since the system is nonlinear, unstable, underactuated and MIMO and has a nonsquare form, the classic control design cannot be applied to control it. In order to remedy this problem, we propose in this paper a new method based on hierarchical steps of the Backstepping controller taking into a count the nonlinearities that cannot be neglected. Furthermore, a Linear Quadratic Regulator controller and LQR + PID based on the linearized system model are also designed for performance comparison. Finally, a simulation study is carried out to prove the effectiveness of proposed control scheme and is validated using the virtual reality environment that proves the performance of the Backstepping controller over the linear ones where it brings the pendulum from any initial condition in the upper hemisphere while the base is brought to the origin of the coordinates.

Augmented-Stability Controller Design for a UAV’s Longitudinal Motion

2011 ◽  
Vol 63-64 ◽  
pp. 533-536
Author(s):  
Xiao Jun Xing ◽  
Jian Guo Yan
Keyword(s):  
Dynamic Characteristics ◽  
Controller Design ◽  
Damping Ratio ◽  
Linear Quadratic Regulator ◽  
Longitudinal Motion ◽  
Linear Quadratic ◽  
Short Period ◽  
Quality Specifications ◽  
Simulation Results ◽  
And Control

With the purpose of overcoming the defect that unmanned air vehicles (UAVs) are easily disturbed by air current and tend to be unstable, an augmented-stability controller was developed for a certain UAV’s longitudinal motion. According to requirements of short-period damping ratio and control anticipation parameter (CAP) in flight quality specifications of GJB185-86 and C*, linear quadratic regulator (LQR) theory was used in the augmented-stability controller’s design. The simulation results show that the augmented-stability controller not only improves the UAV’s stability and dynamic characteristics but also enhances the UAV’s robustness.

Novel Method on Using Evolutionary Algorithms for PD Optimal Tuning

2011 ◽  
Vol 110-116 ◽  
pp. 4977-4984 ◽  
Author(s):  
R.A. Khoshrooz ◽  
M.A.D. Vahid ◽  
M. Mirshams ◽  
M.R. Homaeinezhad ◽  
A.H. Ahadi
Keyword(s):  
Attitude Control ◽  
Controller Design ◽  
Linear Quadratic Regulator ◽  
Initial Guess ◽  
Pd Controller ◽  
Linear Quadratic ◽  
Optimal Tuning ◽  
Heavy Burden ◽  
Novel Method

This paper presents a method to solve the Evolutionary Algorithm (EA) problems for optimal tuning of the Proportional-Deferential (PD) controller parameters. The major efficiency of the proposed method is the Genetic Algorithm (GA) stuck avoidance as well an appropriate estimation for GA lower and upper bounds. Also by this method for the Particle Swarm Optimization (PSO) methodology the initial choice of the controller parameters can be fulfilled to achieve the acceptable performance accuracies. For both GA and PSO methods, the Linear Quadratic Regulator (LQR) obtained trend is used as the reference for the determination of the aforementioned bounds and initial guess. The presented algorithm was applied to regulate a PD controller for the attitude control of a virtual satellite and also with Hardware-in-the-loop (HIL) reaction wheels. Heavy burden trying and error was eliminated from the PD controller design which can be mentioned as the important merit of the presented study.

Stability Robustness of LQ and LQG Active Suspensions

1994 ◽  
Vol 116 (1) ◽  
pp. 123-131 ◽  
Author(s):  
A. G. Ulsoy ◽  
D. Hrovat ◽  
T. Tseng
Keyword(s):  
Controller Design ◽  
Active Suspension ◽  
Point Of View ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Active Suspensions ◽  
Quarter Car Model ◽  
Stability Robustness ◽  
Trade Offs ◽  
Two Degree Of Freedom

A two-degree-of-freedom quarter-car model is used as the basis for linear quadratic (LQ) and linear quadratic Gaussian (LQG) controller design for an active suspension. The LQ controller results in the best rms performance trade-offs (as defined by the performance index) between ride, handling and packaging requirements. In practice, however, all suspension states are not directly measured, and a Kalman filter can be introduced for state estimation to yield an LQG controller. This paper (i) quantifies the rms performance losses for LQG control as compared to LQ control, and (ii) compares the LQ and LQG active suspension designs from the point of view of stability robustness. The robustness of the LQ active suspensions is not necessarily good, and depends strongly on the design of a backup passive suspension in parallel with the active one. The robustness properties of the LQG active suspension controller are also investigated for several distinct measurement sets.

scholarly journals Attitude and Altitude Controller Design for Quad-Rotor Type MAVs

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Wei Wang ◽  
Hao Ma ◽  
Min Xia ◽  
Liguo Weng ◽  
Xuefei Ye
Keyword(s):  
Attitude Control ◽  
Controller Design ◽  
Sliding Mode ◽  
Micro Air Vehicles ◽  
Triaxial Accelerometer ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Constant Altitude ◽  
The Military ◽  
Rotor Type

Micro air vehicles (MAVs) have a wide application such as the military reconnaissance, meteorological survey, environmental monitoring, and other aspects. In this paper, attitude and altitude control for Quad-Rotor type MAVs is discussed and analyzed. For the attitude control, a new method by using three gyroscopes and one triaxial accelerometer is proposed to estimate the attitude angle information. Then with the approximate linear model obtained by system identification, Model Reference Sliding Mode Control (MRSMC) technique is applied to enhance the robustness. In consideration of the relatively constant altitude model, a Linear Quadratic Gaussian (LQG) controller is adopted. The outdoor experimental results demonstrate the superior stability and robustness of the controllers.

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