Adaptive Predictor-Based Output Feedback Control for a Class of Unknown MIMO Linear Systems: Experimental Results

2014 ◽  
Author(s):  
Chuong Hoang Nguyen ◽  
Alexander Leonessa
Keyword(s):  
Feedback Control ◽  
Linear Systems ◽  
Output Feedback ◽  
Reference System ◽  
State Feedback Control ◽  
Experimental Results ◽  
Control Input ◽  
Test Bed ◽  
Full State ◽  
System Output

Experimental results are presented to validate a recently developed adaptive output feedback controller for a general class of unknown MIMO linear systems. The control approach relies on three components, a predictor, a reference model, and a controller. Specifically, since the predictor is designed to predict the system’s output for any admissible control input, controlling the uncertain system is reduced to controlling the predictor, which is a virtual system with known dynamics and full state available. Subsequently, a full state feedback control law is designed to control the predictor output to approach the reference system, while the reference system tracks the desired trajectory while accounting for the actuator amplitude and rate saturation constraints. Ultimately, the control objective of driving the actual system output to track the desired trajectories is achieved by showing that the system output, the predictor output, and the reference system trajectories all converge to each other. Theorems and the step-by-step implementation of the control strategy are presented. Finally, the control’s efficacy is illustrated by a real time implementation of the proposed algorithm on an actual helicopter test bed.

Adaptive Predictor-Based Output Feedback Control for a Class of Unknown MIMO Linear Systems

2014 ◽  
Author(s):  
Chuong Hoang Nguyen ◽  
Alexander Leonessa
Keyword(s):  
Feedback Control ◽  
Linear Systems ◽  
Output Feedback ◽  
Reference System ◽  
Reference Model ◽  
Output Feedback Control ◽  
State Feedback Control ◽  
Control Input ◽  
Actual System ◽  
System Output

In this paper, the problem of characterizing adaptive output feedback control laws for a general class of unknown MIMO linear systems is considered. Specifically, the presented control approach relies on three components, a predictor, a reference model, and a controller. The predictor is designed to predict the system’s output with arbitrary accuracy, for any admissible control input. Subsequently, a full state feedback control law is designed to control the predictor output to approach the reference system, while the reference system tracks the desired trajectory. Ultimately, the control objective of driving the actual system output to track the desired trajectories is achieved by showing that the system output, the predictor output, and the reference system trajectories all converge to each other.

Predictor-Based Adaptive Output Feedback Control: Application to Functional Electrical Stimulation of a Human Arm Model

2016 ◽  
Vol 138 (11) ◽  
Author(s):  
Chuong H. Nguyen ◽  
Alexander Leonessa
Keyword(s):  
Feedback Control ◽  
Linear Systems ◽  
Output Feedback ◽  
Reference System ◽  
Mimo Systems ◽  
Output Feedback Control ◽  
Control Law ◽  
Human Arm ◽  
System Output ◽  
Asme Paper

A simulation study to control the motion of a human arm using muscle excitations as inputs is presented to validate a recently developed adaptive output feedback controller for a class of unknown multi-input multi-output (MIMO) systems. The main contribution of this paper is to extend the results of Nguyen and Leonessa (2014, “Adaptive Predictor-Based Output Feedback Control for a Class of Unknown MIMO Linear Systems,” ASME Paper No. DSCC2014-6214; 2014, “Adaptive Predictor-Based Output Feedback Control for a Class of Unknown MIMO Linear Systems: Experimental Results,” ASME Paper No. DSCC2014-6217; and 2015, “Adaptive Predictor-Based Output Feedback Control for a Class of Unknown MIMO Systems: Experimental Results,” American Control Conference, pp. 3515–3521) by combining a recently developed fast adaptation technique and a new controller structure to derive a simple approach for a class of high relative degree uncertain systems. Specifically, the presented control approach relies on three components: a predictor, a reference model, and a controller. The predictor is designed to predict the systems output for any admissible control input. A full state feedback control law is then derived to control the predictor output to approach the reference system. The control law avoids the recursive step-by-step design of backstepping and remains simple regardless of the system relative degree. Ultimately, the control objective of driving the actual system output to track the desired trajectory is achieved by showing that the system output, the predictor output, and the reference system trajectories all converge to each other. Thelen and Millard musculotendon models (Thelen, D. G., 2003, “Adjustment of Muscle Mechanics Model Parameters to Simulate Dynamic Contractions in Older Adults,” ASME J. Biomech. Eng., 125(1), pp. 70–77; Millard, M, Uchida, T, Seth, A, and Delp, Scott L., 2013, “Flexing Computational Muscle: Modeling and Simulation of Musculotendon Dynamics,” ASME J. Biomech. Eng., 135(2), p. 021005) are used to validate the proposed controller fast tracking performance and robustness.

Feedback Linearizing Control of Surge in an Axial Compression System: Theory and Experimental Validation

1995 ◽  
Author(s):  
O. O. Badmus ◽  
S. Chowdhury ◽  
C. N. Nett
Keyword(s):  
Feedback Control ◽  
Closed Loop ◽  
Controller Design ◽  
Dynamic Pressure ◽  
Axial Compressor ◽  
State Feedback Control ◽  
Effective Length ◽  
Control Input ◽  
System Input ◽  
System Output

This paper presents experimental demonstration of surge stabilization in an axial compressor rig with a feedback linearizing controller. The controller design approach is model-based, and hence a nonlinear surge model for the facility is first validated. The surge model is a modification of the classic one-dimensional incompressible fluid surge model, with an effective length function incorporated, to account for the increased path-length of the fluid in the compressor due to the imparted tangential forces of the blade. This model, which adequately describes the observed surge dynamics both in terms of amplitude and frequency of oscillation, is then used to develop the feedback control law. The feedback linearizing control input implicitly linearizes the dynamics between the system input, throttle area parameter, and the system output, inlet dynamic pressure. A linear state feedback control input, implemented on the feedback linearized system thus ensures stabilization of the surge dynamics in the original nonlinear model. Finally, the nonlinear based observer is included in closed loop implementation to enhance the tracking of the system output, and also to minimize the adverse effect of measurement noise, thereby improving closed loop system performance.

Human Postural Feedback Response Described by Eigenvector

2006 ◽  
Vol 326-328 ◽  
pp. 739-742 ◽  
Author(s):  
Se Young Kim ◽  
Suk Yung Park
Keyword(s):  
Feedback Control ◽  
State Feedback ◽  
State Feedback Control ◽  
Joint Torque ◽  
Modal Control ◽  
Control Input ◽  
Postural Responses ◽  
Control Gain ◽  
Full State ◽  
Full State Feedback

Human postural responses appeared to have stereotyped modality, such as ankle mode, knee mode, and hip mode in response to various levels of postural challenges. We examined whether human postural control gain of full-state feedback could be decoupled along with the eigenvectors. To verify the model, postural responses subjected to fast backward perturbation were used. Upright posture was modeled as 3-segment inverted pendulum incorporated with linear feedback control, and joint torques were calculated using inverse dynamics. Postural modalities, such as ankle, knee and hip mode, were obtained from eigenvectors of biomechanics model. As oppose to the full-state feedback control, independent modal control assumes that modal control input is determined by the linear combinations of corresponding modality. We used linear regression to obtain and compare the feedback gains for both eigenvector control gain and full-state feedback. As a result, we found that both feedback gains of two control models that fit the joint torque data are reasonably closed each other especially at the joint angle feedback gains. This implies that the simple parameterization using eigenvectors may be used to correlate the feedback gains of full-state feedback control.

A Linear Matrix Inequality Approach to Output Feedback Control of Fractional-Order Unified Chaotic Systems With One Control Input

2016 ◽  
Vol 11 (5) ◽  
Author(s):  
Pitcha Khamsuwan ◽  
Suwat Kuntanapreeda
Keyword(s):  
Feedback Control ◽  
Fractional Order ◽  
Chaotic Systems ◽  
Direct Method ◽  
Output Feedback Control ◽  
State Feedback Control ◽  
Linear Matrix ◽  
Control Input ◽  
Unified Chaotic Systems ◽  
System Output

This paper focuses on stabilization of fractional-order unified chaotic systems. In contrast to existing methods in literature, the proposed method requires only the system output for feedback and uses only one control input. The controller consists of a state feedback control law and a dynamic estimator. Sufficient stability conditions are derived using a fractional-order extension of the Lyapunov direct method and a new lemma of the Caputo fractional derivative. The conditions are expressed in the form of linear matrix inequalities (LMIs). All the parameters of the controller can be simultaneously obtained by solving the LMIs. Numerical simulations are provided to illustrate the feasibility and effectiveness of the proposed method.

Extended state observer–based output feedback control for spacecraft pose tracking with control input saturation

2021 ◽  
pp. 095441002110177
Author(s):  
Kejie Gong ◽  
Ying Liao ◽  
Yafei Mei
Keyword(s):  
Feedback Control ◽  
Output Feedback ◽  
Finite Time ◽  
Output Feedback Control ◽  
State Observer ◽  
Extended State Observer ◽  
Control Input ◽  
Extended State ◽  
Pose Tracking ◽  
Control Scheme

This article proposed an extended state observer (ESO)–based output feedback control scheme for rigid spacecraft pose tracking without velocity feedback, which accounts for inertial uncertainties, external disturbances, and control input constraints. In this research, the 6-DOF tracking error dynamics is described by the exponential coordinates on SE(3). A novel continuous finite-time ESO is proposed to estimate the velocity information and the compound disturbance, and the estimations are utilized in the control law design. The ESO ensures a finite-time uniform ultimately bounded stability of the observation states, which is proved utilizing the homogeneity method. A non-singular finite-time terminal sliding mode controller based on super-twisting technology is proposed, which would drive spacecraft tracking the desired states. The other two observer-based controllers are also proposed for comparison. The superiorities of the proposed control scheme are demonstrated by theory analyses and numerical simulations.

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