A Stochastic Regulator for Integrated Communication and Control Systems: Part II—Numerical Analysis and Simulation

1991 ◽  
Vol 113 (4) ◽  
pp. 612-619 ◽  
Author(s):  
Luen-Woei Liou ◽  
Asok Ray
Keyword(s):  
Control Systems ◽  
Numerical Procedure ◽  
Linear Quadratic Regulator ◽  
State Feedback Control ◽  
Control Law ◽  
Linear Quadratic ◽  
Simulation Experiments ◽  
Integrated Communication ◽  
And Control ◽  
Future Work

A state feedback control law has been derived in Part I [1] of this two-part paper on the basis of an augmented plant model [2, 3, 4] that accounts for the randomly varying delays induced by the network in Integrated Communication and Control Systems (ICCS). The control algorithm was formulated as a linear quadratic regulator problem and then solved using the principle of dynamic programming and optimality. This paper, which is the second of two parts, presents (i) a numerical procedure for synthesizing the control parameters and (ii) results of simulation experiments for verification of the above control law using the flight dynamic model of an advanced aircraft. This two-part paper is concluded with recommendations for future work.

A Stochastic Regulator for Integrated Communication and Control Systems: Part I—Formulation of Control Law

1991 ◽  
Vol 113 (4) ◽  
pp. 604-611 ◽  
Author(s):  
Luen-Woei Liou ◽  
Asok Ray
Keyword(s):  
Performance Evaluation ◽  
Control Systems ◽  
Dynamic Performance ◽  
State Feedback Control ◽  
Control Law ◽  
Spatially Distributed ◽  
Integrated Communication ◽  
Finite Time Horizon ◽  
And Performance ◽  
And Control

Integrated Communication and Control Systems (ICCS), recently introduced and analyzed in a series of papers [1–7], are applicable to complex dynamical processes like advanced aircraft, spacecraft, automotive, and manufacturing processes. Time-division-multiplexed computer networks are employed in ICCS for exchange of information between spatially distributed plant components as well as for coordination of the diverse control and decision-making functions. Unfortunately, an ICCS network introduces randomly varying, distributed delays within the feedback loops in addition to the digital sampling and data processing delays. These network-induced delays degrade the system dynamic performance, and are a source of potential instability. This two-part paper presents the synthesis and performance evaluation of a stochastic optimal control law for ICCS. In this paper, which is the first of two parts, a state feedback control law for ICCS has been formulated by using the dynamic programming and optimality principle on a finite-time horizon. The control law is derived on the basis of a stochastic model of the plant which is augmented in state space to take into account the effects of randomly varying delays in the feedback loop. The second part [8] presents numerical analysis of the control law and its performance evaluation by simulation of the flight dynamic model of an advanced aircraft.

scholarly journals Optimal Design of Fault-Tolerant Controller for an Electric Power Steering System with Sensor Failures Using Genetic Algorithm

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xue Liu ◽  
Hui Pang ◽  
Yuting Shang ◽  
Wen Wu
Keyword(s):  
Genetic Algorithm ◽  
Electric Power ◽  
Fault Tolerant ◽  
Linear Quadratic Regulator ◽  
State Feedback Control ◽  
Control Law ◽  
Linear Quadratic ◽  
Electric Power Steering ◽  
Sensor Failures ◽  
Power Steering

This paper focuses on the fault-tolerant control (FTC) problem for an electric power steering (EPS) system subjected to stochastic sensor failures, and a novel fault-tolerant controller is proposed based on the genetic algorithm (GA). A mathematical model of the EPS system with sensor failures is first established, and the state feedback control law is solved by using linear quadratic regulator techniques to stabilize the closed-loop control system. Then, the dynamic response errors of the EPS system with and without sensor faults are chosen as the optimization objective function. Furthermore, the appropriate weighting matrices are evaluated to obtain the optimal fault control law by using GA. Finally, simulation results are presented to illustrate the effectiveness of the proposed control strategy.

scholarly journals Mathematical Modelling and Control of a Two-Wheeled PUMA-LikeVehicle

2016 ◽  
Vol 6 (2) ◽  
pp. 11 ◽  
Author(s):  
Khaled M Goher
Keyword(s):  
Mathematical Modelling ◽  
Sliding Mode ◽  
Impact Load ◽  
State Space Model ◽  
Linear Quadratic Regulator ◽  
The Body ◽  
Pole Placement ◽  
General Motors ◽  
Linear Quadratic ◽  
And Control

<p class="1Body">This paper presents mathematical modelling and control of a two-wheeled single-seat vehicle. The design of the vehicle is inspired by the Personal Urban Mobility and Accessibility (PUMA) vehicle developed by General Motors® in collaboration with Segway®. The body of the vehicle is designed to have two main parts. The vehicle is activated using three motors; a linear motor to activate the upper part in a sliding mode and two DC motors activating the vehicle while moving forward/backward and/or manoeuvring. Two stages proportional-integral-derivative (PID) control schemes are designed and implemented on the system models. The state space model of the vehicle is derived from the linearized equations. Controller based on the Linear Quadratic Regulator (LQR) and the pole placement techniques are developed and implemented. Further investigation of the robustness of the developed LQR and the pole placement techniques is emphasized through various experiments using an applied impact load on the vehicle.</p>

Modeling and Control of a Complex Interacting Process

2011 ◽  
Vol 403-408 ◽  
pp. 3758-3762
Author(s):  
Subhajit Patra ◽  
Prabirkumar Saha
Keyword(s):  
Storage System ◽  
Linear Quadratic Regulator ◽  
Model Parameters ◽  
Linear Quadratic ◽  
Modeling And Control ◽  
Dynamic Matrix ◽  
Liquid Storage ◽  
Efficient Control ◽  
And Control

In this paper, two efficient control algorithms are discussed viz., Linear Quadratic Regulator (LQR) and Dynamic Matrix Controller (DMC) and their applicability has been demonstrated through case study with a complex interacting process viz., a laboratory based four tank liquid storage system. The process has Two Input Two Output (TITO) structure and is available for experimental study. A mathematical model of the process has been developed using first principles. Model parameters have been estimated through the experimentation results. The performance of the controllers (LQR and DMC) has been compared to that of industrially more accepted PID controller.

Performance Analysis of Integrated Communication and Control System Networks

1990 ◽  
Vol 112 (3) ◽  
pp. 365-371 ◽  
Author(s):  
Y. Halevi ◽  
A. Ray
Keyword(s):  
Control System ◽  
Statistical Analysis ◽  
Performance Analysis ◽  
Control Systems ◽  
Manufacturing Plants ◽  
Asynchronous Time Division Multiplexing ◽  
Processing Plants ◽  
Integrated Communication ◽  
Time Division ◽  
And Control

This paper presents statistical analysis of delays in Integrated Communication and Control System (ICCS) networks [1–4] that are based on asynchronous time-division multiplexing. The models are obtained in closed form for analyzing control systems with randomly varying delays. The results of this research are applicable to ICCS design for complex dynamical processes like advanced aircraft and spacecraft, autonomous manufacturing plants, and chemical and processing plants.

Acoustic Control Modeling of Conical Bores With Actuating Boundary Conditions

2001 ◽  
Author(s):  
Kevin M. Farinholt ◽  
Donald J. Leo
Keyword(s):  
Boundary Conditions ◽  
Driving Forces ◽  
State Space Model ◽  
Linear Quadratic Regulator ◽  
Mode Shapes ◽  
Linear Quadratic ◽  
Acoustic Control ◽  
Average Control ◽  
The One ◽  
And Control

Abstract An investigation of the natural frequencies and mode shapes associated with sealed conical bores having actuating boundary conditions is presented. Beginning with the one dimensional wave equation for spherically expanding waves, modal characteristics are developed as functions of cone geometry and actuator parameters. This paper presents both analytical and experimental comparisons for the purpose of validating model and development techniques. An investigation of the orthogonality and adjointness of the solution is presented. A discussion of incorporating driving forces in the system model for the purpose of coupling control actuators with internal acoustics is also included. Including these driving forces, a state space model of the system is developed for the purpose of applying modern feedback control. This paper concludes with a study on applying Linear Quadratic Regulator techniques to this system, relating tradeoffs between spatially averaged pressure and control voltages. The results of our simulations indicate that pressure reductions of 30% are attainable with average control voltages of 14.4 volts, given an example geometry.

scholarly journals System design for inverted pendulum using LQR control via IoT

2020 ◽  
Vol 11 ◽  
pp. 12
Author(s):  
Dechrit Maneetham ◽  
Petrus Sutyasadi
Keyword(s):  
Inverted Pendulum ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Lqr Control ◽  
Lqr Controller ◽  
Model Tuning ◽  
And Performance ◽  
Performance Results ◽  
And Control

This research proposes control method to balance and stabilize an inverted pendulum. A robust control was analyzed and adjusted to the model output with real time feedback. The feedback was obtained using state space equation of the feedback controller. A linear quadratic regulator (LQR) model tuning and control was applied to the inverted pendulum using internet of things (IoT). The system's conditions and performance could be monitored and controlled via personal computer (PC) and mobile phone. Finally, the inverted pendulum was able to be controlled using the LQR controller and the IoT communication developed will monitor to check the all conditions and performance results as well as help the inverted pendulum improved various operations of IoT control is discussed.

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