A Control Scheme for an Opposed Recumbent Tandem Human-Powered Bicycle

1996 ◽  
Vol 12 (4) ◽  
pp. 480-492
Author(s):  
Scott O. Cloyd ◽  
Mont Hubbard ◽  
LeRoy W. Alaways
Keyword(s):  
Feedback Control ◽  
Linear Quadratic Regulator ◽  
Optimal Feedback Control ◽  
State Variables ◽  
Linear Quadratic ◽  
Lateral Deviation ◽  
Control Scheme ◽  
Control Schemes ◽  
Lean Angle ◽  
Human Powered

Feedback control of a human-powered single-track bicycle is investigated through the use of a linearized dynamical model in order to develop feedback gains that can be implemented by a human pilot in an actual vehicle. The object of the control scheme is to satisfy two goals: balance and tracking. The pilot should be able not only to keep the vehicle upright but also to direct the forward motion as desired. The two control inputs, steering angle and rider lean angle, are assumed to be determined by the rider as a product of feedback gains and “measured” values of the state variables: vehicle lean, lateral deviation from the desired trajectory, and their derivatives. Feedback gains are determined through linear quadratic regulator theory. This results in two control schemes, a “full” optimal feedback control and a less complicated technique that is more likely to be usable by an inexperienced pilot. Theoretical optimally controlled trajectories are compared with experimental trajectories in a lane change maneuver.

scholarly journals Decentralized Control for Scalable Quadcopter Formations

2016 ◽  
Vol 2016 ◽  
pp. 1-10
Author(s):  
Qasim Ali ◽  
Sergio Montenegro
Keyword(s):  
Position Control ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Time Duration ◽  
Control Effort ◽  
Ground Station ◽  
Model Following ◽  
Control Scheme ◽  
Control Schemes ◽  
And Control

An innovative framework has been developed for teamwork of two quadcopter formations, each having its specified formation geometry, assigned task, and matching control scheme. Position control for quadcopters in one of the formations has been implemented through a Linear Quadratic Regulator Proportional Integral (LQR PI) control scheme based on explicit model following scheme. Quadcopters in the other formation are controlled through LQR PI servomechanism control scheme. These two control schemes are compared in terms of their performance and control effort. Both formations are commanded by respective ground stations through virtual leaders. Quadcopters in formations are able to track desired trajectories as well as hovering at desired points for selected time duration. In case of communication loss between ground station and any of the quadcopters, the neighboring quadcopter provides the command data, received from the ground station, to the affected unit. Proposed control schemes have been validated through extensive simulations using MATLAB®/Simulink® that provided favorable results.

Two fuzzy control schemes for Lorenz-Stenflo chaotic system

2011 ◽  
Vol 18 (11) ◽  
pp. 1675-1682 ◽  
Author(s):  
Huaqing Li ◽  
Xiaofeng Liao ◽  
Xinyu Lei
Keyword(s):  
Feedback Control ◽  
Fuzzy Control ◽  
Equilibrium Point ◽  
Chaotic System ◽  
Control Method ◽  
Adaptive Fuzzy Control ◽  
State Variables ◽  
Control Scheme ◽  
Control Schemes ◽  
Feedback Control Method

In this paper, two effective fuzzy control schemes, i.e., fuzzy feedback control method and adaptive fuzzy control method are introduced to suppress the state variables of the Lorenz-Stenflo chaotic system (LSCS) to its equilibrium point. For the first fuzzy control scheme, with the abundant modeling capability of the T-S fuzzy model, the LSCS can be decomposed into some local linear systems, which makes it very convenient to use the fuzzy feedback control method to analyze it. Based on the Lyapunov stability theorem, a criterion is also derived to guarantee the controlled LSCS is robust stable at the equilibrium point, even if there exist external perturbations. For the second fuzzy control scheme, fuzzy logic systems areexploited to approximate the nonlinear functions. Moreover, an adaptive technique is employed to construct an effective fuzzy controller, which can drive all state variables into a rather small neighborhood of its equilibrium point. By choosing a group of suitable parameters, the controlled system can approach the equilibrium point with high precision. Two numerical simulations are presented to demonstrate the effectiveness and feasibility of the two fuzzy control schemes.

scholarly journals Suboptimal Regulation of a Class of Bilinear Interconnected Systems with Finite-Time Sliding Planning Horizons

2008 ◽  
Vol 2008 ◽  
pp. 1-26 ◽  
Author(s):  
M. de la Sen ◽  
Aitor J. Garrido ◽  
J. C. Soto ◽  
O. Barambones ◽  
I. Garrido
Keyword(s):  
Control Law ◽  
State Variables ◽  
Linear Quadratic ◽  
Equivalent Representation ◽  
Quadratic Performance Index ◽  
Matrix Sequence ◽  
Control Scheme ◽  
Quadratic Performance ◽  
System Equations ◽  
Riccati Matrix

This paper focuses on the suboptimization of a class of multivariable discrete-time bilinear systems consisting of interconnected bilinear subsystems with respect to a linear quadratic optimal regulation criterion which involves the use of state weighting terms only. Conditions which ensure the controllability of the overall system are given as a previous requirement for optimization. Three transformations of variables are made on the system equations in order to implement the scheme on an equivalent linear system. This leads to an equivalent representation of the used quadratic performance index that involves the appearance of quadratic weighting terms related to both transformed input and state variables. In this way, a Riccati-matrix sequence, allowing the synthesis of a standard feedback control law, is obtained. Finally, the proposed control scheme is tested on realistic examples.

scholarly journals DYNAMICS BASED CONTROL OF A SKID STEERING MOBILE ROBOT

2016 ◽  
Vol 9 (2) ◽  
pp. 70 ◽  
Author(s):  
Osama Elshazly ◽  
Hossam Abbas ◽  
Zakarya Zyada
Keyword(s):  
Mobile Robot ◽  
Inverse Dynamics ◽  
Linear Quadratic Regulator ◽  
Nonlinear Controller ◽  
Linear Quadratic ◽  
Reduced Order ◽  
Lqr Control ◽  
Control Schemes ◽  
Skid Steering ◽  
Drive Model

In this paper, development of a reduced order, augmented dynamics-drive model that combines both the dynamics and drive subsystems of the skid steering mobile robot (SSMR) is presented. A Linear Quadratic Regulator (LQR) control algorithm with feed-forward compensation of the disturbances part included in the reduced order augmented dynamics-drive model is designed. The proposed controller has many advantages such as its simplicity in terms of design and implementation in comparison with complex nonlinear control schemes that are usually designed for this system. Moreover, the good performance is also provided by the controller for the SSMR comparable with a nonlinear controller based on the inverse dynamics which depends on the availability of an accurate model describing the system. Simulation results illustrate the effectiveness and enhancement provided by the proposed controller.

Mixed Strategy Global Sub-Optimal Feedback Control for Chaotic Systems

1997 ◽  
Vol 07 (03) ◽  
pp. 607-623 ◽  
Author(s):  
H. W. J. Lee ◽  
M. Paskota ◽  
K. L. Teo
Keyword(s):  
Feedback Control ◽  
State Space ◽  
Chaotic Systems ◽  
Mixed Strategy ◽  
The State ◽  
Optimal Feedback Control ◽  
Target Region ◽  
Optimal Feedback ◽  
Control Scheme

How to perform targeting of chaotic systems in a global sense is an important question. In this paper, we address this problem by introducing a mixed strategy global sub-optimal feedback control scheme. The idea is to partition the state space into 2 parts, namely, the target region and its complement. The proposed controller will take different forms depending on which partition of the state space the system is in. Simulations are also provided to illustrate the proposed scheme.

FULL-AND REDUCED- ORDER COMPENSATOR FOR INNOSAT ATTITUDE CONTROL

2015 ◽  
Vol 76 (12) ◽  
Author(s):  
Fadzilah Hashim ◽  
Mohd Yusoff Mashor ◽  
Siti Maryam Sharun
Keyword(s):  
State Space ◽  
Attitude Control ◽  
Space Form ◽  
Transfer Functions ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Reduced Order ◽  
Lqr Control ◽  
Best Value ◽  
Control Scheme

This paper presents a study on the estimator based on Linear Quadratic Regulator (LQR) control scheme for Innovative Satellite (InnoSAT). By using LQR control scheme, the controller and the estimator has been derived for state space form in all three axes to stabilize the system’s performance. This study starts by converting the transfer functions of attitude control into state space form.  Then, the step continues by finding the best value of weighting matrices of LQR in order to obtain the best value of controller gain, K. After that, the best value of L is obtained for the estimator gain. The value of K and L is combined in forming full order compensator and in the same time the reduced order compensator is also formed. Lastly, the performance of full order compensator is compared to reduced order compensator. From the simulation, results indicate that both types of estimators have presented good stability and tracking performance. However, reduced order estimator has simpler equation and faster convergence to zero than the full order estimator. This property is very important in developing a satellite attitude control for real-time implementation.

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.

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