Comparative Study of Trajectory Tracking Control for Automated Vehicles via Model Predictive Control and Robust H-infinity State Feedback Control

A comparative study of model predictive control(MPC)schemes and robust Hstate feedback control(RSC)method for trajectory tracking is proposed in this paper.The main objective of this paper is to compare MPC and RSC controllers’performance in tracking predefined trajectory under different scenarios.MPC controller is designed based on the simple longitudinal-yaw-lateral motions of a single-track vehicle with a linear tire,which is an approximation of the more realistic model of a vehicle with double-track motion with a non-linear tire mode.RSC is designed on the basis of the same method as adopted for the MPC controller to achieve a fair comparison.Then,three test cases are built in CarSim-Simulink joint platform.Specifically,the verification test is used to test the tracking accuracy of MPC and RSC controller under well road conditions.Besides,the double lane change test with low road adhesion is designed to find the maximum velocity that both controllers can carry out while guaranteeing stability.Furthermore,an extreme curve test is built where the road adhesion changes suddenly,in order to test the performance of both controllers under extreme conditions.Finally,the advantages and disadvantages of MPC and RSC under different scenarios are also discussed.

An Improvement on Data-Driven Pole Placement for State Feedback Control and Model Identification

The recently proposed data-driven pole placement method is able to make use of measurement data to simultaneously identify a state space model and derive pole placement state feedback gain. It can achieve this precisely for systems that are linear time-invariant and for which noiseless measurement datasets are available. However, for nonlinear systems, and/or when the only noisy measurement datasets available contain noise, this approach is unable to yield satisfactory results. In this study, we investigated the effect on data-driven pole placement performance of introducing a prefilter to reduce the noise present in datasets. Using numerical simulations of a self-balancing robot, we demonstrated the important role that prefiltering can play in reducing the interference caused by noise.

Observer-based State Feedback Control to Suppress Stick-slip Vibrations in Oil Well Drill-string

In drilling field, stick-slip vibrations of the drill-string are the main reason for the failure of the drilling system. To suppress the undesired stick-slip vibrations, an observer-based state feedback control method is proposed. The drilling system is described by a lumped parameter model including a Karnopp friction torque model. A state observer is designed to estimate the bit velocity in bottom hole and a state feedback controller is proposed to control the top drive velocity. By simulation, the performance of the control algorithm is demonstrated. Based on the control algorithm, a stick-slip vibration control system is developed. Test results show that the control system can effectively eliminate stick-slip vibrations of the drill-string and can be applied to the drilling field.

Robust State Feedback Control of Wind-Excited Tall Buildings

The introduction of robust control theory into structure control, as well as design procedure of stabilizing controllers for structures with parameter uncertainty and model error is discussed. A stability bound is derived from the polar decomposition of the nominal system matrix. In addition, our study shows that application of low pass filters avoids spillover by eliminating the unconsidered high frequency components. It is demonstrated, via an example, our approach leads to excellent control result and offers far better robustness than previous solutions.

Optimal state feedback control of brushless direct-current motor drive systems based on Lyapunov stability criterion

This paper develops a unified methodology for a real-time speed control of brushless direct-current motor drive systems in the presence of measurement noise and load torque disturbance. First, the mathematical model and hardware structure of system is established. Next, an optimal state feed back controller using the Kalman filter state estimation technique is derived. This is followed by an adaptive control algorithm to compensate for the effects of noise and disturbance. Those two algorithms working together can provide a very-high-speed regulation and dynamic response over a wide range of operating conditions. Simulated responses are presented to highlight the effectiveness of the proposed control strategy.

Robust H_∞ Stabilization of Uncertain Linear Time-Delay System with Delayed/Undelayed State Feedback Controllers

This paper focuses on the H∞ controller design for linear systems with time-varying delays and norm-bounded parameter perturbations in the system state and control/disturbance. On the existence of delayed/undelayed full state feedback controllers, we present a sufficient condition and give a design method in the form of Riccati equation. The controller can not only stabilize the time-delay system, but also make the H∞ norm of the closed-loop system be less than a given bound. This result practically generalizes the related results in current literature.

Mixed H_2/H_∞ State Feedback Attitude Control of Microsatellite Based on Extended LMI Method

For the appearance of the additive perturbation of controller gain when the controller parameter has minute adjustment at the initial running stage of system,to avoid the adverse effects,this paper investigates the mixed H_2/H_∞ state feedback attitude control problem of microsatellite based on extended LMI method.Firstly,the microsatellite attitude control system is established and transformed into corresponding state space form.Then,without the equivalence restriction of the two Lyapunov variables of H_2 and H∞performance,this paper introduces additional variables to design the mixed H_2/H_∞ control method based on LMI which can also reduce the conservatives.Finally,numerical simulations are analyzed to show that the proposed method can make the satellite stable within 20 s whether there is additive perturbation of the controller gain or not.The comparative analysis of the simulation results between extended LMI method and traditional LMI method also demonstrates the effectiveness and feasibility of the proposed method in this paper.

Impulsive state feedback control during the sulphitation reaction in process of manufacture of sugar

In this paper,the system with impulsive state feedback control corresponding to the sulphitation reaction in process of manufacturo of sugar is considered.By means of square approximation and a series of switched systems,the periodic solution is approximated by a series of continuous hybrid limit cycles.Similar to the analysis of limit cycles of continuous systems,the existence and stability criteria of the order-1 periodic solution are obtained.Further,numerical analysis and discussion are given.

Adaptive State Feedback Predictive Control and Expert Control for a Delayed Coking Furnace

预兆的控制(SFPC ) 计划和专家控制策划的适应州的反馈被介绍并且适用于 1200 kt 路 a 的温度控制 ? 1 推迟了 coking 炉子，它是为推迟的 coking 进程的关键设备。适应 SFPC 被用来在正常操作改进温度控制的表演。一个简化非线性的模型根据炉子的第一个原则被开发由 linearization 获得一个州的空间模型。利用非线性的模型，因为试管 coking 和负担变化，改编方法的一个联机模型被介绍提供过程特征的动态变化。为了补偿源于特别速度的注射蒸气的突然的增加到试管，一个监视方法和一位专家的插头温度的大反的反应，基于热控制计划平衡计算被建议。工业实现显示出建议控制策略的有效性和可行性。

State Feedback Sliding Mode Control without Chattering by Constructing Hurwitz Matrix for AUV Movement

This paper presents a new method to eliminate the chattering of state feedback sliding mode control （SMC） law for the mobile control of an autonomous underwater vehicle （AUV） which is nonlinear and suffers from unknown disturbances system. SMC is a well-known nonlinear system control algorithm for its anti-disturbances capability, while the chattering on switch surface is one stiff question. To dissipate the well-known chattering of SMC, the switching manifold is proposed by presetting a Hurwitz matrix which is deducted from the state feedback matrix. Meanwhile, the best switching surface is achieved by use of eigenvalues of the Hurwitz matrix. The state feedback control parameters are not only applied to control the states of AUV but also connected with coefficients of switching surface. The convergence of the proposed control law is verified by Lyapunov function and the robust character is validated by the Matlab platform of one AUV model.

Disturbance Attenuation State-Feedback Control for Uncertain Interconnected Systems

This paper studies the problem of robust H∞ control design for a class of uncertain interconnected systems via state feedback. This class of systems are described by a state space model, which contains unknown nonlinear interaction and time-varying norm-bounded parametric uncertainties in state equation. Using the Riccati-equation-based approach we design state feedback control laws, which guarantee the decentralized stability with disturbance attenuation for the interconnected uncertain systems. A simple example of an interconnected uncertain linear system is presented to illustrate the results.

ASUBOPTIMAL DESIGN OF H∞DECENTRALIZED STATE FEEDBACK CONTROL FOR INTERCONNEC TED SYSTEMS

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Bisimulation-based stabilization of probabilistic Boolean control networks with state feedback control

This study is concerned with probabilistic Boolean control networks(PBCNs)with state feedback control.A novel definition of bisimilar PBCNs is proposed to lower computational complexity.To understand more on bisimulation relations between PBCNs,we resort to a powerful matrix manipulation called semi-tensor product(STP).Because stabilization of networks is of critical importance,the propagation of stabilization with probability one between bisimilar PBCNs is then considered and proved to be attainable.Additionally,the transient periods(the maximum number of steps to implement stabilization)of two PBCNs are certified to be identical if these two networks are paired with a bisimulation relation.The results are then extended to the probabilistic Boolean networks.

Generalized electro-biothermo-fluidic and dynamicalmodeling of cancer growth: state-feedback controlled cesium therapy approach

This paper develops a generalized dynamical model to describe the interactive dynamics between normal cells, tumor cells, immune cells, drug therapy, electromagnetic field of the human cells, extracellular heat and fluid transfer, and intercellular fractional mass of Oxygen, cell acidity and Pancreatin enzyme. The overall dynamics stability, controllability and observability have been investigated. Moreover, Cesium therapy is considered as a control input to the 11-dimensional dynamics using state-feedback controlled system and pole placement technique. This approach is found to be effective in driving the desired rate of tumor cell kill and converging the system to healthy equilibrium state. Furthermore, the ranges of the system dynamics parameters which lead to instability and growth of tumor cells have been identified. Finally, simulation results are demonstrated to verify the effectiveness of the applied approach which can be implemented successfully to cancer patients.

Robust State Feedback H_∞Control for Dynamic Biped Robot Based on T-S Fuzzy Model

T-S fuzzy model was applied to describe nonlinear system and global fuzzy model was expressed by the form of uncertain system.Based on robust state feedback H_∞control strategy,designed a global asymptotic steady fuzzy model.This control system can use the experimental input-output data pairs for the biped robot learning and walking with dynamic balance.It is proved by simulation result that robust state feedback H_∞control method based on T-S fuzzy model can effectively restrain the effect of model uncertainties and external disturbance acting on biped robot.From these works,we showed the satisfactory performance of joint tracking without any chattering.

Delay-dependent H-infinity control for continuous time-delay systems via state feedback

The delay-dependent H-infinity analysis and H-infinity control problems for continuous time-delay systems are studied. By introducing an equality with some free weighting matrices, an improved criterion of delay-dependent stability with H-infinity performance for such systems is presented, and a criterion of existence and some design methods of delay-dependent H-infinity controller for such systems are proposed in term of a set of matrix inequalities, which is solved efficiently by an iterative algorithm. Further, the corresponding results for the delay-dependent robust H-infinity analysis and robust H-infinity control problems for continuous time-delay uncertain systems are given. Finally, two numerical examples are given to illustrate the efficiency of the proposed method by comparing with the other existing results.

Robust adaptive control for a class of uncertain non-affine nonlinear systems using neural state feedback compensation

A robust adaptive control is proposed for a class of uncertain nonlinear non-affine SISO systems. In order to approximate the unknown nonlinear function, an affine type neural network(ATNN) and neural state feedback compensation are used, and then to compensate the approximation error and external disturbance, a robust control term is employed. By Lyapunov stability analysis for the closed-loop system, it is proven that tracking errors asymptotically converge to zero. Moreover, an observer is designed to estimate the system states because all the states may not be available for measurements. Furthermore, the adaptation laws of neural networks and the robust controller are given based on the Lyapunov stability theory. Finally, two simulation examples are presented to demonstrate the effectiveness of the proposed control method. Finally, two simulation examples show that the proposed method exhibits strong robustness, fast response and small tracking error, even for the non-affine nonlinear system with external disturbance, which confirms the effectiveness of the proposed approach.

The feedback control of fractional order unified chaotic system

This paper studies the stability of the fractional order unified chaotic system. On the unstable equilibrium points, the equivalent passivity＇＇ method is used to design the nonlinear controller. With the definition of fractional derivatives and integrals, the Lyapunov function is constructed by which it is proved that the controlled fractional order system is stable. With Laplace transform theory, the equivalent integer order state equation from the fractional order nonlinear system is obtained, and the system output can be solved. The simulation results validate the effectiveness of the theory.

Robust Feedback Controller for Exponential Stability of Nonlinear Systems with Mismatched Uncertainties

The robust stabilization of nonlinear systems with mismatched uncertainties is investigated. Based on the stability of the nominal system, a new approach to synthesizing a class of continuous state feedback controllers for uncertain nonlinear dynamical systems is proposed. By such feedback controllers, the exponential stability of uncertain nonlinear dynamical systems can be guaranteed. The approach can give a clear insight to system analysis. An illustrative example is given to demonstrate the utilization of the approach developed. Simulation results show that the method presented is practical and effective.