scholarly journals Adaptive Control Design with Assigned Tracking Accuracy for a Class of Nonlinearly Parameterized Input-Delayed Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Dajie Yao ◽  
Jing Li ◽  
Jian Wu
Keyword(s):  
Adaptive Control ◽  
Closed Loop ◽  
A Priori ◽  
Tracking Error ◽  
Input Delay ◽  
Tracking Accuracy ◽  
Unknown Parameters ◽  
Controlled System ◽  
Delayed Systems ◽  
Nonlinearly Parameterized

This paper addresses the adaptive control problem of a class of nonlinear systems with unknown parameters and input delay, and the tracking accuracy of the controlled system is assigned a priori. The Pade approximation method is introduced to deal with the problem from the input delay. By creating a group of nonnegative functions, an appropriate controller is designed with the backstepping technology. It is shown that under the obtained controller, the boundedness of all the closed-loop signals is guaranteed, and the tracking error especially can converge to the accuracy assigned a priori. Finally, a simulation example is given to verify the effectiveness of the proposed scheme.

Vehicle yaw-inertia- and mass-independent adaptive steering control

2009 ◽  
Vol 223 (9) ◽  
pp. 1101-1108 ◽  
Author(s):  
J Wang ◽  
M F Hsieh
Keyword(s):  
Adaptive Control ◽  
Tracking Error ◽  
Stability Control ◽  
Driving Safety ◽  
Control Law ◽  
Steering Control ◽  
Tracking Accuracy ◽  
Unknown Parameters ◽  
Practical Applications ◽  
Adaptive Control Law

This paper describes a vehicle stability control (VSC) system using a vehicle yaw-inertia- and mass-independent adaptive control law. As a primary vehicle active control system, VSC can significantly improve vehicle driving safety for passenger cars and enhance trajectory tracking accuracy for other applications such as autonomous, surveillance, and mobile robot vehicles. For the designs of vehicle dynamic control systems, vehicle yaw inertia and mass are two of the most important parameters. However, in practical applications, vehicle yaw inertia and mass often change with vehicle payload and load distribution. In this paper, an adaptive control law is proposed to treat the vehicle yaw inertia and mass as unknown parameters and automatically address their variations. For the proposed adaptive control law, asymptotic stability of the yaw rate tracking error was proved by a Lyapunov-like analysis for certain vehicle architectures under some reasonable assumptions. The performance of the yaw-inertia- and mass-independent adaptive VSC system was evaluated under several driving conditions (i.e. double lane changing on a slippery surface and braking on a split- μ surface tests) through simulation studies using a high-fidelity full-vehicle model provided by CarSim®.

scholarly journals Adaptive Neural Control with Prespecified Tracking Accuracy for a Class of Switched Systems Subject to Input Delay

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Xu Zhang ◽  
Jian Wu ◽  
Wu Ai ◽  
Jing Li
Keyword(s):  
Switched Systems ◽  
Neural Control ◽  
A Priori ◽  
Tracking Error ◽  
Input Delay ◽  
Tracking Accuracy ◽  
Adaptive Tracking Control ◽  
Control Scheme ◽  
Switching Functions ◽  
Adaptive Neural Controller

This paper is concerned with the adaptive tracking control design for a class of uncertain switched systems subject to input delay. Unlike the existing results on uncertain switched systems, the new proposed control scheme ensures that the tracking error converges to the accuracy given a priori according to the requirement. To achieve this aim, some nonnegative switching functions are introduced to replace the conventional Lyapunov function. In addition, neural networks are used to approximate the unknown simultaneous domination functions. By combining the backstepping technique and some common nonnegative switching functions, a stable adaptive neural controller is established. It can be shown that the closed-loop system is semiglobally uniformly ultimately bounded (SGUUB) and the tracking error satisfies the predefined accuracy. The effectiveness of the proposed control scheme is verified by a simulation example.

Logic-Based Switching Adaptive Control of DC-DC Buck Converter

2012 ◽  
Vol 229-231 ◽  
pp. 2209-2212
Author(s):  
Bao Bin Liu ◽  
Wei Zhou
Keyword(s):  
Adaptive Control ◽  
Closed Loop ◽  
Buck Converter ◽  
Uncertain Parameters ◽  
Small Signal ◽  
Closed Loop System ◽  
Unknown Parameters ◽  
Signal Model ◽  
Small Signal Model ◽  
Control Scheme

Logic-based switching adaptive control scheme is proposed for the model of DC-DC buck converter in presence of uncertain parameters and power supply disturbance. All uncertain parameters and the disturbance are estimated together through constructing Lyapunov function. And a switching mechanism is used to ensure global asymptotic stability of the closed-loop system. The results of simulation show that even if there are multiple unknown parameters in the small-signal model, the control system of DC-DC buck converter can estimate unknown parameters quickly and accurately.

Adaptive control of a class of non-linear systems preceded by backlash-like hysteresis

2014 ◽  
Vol 24 (5) ◽  
Author(s):  
JIANPING CAI ◽  
LUJUAN SHEN ◽  
FUZHEN WU
Keyword(s):  
Differential Equation ◽  
Adaptive Control ◽  
Linear Systems ◽  
Tracking Error ◽  
Robust Adaptive Control ◽  
Unknown Parameters ◽  
Control Scheme ◽  
Non Linear ◽  
Non Linear Systems ◽  
Robust Adaptive

We consider a class of uncertain non-linear systems preceded by unknown backlash-like hysteresis, which is modelled by a differential equation. We propose a new state feedback robust adaptive control scheme using a backstepping technique and properties of the differential equation. In this control scheme, we construct a new continuous function to design an estimator to estimate the unknown constant parameters and the unknown bound of a ‘disturbance-like’ term. The transient performance of the output tracking error can be guaranteed by the introduction of pre-estimates of the unknown parameters in our controller together with update laws. We do not require bounds on the ‘disturbance-like’ term or unknown system parameters in this scheme. The global stability of the closed-loop system can be proved.

Composite Model Reference Adaptive Control for a Class of Nonlinear Fractional Order Systems

2015 ◽  
Author(s):  
Yiheng Wei ◽  
Shu Liang ◽  
Yangsheng Hu ◽  
Yong Wang
Keyword(s):  
Adaptive Control ◽  
Fractional Order ◽  
Closed Loop ◽  
Tracking Error ◽  
Model Reference Adaptive Control ◽  
Prediction Errors ◽  
Model Reference ◽  
Closed Loop Systems ◽  
The Stability ◽  
Model Reference Adaptive

This article presents a novel model reference adaptive control of fractional order nonlinear systems, which is a generalization of existing method for integer order systems. The formulating adaptive law is in terms of both tracking and prediction errors, whereas existing methods only depends on tracking error. The transient performance of the closed-loop systems with the proposed control strategy improves in the sense of generating smooth system output. The stability and tracking convergence of the resulting closed-loop system are analyzed via the indirect Lyapunov method. Meanwhile, the proposed controller is implemented by employing some fractional order tracking differentiator to generate the required fractional derivatives of a signal. Numerical examples are provided to illustrate the effectiveness of our results.

scholarly journals BIFURCATIONS AND LIMIT DYNAMICS IN ADAPTIVE CONTROL SYSTEMS

2005 ◽  
Vol 15 (05) ◽  
pp. 1641-1664 ◽  
Author(s):  
G. R. ROKNI LAMOOKI ◽  
S. TOWNLEY ◽  
H. M. OSINGA
Keyword(s):  
Adaptive Control ◽  
Control Systems ◽  
Closed Loop ◽  
Initial Conditions ◽  
Adaptive Stabilization ◽  
Unknown Parameters ◽  
Adaptive Controllers ◽  
Limit System ◽  
Adaptive Control Systems ◽  
Second Order Systems

Adaptive controllers are used in systems where one or more parameters are unknown. Such controllers are designed to stabilize the system using an estimate for the unknown parameters that is adapted automatically as part of the stabilization. One drawback in adaptive control design is the possibility that the closed-loop limit system is not stable. The worst situation is the existence of a destabilized limit system attracting a large open subset of initial conditions. These situations lie behind bad behavior of the closed-loop adaptive control system. The main issue in this paper is to identify and characterize the occurrence of such bad behavior in the adaptive stabilization of first- and second-order systems with one unknown parameter. We develop normal forms for all possible cases and find the conditions that lead to bad behavior. In this context, we discuss a number of bifurcation-like phenomena.

Sensitivity Comparison to Loop Latencies Between Damping Versus Stiffness Feedback Control Action in Distributed Controllers

2014 ◽  
Author(s):  
Ye Zhao ◽  
Nicholas Paine ◽  
Luis Sentis
Keyword(s):  
Closed Loop ◽  
Impedance Control ◽  
Tracking Error ◽  
Loop System ◽  
Tracking Performance ◽  
System Stability ◽  
Step Response ◽  
Tracking Accuracy ◽  
Closed Loop System ◽  
And Performance

This paper studies the effects of damping and stiffness feedback loop latencies on closed-loop system stability and performance. Phase margin stability analysis, step response performance and tracking accuracy are respectively simulated for a rigid actuator with impedance control. Both system stability and tracking performance are more sensitive to damping feedback than stiffness feedback latencies. Several comparative tests are simulated and experimentally implemented on a real-world actuator to verify our conclusion. This discrepancy in sensitivity motivates the necessity of implementing embedded damping, in which damping feedback is implemented locally at the low level joint controller. A direct benefit of this distributed impedance control strategy is the enhancement of closed-loop system stability. Using this strategy, feedback effort and thus closed-loop actuator impedance may be increased beyond the levels possible for a monolithic impedance controller. High impedance is desirable to minimize tracking error in the presence of disturbances. Specially, trajectory tracking accuracy is tested by a fast swing and a slow stance motion of a knee joint emulating NASA-JSC’s Valkyrie legged robot. When damping latencies are lowered beyond stiffness latencies, gravitational disturbance is rejected, thus demonstrating the accurate tracking performance enabled by a distributed impedance controller.

Towards an Adaptive Control Concept for Unknown Nonlinear MIMO Systems

2018 ◽  
Author(s):  
Elmira Madadi ◽  
Dirk Söffker
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Control Method ◽  
Mimo Systems ◽  
Tracking Error ◽  
Underlying Structure ◽  
Unknown Parameters ◽  
Modified Model ◽  
Model Free ◽  
Model Free Control

The design of an accurate model often appears as the most challenging tasks for control engineers especially focusing to the control of nonlinear systems with unknown parameters or effects to be identified in parallel. For this reason, development of model-free control methods is of increasing importance. The class of model-free control approaches is defined by the non-use of any knowledge about the underlying structure and/or related parameters of the dynamical system. Therefore the major criteria to evaluate model-free control performance are aspects regarding robustness against unknown inputs and disturbances to achieve a suitable tracking performance including ensuring stability. Consequently it is assumed that the system plant model to be controlled is unknown, only the inputs and outputs are used as measurements. In this contribution a modified model-free adaptive approach is given as the extended version of existing model-free adaptive control to improve the performance according to the tracking error at each sample time. Using modified model-free adaptive controller, the control goal can be achieved efficiently without an individual control design process for different kinds unknown nonlinear systems. The main contribution of this paper is to extend the modified model-free adaptive control method to unknown nonlinear multi-input multi-output (MIMO) systems. A numerical example is shown to demonstrate the successful application and performance of this method.

On Performance Losses in Some Adaptive Control Systems: I

1965 ◽  
Vol 87 (1) ◽  
pp. 90-94 ◽  
Author(s):  
Masanao Aoki
Keyword(s):  
Adaptive Control ◽  
Control Systems ◽  
Unknown Parameter ◽  
A Priori ◽  
Control Policy ◽  
Optimal Estimation ◽  
Perfect Information ◽  
Point Of View ◽  
Unknown Parameters ◽  
Linear Differential

In controlling dynamic systems with unknown parameters and/or systems operating in unknown environment, the systems suffer due to the unknowness of pertinent parameter values, compared with situations with perfect information where all pertinent information is available to control systems optimally. The paper defines the concept of loss of performance to represent the loss in performance of some adaptive control situations compared with perfect information situations and defines the optimal control problems as the one where the loss of performance is minimized. This concept is illustrated for a control system governed by a scalar linear differential equation with unknown gain. The minimax control policy is defined as the control policy which minimized the maximum possible loss in performance where no a priori knowledge on the unknown parameter is available. It also discusses the optimal estimation problem of the unknown parameter from the point of view of loss of performance.

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