Pure State Feedback Switching Control Based on the Online Estimated State for Stochastic Open Quantum Systems

For the n-qubit stochastic open quantum systems,based on the Lyapunov stability theorem and LaSalle’s invariant set principle,a pure state switching control based on on-line estimated state feedback(short for OQST-SFC)is proposed to realize the state transition the pure state of the target state including eigenstate and superposition state.The proposed switching control consists of a constant control and a control law designed based on the Lyapunov method,in which the Lyapunov function is the state distance of the system.The constant control is used to drive the system state from an initial state to the convergence domain only containing the target state,and a Lyapunov-based control is used to make the state enter the convergence domain and then continue to converge to the target state.At the same time,the continuous weak measurement of quantum system and the quantum state tomography method based on the on-line alternating direction multiplier(QST-OADM)are used to obtain the system information and estimate the quantum state which is used as the input of the quantum system controller.Then,the pure state feedback switching control method based on the on-line estimated state feedback is realized in an n-qubit stochastic open quantum system.The complete derivation process of n-qubit QST-OADM algorithm is given;Through strict theoretical proof and analysis,the convergence conditions to ensure any initial state of the quantum system to converge the target pure state are given.The proposed control method is applied to a 2-qubit stochastic open quantum system for numerical simulation experiments.Four possible different position cases between the initial estimated state and that of the controlled system are studied and discussed,and the performances of the state transition under the corresponding cases are analyzed.

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

An adaptive state feedback predictive control （SFPC） scheme and an expert control scheme are presented and applied to the temperature control of a 1200 kt·a^-1 delayed coking furnace, which is the key equipment for the delayed coking process. Adaptive SFPC is used to improve the performance of temperature control in normal operation. A simplified nonlinear model on the basis of first principles of the furnace is developed to obtain a state space model by linearization. Taking advantage of the nonlinear model, an online model adapting method is presented to accommodate the dynamic change of process characteristics because of tube coking and load changes. To compensate the large inverse response of outlet temperature resulting from the sudden increase of injected steam of a particular velocity to tubes, a monitoring method and an expert control scheme based on heat balance calculation are proposed. Industrial implementation shows the effectiveness and feasibility of the proposed control strategy.

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.

Geometric Structures of Stable Time-Variant State Feedback Systems

A new technique for considering the stabilizing time-variant state feedback gains is proposed from the viewpoint of information geometry. First, parametrization of the set of all stabilizing time-variant state feedback gains is given. Moreover, a diffeomorphic structure between the set of stabilizing time-variant state feedback gains and the Cartesian product of positive definite matrix and skew symmetric matrix satisfying certain algebraic conditions is constructed. Furthermore, an immersion and some results about the eigenvalue locations of stable state feedback systems are derived.

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.

State Feedback Control for a Class of Fractional Order Nonlinear Systems

Using the Lyapunov function method, this paper investigates the design of state feedback stabilization controllers for fractional order nonlinear systems in triangular form, and presents a number of new results. First, some new properties of Caputo fractional derivative are presented, and a sufficient condition of asymptotical stability for fractional order nonlinear systems is obtained based on the new properties. Then, by introducing appropriate transformations of coordinates, the problem of controller design is converted into the problem of finding some parameters, which can be certainly obtained by solving the Lyapunov equation and relevant matrix inequalities. Finally, based on the Lyapunov function method, state feedback stabilization controllers making the closed-loop system asymptotically stable are explicitly constructed. A simulation example is given to demonstrate the effectiveness of the proposed design procedure. © 2014 Chinese Association of Automation.

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.

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

In the paper, the problem of H∞ decentralized state feedback control for largescale systems is described. An algorithm is proposed which uses the method of a feasible direction matrix. The algorithm only requires the solution of an algebraic Riccati equation (ARE) and makes the H∞norm of the closedloop transfer function matrix from disturbance inputs to controlled outputs less than a given constant which ensure the stability of the overall controlled system at each iteration. The given example shows that the convergence of the algorithm is satisfactory.

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.

Dissipative preparation of a steady three-dimensional entangled state via quantum-jump-based feedback

A robust and scalable scheme to generate a steady three-dimensional entangled state for a V-type atom and a A- type atom trapped in a strongly dissipative bimodal cavity is proposed by direct feedback control based on quantum-jump detection. The robustness of this scheme reflects in the insensitivity to detection inefficiencies and the strong ability against the parameter fluctuations in the feedback, driving, and coupling strengths. The influence of atomic spontaneous emission can be suppressed by using the local feedback control. The scalability is ensured that N-dimensional entangled states of two atoms can be deterministically generated.

State feedback design for singularly perturbed system using unified approach

The state feedback design for singularly perturbed systems described in Delta operator is considered. The composite state feedback controller for slow and fast subsystems is designed by using the direct method. The obtained results can bring previous conclusions of continuous and discrete time systems into the unified Delta framework. A simulation example is presented to demonstrate the validity and efficiency of the design.

On Asymptotic Stabilization of Linear Discrete-time Systems with Saturated State Feedback

As saturation is involved in the stabilizing feedback control of a linear discrete-time system, the original global-asymptotic stabilization (GAS) may drop to region-asymptotic stabilization (RAS). How to test if the saturated feedback system is GAS or RAS? The paper presents a criterion to answer this question, and describes an algorithm to calculate an invariant attractive ellipsoid for the RAS case. At last, the effectiveness of the approach is shown with examples.

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.

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.

Pseudo-Predictor Feedback Control for Multiagent Systems with Both State and Input Delays

This paper is concerned with the consensus problem for high-order continuous-time multiagent systems with both state and input delays.A novel approach referred to as pseudopredictor feedback protocol is proposed.Unlike the predictorbased feedback protocol which utilizes the open-loop dynamics to predict the future states,the pseudo-predictor feedback protocol uses the closed-loop dynamics of the multiagent systems to predict the future agent states.Full-order/reduced-order observer-based pseudo-predictor feedback protocols are proposed,and it is shown that the consensus is achieved and the input delay is compensated by the proposed protocols.Necessary and sufficient conditions guaranteeing the stability of the integral delay systems are provided in terms of the stability of the series of retarded-type time-delay systems.Furthermore,compared with the existing predictor-based protocols,the proposed pseudo-predictor feedback protocol is independent of the input signals of the neighboring agents and is easier to implement.Finally,a numerical example is given to demonstrate the effectiveness of the proposed approaches.

Adaptive State-feedback Stabilization for More General High-order Stochastic Nonlinear Systems

适应州反馈的稳定为在的高顺序的随机的非线性的系统的一个类被调查函数 fi 的上面的界限(?? 铄吗？？

Improvement for consensus performance of multi-agent systems based on delayed-state-derivative feedback

The delayed-state-derivative feedback （DSDF） is in- troduced into the existing consensus protocol to simultaneously improve the robustness to communication delay and accele- rate the convergence speed of achieving the consensus. The frequency-domain analysis, together with the algebra graph the- ory, is employed to derive the sufficient and necessary condition guaranteeing the average consensus. It is shown that introduc- ing the DSDF with the proper intensity in the existing consensus protocol can improve the robustness to communication delay. By analyzing the effect of DSDF on the closed-loop poles, this pa- per proves that for a supercritical-delay multi-agent system, this strategy can also accelerate the convergence speed of achieving the consensus with provided the proper intensity of the DSDE Simulations are provided to demonstrate the effectiveness of the theoretical results.

State Feedback Stabilzation for a Class of Time-delay Nonlinear Systems

The problem of global stabilization by state feedback for a class of time-delay nonlinear system is considered. By constructing the appropriate Lyapunov-Krasovskii functionals (LKF) and using the backstepping design, a linear state feedback controller making the closed-loop system globally asymptotically stable is constructed.

Robust Control System Design Using Proportional Plus Partial Derivative State Feedback

经由为矩阵对的概括特征值敏感问题的比例的正部分衍生物状态反馈和结果把线性系统基于为描述符建议的一般参量的 eigenstructure 赋值结果，到在开环的系统矩阵的使不安的元素的靠近环的特征值敏感的参量的表示被获得。为有在经由反馈当时是的比例的正部分衍生物状态的线性系统建议了的描述符的最小的敏感的特征值赋值的一个有效算法。算法不包含回到过程，并且允许靠近环的特征值方便地在需要的区域以内被优化。一个例子表明它的有效性和简洁。