Adaptive Augmenting Control Design for Time-Varying Polytopic Systems

2016 ◽  
Vol 139 (1) ◽  
Author(s):  
Hessam Mahdianfar ◽  
Emmanuel Prempain
Keyword(s):  
Convex Optimization ◽  
State Feedback ◽  
Closed Loop ◽  
Reference Model ◽  
Tracking Error ◽  
Control Design ◽  
Adaptive Controller ◽  
Time Varying ◽  
Robust Convex Optimization ◽  
And Performance

To increase the performance of closed-loop controlled systems in off-nominal conditions and in the presence of inevitable faults and uncertainties, a systematic approach based on robust convex optimization for adaptive augmenting control design is discussed in this paper. More specifically, this paper addresses the problem of adaptive augmenting controller (AAC) design for systems with time-varying polytopic uncertainty. First, a robust state-feedback controller is designed via robust convex optimization as a baseline controller. The closed-loop polytopic system with the baseline controller is considered as the desired time-varying reference model for the design of a direct state-feedback adaptive controller. Next using Lyapunov arguments, global stability of combined robust baseline and adaptive augmenting controllers is established. Furthermore, it is proved that tracking error converges to zero asymptotically. A case study for a generic nonminimum phase nonlinear pitch-axis missile autopilot is conducted. Simulation tests are performed to evaluate stability and performance of nonlinear time-varying closed-loop system in the presence of uncertainties in pitching moment and normal force coefficients, and unmodeled time delays. In addition, results of the simulations indicate satisfactory robustness in case of severe loss of control effectiveness event.

H∞ fuzzy proportional integral state feedback controller of photovoltaic systems under asymmetric actuator constraints

2020 ◽  
pp. 014233122092157
Author(s):  
K Houda ◽  
D Saifia ◽  
M Chadli ◽  
S Labiod
Keyword(s):  
State Feedback ◽  
Reference Model ◽  
Tracking Error ◽  
Control Design ◽  
Atmospheric Condition ◽  
Boost Converter ◽  
Feedback Controller ◽  
Duty Ratio ◽  
Linear Matrix ◽  
State Feedback Controller

This paper presents a new strategy for a robust maximum power point (MPP) tracking fuzzy controller for photovoltaic (PV) systems subject to actuator asymmetric saturation. A DC-DC boost converter is used to connect a PV panel with an output load. The output voltage of the DC-DC boost converter can be adjusted by duty ratio that is limited between 0 and 1. The aim of our control design is to track the MPP under atmospheric condition changes and the presence of the asymmetric saturation of the duty ratio. To minimize tracking error and disturbance effect, the dynamic behaviour of a PV system and its reference model are described by using Takagi–Sugeno fuzzy models. Then, a constrained control based on a fuzzy PI state feedback controller is proposed. The H∞ control approach is used in control design and stability conditions of the closed-loop system are formulated and solved in terms of linear matrix inequalities. Finally, simulation results are given to show the tracking performance of the control design.

The Swing Control of Cranes with Variable Rope Length Based on Linear Time Varying System Theory

2012 ◽  
Vol 461 ◽  
pp. 763-767
Author(s):  
Li Fu Wang ◽  
Zhi Kong ◽  
Xin Gang Wang ◽  
Zhao Xia Wu
Keyword(s):  
State Feedback ◽  
Closed Loop ◽  
Linear Time ◽  
Feedback Stabilization ◽  
Time Varying ◽  
Closed Loop System ◽  
Overhead Cranes ◽  
Time Varying Systems ◽  
Time Invariant ◽  
Time Invariant System

In this paper, following the state-feedback stabilization for time-varying systems proposed by Wolovich, a controller is designed for the overhead cranes with a linearized parameter-varying model. The resulting closed-loop system is equivalent, via a Lyapunov transformation, to a stable time-invariant system of assigned eigenvalues. The simulation results show the validity of this method.

A New Plug-In Adaptive Controller for Rejection of Periodic Disturbances

1993 ◽  
Vol 115 (3) ◽  
pp. 543-546 ◽  
Author(s):  
Jwusheng Hu ◽  
Masayoshi Tomizuka
Keyword(s):  
Closed Loop ◽  
Structural Information ◽  
Tracking Error ◽  
Disk Drive ◽  
Adaptive Controller ◽  
Error Signal ◽  
Feedback Control System ◽  
Periodic Disturbances ◽  
Tracking Controller ◽  
Digital Algorithm

In this paper, an adaptive digital algorithm for rejecting periodic disturbances is proposed. Modified from the adaptive tracking controller [4], the controller is constructed in a “plug-in” manner, i.e., it can be added to an existed feedback control system without altering the original closed-loop configuration. It is shown that the controller can reject disturbances at selected frequencies independently. Furthermore, since the controller only deals with phase and gain of the error signal, no structural information about the plant is required. The controller is implemented on a disk drive system for track following. The result shows that by rejecting the disturbance up to four times of its fundamental frequency, the tracking error is reduced substantially.

Observer and Controller Design Using Time-Varying Gains: Duality and Distinctions

2004 ◽  
Vol 127 (2) ◽  
pp. 267-274
Author(s):  
Vladimir Polotski
Keyword(s):  
State Feedback ◽  
Closed Loop ◽  
Dual Problem ◽  
Controller Design ◽  
Time Varying ◽  
Feedback Controllers ◽  
Observer Error ◽  
Time Varying Systems ◽  
Error Dynamics ◽  
Time Invariant

Stabilization of linear systems by state feedback is an important problem of the controller design. The design of observers with appropriate error dynamics is a dual problem. This duality leads, at first glance, to the equivalence of the responses in the synthesized systems. This is true for the time-invariant case, but may not hold for time-varying systems. We limit ourselves in this work by the situation when the system itself is time invariant, and only the gains are time varying. The possibility of assigning a rapidly decaying response without peaking is analyzed. The solution of this problem for observers using time-varying gains is presented. Then we show that this result cannot be obtained for state feedback controllers. We also analyze the conditions under which the observer error dynamics and the response of the closed loop time-varying controllers are equivalent. Finally we compare our results to recently proposed observer converging in finite time and Riccati-based continuous observer with limited overshoots.

scholarly journals Neural Networks Approximator Based Robust Adaptive Controller Design of Hypersonic Flight Vehicles Systems Coupled with Stochastic Disturbance and Dynamic Uncertainties

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Guoqiang Zhu ◽  
Lingfang Sun ◽  
Xiuyu Zhang
Keyword(s):  
Controller Design ◽  
Tracking Error ◽  
Adaptive Controller ◽  
Stochastic Disturbance ◽  
Hypersonic Flight ◽  
Flight Vehicles ◽  
Uncertain Dynamics ◽  
Robust Adaptive ◽  
And Performance ◽  
Dynamic Uncertainties

A neural network robust control is proposed for a class of generic hypersonic flight vehicles with uncertain dynamics and stochastic disturbance. Compared with the present schemes of dealing with dynamic uncertainties and stochastic disturbance, the outstanding feature of the proposed scheme is that only one parameter needs to be estimated at each design step, so that the computational burden can be greatly reduced and the designed controller is much simpler. Moreover, by introducing a performance function in controller design, the prespecified transient and performance of tracking error can be guaranteed. It is proved that all signals of closed-loop system are uniformly ultimately bounded. The simulation results are carried out to illustrate effectiveness of the proposed control algorithm.

scholarly journals Subspace predictive control: stability and performance enhancement

2021 ◽  
Author(s):  
Saba Sedghizadeh
Keyword(s):  
Time Delay ◽  
Predictive Control ◽  
Closed Loop ◽  
System Modeling ◽  
Design Procedure ◽  
Control Design ◽  
Time Delay Estimation ◽  
Function Optimization ◽  
System Stability ◽  
And Performance

In the absence of prior knowledge of a system, control design relies heavily on the system identifi- cation procedure. In real applications, there is an increasing demand to combine the usually time consuming system identification and modeling step with the control design procedure. Motivated by this demand, data-driven control approaches attempt to use the input-output data to design the controller directly. Subspace Predictive Control (SPC) is one popular example of these algorithms that combines Model Predictive Control (MPC) and Subspace Identification Methods (SIM). SPC instability and performance deterioration in closed-loop implementations are majorly caused by either poor tuning of SPC horizons or changes in the dynamics of the system. Stability and performance analysis of the SPC are the focus of this dissertation. We first provide the necessary and sufficient condition for SPC closed-loop stability. The results introduce SPC stability graphs that can provide the feasible prediction horizon range. Consequently, these stability constraints are included in SPC cost function optimization to provide a new method for determining the SPC horizons. The novel SPC horizon selection enhances the closed-loop performance effectively. Note that time-delay estimation and order selection in system modeling have been a challenging step in applications and industry. Here, we propose a new approach denoted by RE-based TDE that simultaneously and fficiently estimates the time-delay for the SIM framework. In addition, we use the recently developed MSEE approach for estimating the system order. Moreover, we propose an arti- ficial intelligence approach denoted by Particle Swarm Optimization Based Fuzzy Gain-Scheduled SPC (PSO-based FGS-SPC). The method overcomes the issue of on-line adaptation of SPC gains for systems with variable dynamics in the presence of the noisy data. The approach eliminates existing tuning problem of controller gain ranges in FGS and updates the SPC gains with no need to apply any external persistently excitation signals. As a result, PSO-based FGS-SPC provides a time efficient control strategy with fast and robust tracking performance compared to conventional and state of the art methods.

scholarly journals Continuous-Time Perfect Control Algorithm—A State Feedback Approach

2021 ◽  
Vol 11 (16) ◽  
pp. 7466
Author(s):  
Marek Krok ◽  
Wojciech P. Hunek ◽  
Paweł Majewski
Keyword(s):  
Design Process ◽  
Process Simulation ◽  
Continuous Time ◽  
Control Algorithm ◽  
State Feedback ◽  
Closed Loop ◽  
Control Design ◽  
Control Law ◽  
New Approach

In this paper, a new approach to the continuous-time perfect control algorithm is given. Focusing on the output derivative, it is shown that the discussed control law can effectively be implemented in terms of state-feedback scenarios. Moreover, the application of nonunique matrix inverses is also taken into consideration during the perfect control design process. Simulation examples given within this work allow us to showcase the main properties obtained for continuous-time perfect control closed-loop plants.

Global stabilization for switched stochastic nonlinear systems via unbounded time-varying scaling

2017 ◽  
Vol 40 (7) ◽  
pp. 2270-2277 ◽  
Author(s):  
Zhibao Song ◽  
Junyong Zhai ◽  
Zhengwei Zhu
Keyword(s):  
Nonlinear Systems ◽  
State Feedback ◽  
Closed Loop ◽  
Switched System ◽  
Feedback Controller ◽  
Stochastic Nonlinear Systems ◽  
Time Varying ◽  
Global Stabilization ◽  
Asymptotically Stable ◽  
Control Scheme

This paper is concerned with the problem of global stabilization for switched stochastic nonlinear systems under arbitrary switchings. Based on the unbounded time-varying scaling of states, we design a state feedback controller to render the closed-loop switched system asymptotically stable in probability. Two examples are given to demonstrate the effectiveness of the proposed control scheme.

scholarly journals Stabilization for Damping Multimachine Power System with Time-Varying Delays and Sector Saturating Actuator

2016 ◽  
Vol 2016 ◽  
pp. 1-13
Author(s):  
Linlin Ma ◽  
Yanping Liang ◽  
Jian Chen
Keyword(s):  
Power System ◽  
State Feedback ◽  
Closed Loop ◽  
Controller Design ◽  
Lyapunov Theory ◽  
Sufficient Condition ◽  
Time Varying ◽  
Pd Controller ◽  
Stabilization Problem ◽  
Effectiveness And Efficiency

This paper studies the stabilization problem for damping multimachine power system with time-varying delays and sector saturating actuator. The multivariable proportional plus derivative (PD) type stabilizer is designed by transforming the problem of PD controller design to that of state feedback stabilizer design for a system in descriptor form. A new sufficient condition of closed-loop multimachine power system asymptomatic stability is derived based on the Lyapunov theory. Computer simulation of a two-machine power system has verified the effectiveness and efficiency of the proposed approach.

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