Linear Quadratic Regulator Controller Design

2015 ◽  
pp. 171-200 ◽  
Author(s):  
Chingiz Hajiyev ◽  
Halil Ersin Soken ◽  
Sıtkı Yenal Vural
Keyword(s):  
Controller Design ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic

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.

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.

scholarly journals Actuator Placement for Active Surge Control in a Multi-Stage Axial Compressor

1996 ◽  
Author(s):  
M. Montazeri-Gh. ◽  
D. J. Allerton ◽  
R. L. Elder
Keyword(s):  
Cost Function ◽  
Mass Flow ◽  
Controller Design ◽  
Axial Compressor ◽  
Minimum Cost ◽  
Linear Quadratic Regulator ◽  
Algebraic Riccati Equation ◽  
Linear Quadratic ◽  
Non Linear ◽  
Actuator Placement

This paper describes an actuator placement methodology for the active control of purely one-dimensional instabilities of a seven-stage axial compressor using an air bleeding strategy. In this theoretical study, using stage-by-stage non-linear modelling based on the conservation equations of mass, momentum, and energy, a scheduling LQR (Linear Quadratic Regulator) controller is designed for several actuator locations in a compressor from the first stage to the plenum. In this controller design, the LQR weighting matrices are selected so that the associated cost function includes only air bleeding mass flow leading to the minimisation of the air bleed. The LQR cost function represents a measure of the consumption of air bleeding and can be calculated analytically using the solution of an Algebraic Riccati Equation. From analysis of the cost at different compressor stages, the location of an air bleeding actuator is selected at the stage with the minimum cost. Finally, using an ACSL simulation program, the scheduling controller has been integrated with a non-linear. stage-by-stage model and the time response of the air bleeding mass flow at different locations has been obtained to confirm the results from the analytical approach. Results are presented to show actively stabilised compressor flow beyond the surge point where the air bleed is minimised. These results also indicate the preferred location of the actuator at the compressor downstream stages for both low and high compressor speeds.

scholarly journals The Design of Optimal PID Control Method for Quadcopter Movement Control

2018 ◽  
Vol 2 (1) ◽  
pp. 1 ◽  
Author(s):  
Hanum Arrosida ◽  
Mohammad Erik Echsony
Keyword(s):  
Pid Control ◽  
Control Method ◽  
Controller Design ◽  
Minimum Energy ◽  
Linear Quadratic Regulator ◽  
Research Field ◽  
Unmanned Aircraft ◽  
Control Methods ◽  
Linear Quadratic ◽  
Optimal Pid Control

Nowadays, quadcopter motion control has become a popular research topic because of its versatile ability as an unmanned aircraft can be used to alleviate human labor and also be able to reach dangerous areas or areas which is unreachable to humans. On the other hand, the Optimal PID control method, which incorporates PID and Linear Quadratic Regulator (LQR) control methods, has also been widely used in industry and research field because it has advantages that are easy to operate, easy design, and a good level of precision. In the PID control method, the main problem to be solved is the accuracy of the gain value Kp, Ki, and Kd because the inappropriateness of those value will result in an imprecise control action. Based on these problems and referring to the previous study, the optimal PID control method was developed by using PID controller structure with tuning gain parameter of PID through Linear Quadratic Regulator (LQR) method. Through the integration of these two control methods, the optimum solutions can be obtained: easier controller design process for quadcopter control when crossing the determined trajectories, steady state error values less than 5% and a stable quadcopter movement with roll and pitch angle stabilization at position 0 radians with minimum energy function.

scholarly journals System Identification and LQR Controller Design with Incomplete State Observation for Aircraft Trajectory Tracking

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5354
Author(s):  
Piotr Lichota ◽  
Franciszek Dul ◽  
Andrzej Karbowski
Keyword(s):  
Simulation Model ◽  
Trajectory Tracking ◽  
Controller Design ◽  
Linear Quadratic Regulator ◽  
Atmospheric Conditions ◽  
Nonlinear Transport ◽  
Linear Quadratic ◽  
Likelihood Principle ◽  
Tracking Errors ◽  
Lqr Controller

This paper presents a controller design process for an aircraft tracking problem when not all states are available. In the study, a nonlinear-transport aircraft simulation model was used and identified through Maximum Likelihood Principle and Extended Kalman Filter. The obtained mathematical model was used to design a Linear–Quadratic Regulator (LQR) with optimal weighting matrices when not all states are measured. The nonlinear aircraft simulation model with LQR controller tracking abilities were analyzed for multiple experiments with various noise levels. It was shown that the designed controller is robust and allows for accurate trajectory tracking. It was found that, in ideal atmospheric conditions, the tracking errors are small, even for unmeasured variables. In wind presence, the tracking errors were proportional to the wind velocity and acceptable for small and moderate disturbances. When turbulence was present in the experiment, state variable oscillations occurred that were proportional to the turbulence intensity and acceptable for small and moderate disturbances.

scholarly journals LPV-Based Controller Design of a Floating Piston Pneumatic Actuator

Actuators ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 98
Author(s):  
Ádám Szabó ◽  
Tamás Bécsi ◽  
Szilárd Aradi ◽  
Péter Gáspár
Keyword(s):  
High Speed ◽  
Controller Design ◽  
Linear Quadratic Regulator ◽  
Pneumatic Actuator ◽  
Pd Controller ◽  
Linear Parameter ◽  
Linear Quadratic ◽  
Minimum Order ◽  
Linear Parameter Varying ◽  
Parameter Varying

The paper presents the modeling and control design of a floating piston pneumatic gearbox actuator using a grid-based Linear Parameter Varying approach. First, the nonlinear model of the pneumatic actuator is presented, then it is transformed into a 6th order Linear Parameter Varying representation with endogenous scheduling parameters. The model is simplified based on empirical considerations to solve the controller synthesis and allow fast controller tuning. The developed Linear Parameter Varying controller is tested in simulations. Moreover, using a balanced truncation-model order reduction method, the minimum order of the controller is determined, which can provide acceptable performance. The simplified controller is implemented in an embedded environment and validated against the real target. Then, the validation results are compared with a gain-scheduled PD controller and a Linear Quadratic Regulator. The results show that by taking the time-varying nature of the scheduling parameters into account, the Linear Parameter Varying controller surpasses the Linear Quadratic Regulator, which cannot handle the high-speed transients around Neutral. Furthermore, the PD controller performs slightly better in two of the four test cases, although the Linear Parameter Varying controller has a higher level of fault tolerance.

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