Full State Feedback Control Design for “Delay Scheduling”

Author(s):  
Mursel Emre Cavdaroglu ◽  
Nejat Olgac

A fixed full state feedback controller design approach is proposed for linear time invariant (LTI) systems with time delays. This approach enables the designer to use recently introduced “delay scheduling” procedure, which opens a new direction in control synthesis. “Delay scheduling” strategy suggests prolonging the existing (and unavoidable) delays in order to recover stability or to improve the control performance features. To be able to do this, however, system should have multiple stable operating zones in the domain of the delays. The main contribution of this paper is to develop a procedure for designing such a control law. It starts with a simple usage of LQR for non-delayed systems. This approach, nevertheless, imparts some complexities when delays are introduced. We handle them using a recent paradigm, called the Cluster Treatment of Characteristic Roots (CTCR). For an example to the ensuing design strategy, we use a fully actuated cart-pendulum system. Relevant simulations are carried out to show the viability of the proposed idea.

This paper presents the design of a full state feedback H∞ controller to an inverted pendulum system. The nonlinear and linearized models of the system are obtained. The main goal of the proposed controller is to maintain the pendulum in the upright position and achieve a desirable tracking for the cart position. To achieve desirable tracking properties an integral term is added. The robustness of the proposed controller is examined when a 20% variation in the parameters of system is considered.


Author(s):  
S.C Sinha ◽  
Alexandra Dávid

In this study, some techniques for the control of chaotic nonlinear systems with periodic coefficients are presented. First, chaos is eliminated from a given range of the system parameters by driving the system to a desired periodic orbit or to a fixed point using a full-state feedback. One has to deal with the same mathematical problem in the event when an autonomous system exhibiting chaos is desired to be driven to a periodic orbit. This is achieved by employing either a linear or a nonlinear control technique. In the linear method, a linear full-state feedback controller is designed by symbolic computation. The nonlinear technique is based on the idea of feedback linearization. A set of coordinate transformation is introduced, which leads to an equivalent linear system that can be controlled by known methods. Our second idea is to delay the onset of chaos beyond a given parameter range by a purely nonlinear control strategy that employs local bifurcation analysis of time-periodic systems. In this method, nonlinear properties of post-bifurcation dynamics, such as stability or rate of growth of a limit set, are modified by a nonlinear state feedback control. The control strategies are illustrated through examples. All methods are general in the sense that they can be applied to systems with no restrictions on the size of the periodic terms.


2001 ◽  
Vol 123 (4) ◽  
pp. 319-326 ◽  
Author(s):  
Karl Stol ◽  
Mark Balas

An investigation of the performance of a model-based periodic gain controller is presented for a two-bladed, variable-speed, horizontal-axis wind turbine. Performance is based on speed regulation using full-span collective blade pitch. The turbine is modeled with five degrees-of-freedom; tower fore-aft bending, nacelle yaw, rotor position, and flapwise bending of each blade. An attempt is made to quantify what model degrees-of-freedom make the system most periodic, using Floquet modal properties. This justifies the inclusion of yaw motion in the model. Optimal control ideas are adopted in the design of both periodic and constant gain full-state feedback controllers, based on a linearized periodic model. Upon comparison, no significant difference in performance is observed between the two types of control in speed regulation.


Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2674 ◽  
Author(s):  
Rizka Bimarta ◽  
Thuy Vi Tran ◽  
Kyeong-Hwa Kim

This paper proposes a frequency-adaptive current control design for a grid-connected inverter with an inductive–capacitive–inductive (LCL) filter to overcome the issues relating to both the harmonic distortion and frequency variation in the grid voltage. The current control scheme consists of full-state feedback control to stabilize the system and integral control terms to track the reference in the presence of disturbance and uncertainty. In addition, the current controller is augmented with resonant control terms to mitigate the harmonic component. The control scheme is implemented in the synchronous reference frame (SRF) to effectively compensate two harmonic orders at the same time by using only one resonant term. Moreover, to tackle the frequency variation issue in grid voltage, the frequency information which is extracted from the phase-locked loop (PLL) block is processed by a moving average filter (MAF) for the purpose of eliminating the frequency fluctuation caused by the harmonically distorted grid voltage. The filtered frequency information is employed to synthesize the resonant controller, even in the environment of frequency variation. To implement full-state feedback control for a grid-connected inverter with an LCL filter, all the state variables should be available. However, the increase in number of sensing devices leads to the rise of cost and complexity for hardware implementation. To overcome this challenge, a discrete-time full-state current observer is introduced to estimate all the system states. When the grid frequency is subject to variation, the discrete-time implementation of the observer in the SRF requires an online discretization process because the system matrix in the SRF includes frequency information. This results in a heavy computational burden for the controller. To resolve such a difficulty, a discrete-time observer in the stationary reference frame is employed in the proposed scheme. In the stationary frame, the discretization of the system model can be accomplished with a simple offline method even in the presence of frequency variation since the system matrix does not include the frequency. To select desirable gains for the full-state feedback controller and full-state observer, an optimal linear quadratic control approach is applied. To validate the practical effectiveness of the proposed frequency-adaptive control, simulation and experimental results are presented.


2016 ◽  
Vol 40 (1) ◽  
pp. 179-190 ◽  
Author(s):  
Langwen Zhang ◽  
Wei Xie ◽  
Zhaozhun Zhong ◽  
Jingcheng Wang

In this paper, a model predictive control algorithm is presented for linear parameter varying systems with both state delays and randomly occurring input saturation. The input saturation is assumed to be occurred randomly with Bernoulli-distributed white sequences. A constant sate feedback law is designed at each time instant to ensure the robust stability of the closed-loop system with respect to polytopic uncertainties. The optimization of model predictive controller is cast into solving a linear matrix inequalities optimization problem. Then, the results are extended to gain-scheduled approach in which a set of state feedback laws are designed for each vertex of the system model. The state feedback law is scheduled by the time varying model parameters to achieve less conservatism in controller design. Finally, two examples are employed to show the effectiveness of the proposed algorithms.


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