An Observer-Free Output Feedback Cooperative Control Architecture for Multivehicle Systems

2017 ◽  
Author(s):  
Ali Albattat ◽  
Tansel Yucelen ◽  
Benjamin C. Gruenwald ◽  
S. Jagannathan
Keyword(s):  
Output Feedback ◽  
Cooperative Control ◽  
Output Feedback Control ◽  
Control Architecture ◽  
Control Law ◽  
Containment Problem ◽  
Theoretical Contribution ◽  
State Space Realization ◽  
Space Realization ◽  
Multivehicle Systems

The contribution of this paper is a new, observer-free output feedback cooperative control architecture for continuous-time, minimum phase, and high-order multivehicle systems in the context of a containment problem (i.e., outputs of the follower vehicles convergence to the convex hull spanned by those of the leader vehicles). The proposed architecture is predicated on a nonminimal state-space realization that generates an expanded set of states only using the filtered input and filtered output and their derivatives for each follower vehicle, without the need for designing an observer for each vehicle. Specifically, the proposed observer-free output feedback control law consists of a vehicle-level controller and a local cooperative controller for each vehicle, where the former addresses internal stability of vehicles and the latter addresses the containment problem. Two illustrative numerical examples complement the proposed theoretical contribution.

Barrier Lyapunov function-based adaptive output feedback failure compensation for a class of non-linear systems with unknown dead-zone non-linearity

2016 ◽  
Vol 39 (8) ◽  
pp. 1169-1181 ◽  
Author(s):  
Yuefei Wu ◽  
Jianyong Yao
Keyword(s):  
Lyapunov Function ◽  
Output Feedback ◽  
Dead Zone ◽  
Output Feedback Control ◽  
Control Law ◽  
Unknown Input ◽  
Barrier Lyapunov Function ◽  
Non Linear ◽  
Bounded Disturbances ◽  
Non Linear Systems

In this paper, an adaptive robust output feedback control approach is proposed for a class of uncertain non-linear systems with unknown input dead-zone non-linearity, unknown failures and unknown bounded disturbances. By constructing the dead-zone inverse and applying the backstepping recursive design technique, a robust adaptive backstepping controller is proposed, in which adaptive control law is synthesized to handle parametric uncertainties and a novel robust control law to attenuate disturbances. The robust output feedback control law is developed by integrating a switching function σ algorithm at each step of the backstepping design procedure. In addition, K-filters are designed to estimate the unmeasured states and neural networks are employed to approximate the unknown non-linear functions. By ensuring boundedness of the barrier Lyapunov function, the major feature of the proposed controller is that it can theoretically guarantee asymptotic output tracking performance, in spite of the presence of unknown input dead-zone non-linearity, various actuator failures and unknown bounded disturbances via Lyapunov stability analysis. The effectiveness of the proposed approach is illustrated by the simulation examples.

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.

scholarly journals Networked Output Feedback Control for a Class of Uncertain Nonlinear Time-Delay Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Hongyan Chu ◽  
Yan Wang ◽  
Weiling Li
Keyword(s):  
Time Delay ◽  
Output Feedback ◽  
Output Feedback Control ◽  
Delay Systems ◽  
Control Law ◽  
Sampled Data ◽  
Stabilization Problem ◽  
Linear Growth Condition ◽  
Data Output ◽  
Uncertain Time

This paper studies the global stabilization problem for a class of uncertain time-delay nonlinear systems by designing a sampled-data output feedback controller via network. Under a lower triangular linear growth condition, when only the output is measurable, a sampled-data output feedback network controller, whose observer and control law are both linear, is constructed to solve the stabilization problem. Using a feedback domination design approach which substantially differs from the separation principle, we explicitly construct a Lyapunov–Krasovskill functional to prove the global asymptotic stability with the help of inductive proof method. The control law is discrete-time and linear, hence simulation examples be easily implemented with computers to show the effectiveness of our proposed method.

Adaptive Rejection of Unmatched General Periodic Disturbances by Dynamic Output Feedback

2013 ◽  
Vol 710 ◽  
pp. 491-495
Author(s):  
Peng Nian Chen
Keyword(s):  
Output Feedback ◽  
Closed Loop ◽  
Output Feedback Control ◽  
Control Law ◽  
Dynamic Output Feedback ◽  
Time Varying ◽  
Closed Loop System ◽  
Periodic Disturbances ◽  
Adaptive Output Feedback Control ◽  
Coefficient Vector

The paper considers rejection of unmatched general periodic disturbances with time-varying gains for a class of nonlinear systems. The period of the periodic disturbances is known, the gains of the disturbances depend on the output of the system, and the coefficient vector of the disturbance input channel is not assumed to be a Hurwitz vector. A novel filtered transformation is presented. Based on the filtered transformation, an adaptive output feedback control law is proposed, which guarantees that the output of the closed loop system converges to zero.

Sign in / Sign up

Export Citation Format

Share Document