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.

An adaptive switching control approach for trajectory tracking of robotic manipulators

In order to design a suitable controller which can achieve accurate trajectory tracking and a good control performance, and guarantee the stability and robustness of a robot system due to external disturbances error and internal parameter variations, an adaptive switching control strategy is proposed. The proposed scheme is designed under the condition of bounded distances and consists of an adaptive switching law and a PD controller. Based on the Lyapunov stability theory, it is proved that the proposed scheme can guarantee the tracking performance of the robotic manipulator and is adapted to varying unknown loads. Simulations are carded out on a two-link robotic manipulator, which illustrate the feasibility and validity of the proposed control scheme and the robustness for variational payloads.

Polytopic LPV modeling and gain-scheduled switching control for a flexible air-breathing hypersonic vehicle

A novel gain-scheduled switching control method for the longitudinal motion of a flexible air-breathing hypersonic vehicle （FAHV） is proposed. Firstly, velocity and altitude are selected as scheduling variables, a polytopic linear parameter varying （LPV） model is developed to represent the complex nonlinear longitudinal dynamics of the FAHV. Secondly, based on the obtained polytopic LPV model, the flight envelope is divided into four smaller subregions, and four gain-scheduled controllers are designed for these parameter subregions. Then, by the defined switching characteristic function, these gain-scheduled controllers are switched in order to guarantee the closed-loop FAHV system to be asymptotically stable and satisfy a given tracking error performance criterion. The condition of gain-scheduled switching controller synthesis is given in terms of linear matrix inequalities （LMIs） which can be easily solved by using standard software packages. Finally, simulation results show the effectiveness of the presented method.

Planning and Control of COP-Switch-Based Planar Biped Walking

Efficient walking is one of the main goals of researches on biped robots. A feasible way is to translate the understanding from human walking into robot walking, for example, an artificial control approach on a human like walking structure. In this paper, a walking pattern based on Center of Pressure （COP） switched and modeled after human walking is introduced firstly. Then, a parameterization method for the proposed walking gait is presented. In view of the complication, a multi-space planning method which divides the whole planning task into three sub-spaces, including simplified model space, work space and joint space, is proposed. Furthermore, a finite-state-based control method is also developed to implement the proposed walking pattern. The state switches of this method are driven by sensor events. For convincing verification, a 2D simulation system with a 9-1ink planar biped robot is developed. The simulation results exhibit an efficient walking gait.

Exponential stabilization of networked control systems and design of switching controller

This paper deals with the problem of switching between an open-loop estimator and a close-loop estimator for compensating transmission error and packet dropout of networked control systems. Switching impulse is considered in order to reduce the error between theory and application, a sufficient condition for exponential stabilization of networked control systems under a given switching rule is presented by multiple Lyapunov-like functions. These results are presented for both continuous-time and discrete-time domains. Controllers are designed by means of linear matrix inequalities. Sim- ulation results show the feasibility and efficiency of the proposed method.

High-speed Nonsingular Terminal Switched Sliding Mode Control of Robot Manipulators

This paper proposes a high-speed nonsingular terminal switched sliding mode control(HNT-SSMC) strategy for robot manipulators. The proposed approach enhances the control system performance by switching among appropriate sliding mode controllers according to different control demands in different regions of the state space. It is shown that the highspeed nonsingular terminal switched sliding mode(HNT-SSM)which is the representation of different control demands and enforced by the HNT-SSMC has the property of global highspeed convergence compared with the nonsingular fast terminal sliding mode(NFTSM), and provides the global non-singularity.The simulation study of an application example is carried out to validate the effectiveness of the proposed strategy.

Hierarchical Switching Control of Multiple Models Based on Robust Control Theory

A new hierarchical switching control system of multiple models based on robust control theory is designed for some plant with large uncertainties. The model set and controller set are designed by robust control theory and the characteristics of robust control system are taken into account. A new kind of switching index function by estimating uncertainty is designed. Furthermore, stability of the closed system is analyzed by the small gain theorem in the sense of exponentially weighted L2 norm. And simulation is done on a plant with both parameter uncertainty and un-modeled dynamics. Both theoretical analysis and simulation results show that this new hierarchical switching control system can control the plant with large uncertainties effectively and has good performance of tracking and stability.

Control of switched systems with actuator saturation

This paper is concerned with controller synthesis for linear switched systems with actuator saturation. Based on common Lyapunov function technique and multiple-Lyapunov function technique, two methods for designing state feedback controller are proposed respectively in terms of linear matrix inequalities for the switched systems with saturation. An approach on enlarging the attractive domain is then investigated, The application of the presented approach is illustrated finally by a numerical example.

A low noise charge sensitive preamplifier with switch control feedback resistance

In this paper, the design and analysis of a new low noise charge sensitive preamplifier for silicon strip, Si(Li), CdZnTe and CsI detectors etc. with switch control feedback resistance were described, the entire system to be built using the CMOS transistors. The circuit configuration of the CSP proposed in this paper can be adopted to develop CMOS-based Application Specific Integrated Circuit further for Front End Electronics of read-out system of nuclear physics, particle physics and astrophysics research, etc. This work is an implemented design that we succeed after a simulation to obtain a rise time less than 3ns, the output resistance less than 94? and the linearity almost good.

Fault diagnosis method for switch control circuit based on SVM-AdaBoost

In order to realize the fault diagnosis of the control circuit of all-electronic computer interlocking system(ACIS)for railway signals,taking a five-wire switch electronic control module as an research object,we propose a method of selecting the sample set of the basic classifier by roulette method and realizing fault diagnosis by using SVM-AdaBoost.The experimental results show that the proportion of basic classifier samples affects classification accuracy,which reaches the highest when the proportion is 85%.When selecting the sample set of basic classifier by roulette method,the fault diagnosis accuracy is generally higher than that of the maximum weight priority method.When the optimal proportion 85%is taken,the accuracy is highest up to 96.3%.More importantly,this way can better adapt to the critical data and improve the anti-interference ability of the algorithm,and therefore it provides a basis for fault diagnosis of ACIS.

Iterative Learning Control for a Class of Linear Discrete-time Switched Systems

在这份报纸，反复的学习控制(ILC ) 与任意的切换的信号为线性分离时间的交换系统的一个类被考虑。交换系统重复地在有限时间间隔期间被操作，这被假定，然后第一个顺序 P 类型 ILC 计划能被用来完成完美的追踪在上自始至终间隔。由超级向量途径，为在重复领域的如此的 ILC 系统的一个集中条件能被给。理论分析被模拟支持。

Adaptive switching control of discrete time nonlinear systems based on multiple models

We use the approach of “optimal” switching to design the adaptive control because the design among multiple models is intuitively more practically feasible than the traditional adaptive control in improving the performances. We prove that for a typical class of nonlinear systems disturbed by random noise, the multiple model adaptive switching control based on WLS (Weighted Least Squares) or projected-LS (Least Squares) is stable and convergent.

Extended state observer based smooth switching control for tilt-rotor aircraft

A tilt-rotor aircraft has three flight modes: helicopter mode, airplane mode and conversion mode. Unlike the traditional aircraft, the tilt-rotor aircraft, which combines the characteristics of helicopters and fixed-wing aircraft, is a complex multi-body system with the violent variation of the aerodynamic parameters. For these characteristics, a new smooth switching control scheme is provided for the tilt-rotor aircraft. First, the reference commands for airspeed and nacelle angles are calculated by analyzing the conversion corridor and the conversion path. Subsequently, based on the finite-time switching theorem, an average dwell time condition is designed to guarantee the stability in the switching process. Besides, considering the state vibrations and bumps may appear in switching points, the fuzzy weighted logic is employed to improve the system transient performance. For disturbance rejection, three extended state observers are designed separately to estimate the disturbances in the switched systems. Compared with the traditional auto disturbance rejection control and proportion integration differentiation control, this method overcomes the conservatism of wasting the whole model information. The control performances of robustness and smoothness are verified with simulation, which shows that the new smooth switching control scheme is more targeted and superior than the traditional design method.

Observer-based robust H-infinity control for uncertain switched systems

The problem of observer-based robust H-infinity control is addressed for a class of linear discrete-time switched systems with time-varying norm-bounded uncertainties by using switched Lyapunov function method. None of the individual subsystems is assumed to be robustly H-infinity solvable. A novel switched Lypunov function matrix with diagonal-block form is devised to overcome the difficulties in designing switching laws. For robust H-infinity stability analysis, two linear-matrix-inequality-based sufficient conditions are derived by only using the smallest region function strategy if some parameters are preselected. Then, the robust H-infinity control synthesis is studied using a switching state feedback and an observer-based switching dynamical output feedback. All the switching laws are simultaneously constructively designed. Finally, a simulation example is given to illustrate the validity of the results.

A switched system approach to stabilization of networked control systems

A switched system approach is proposed to model networked control systems （NCSs） with communication constraints. This enables us to apply the rich theory of switched systems to analyzing such NCSs. Sufficient conditions are presented on the stabilization of NCSs. Stabilizing state/output feedback controllers can be constructed by using the feasible solutions of some linear matrix inequalities （LMIs）. The merit of our proposed approach is that the behavior of the NCSs can be studied by considering switched system without augmenting the system. A simulation example is worked out to illustrate the effectiveness of the proposed approach.

Multi-objective nonlinear model predictive control through switching cost functions and its applications to chemical processes

This paper proposes a switching multi-objective model predictive control(MOMPC) algorithm for constrained nonlinear continuous-time process systems.Different cost functions to be minimized in MPC are switched to satisfy different performance criteria imposed at different sampling times.In order to ensure recursive feasibility of the switching MOMPC and stability of the resulted closed-loop system,the dual-mode control method is used to design the switching MOMPC controller.In this method,a local control law with some free-parameters is constructed using the control Lyapunov function technique to enlarge the terminal state set of MOMPC.The correction term is computed if the states are out of the terminal set and the free-parameters of the local control law are computed if the states are in the terminal set.The recursive feasibility of the MOMPC and stability of the resulted closed-loop system are established in the presence of constraints and arbitrary switches between cost functions.Finally,implementation of the switching MOMPC controller is demonstrated with a chemical process example for the continuous stirred tank reactor.

Optimization problems for switched systems with impulsive control

By using Impulsive Maximum Principal and three stage optimization method,this paper discusses optimization problems for linear impulsive switched systems with hybridcontrols, which includes continuous control and impulsive control. The linear quadratic optimizationproblems without constraints such as optimal hybrid control, optimal stability and optimalswitching instants are addressed in detail. These results are applicable to optimal control problemsin economics,mechanics, and management.

Iterative Learning Control for a Class of Linear Continuous-time Switched Systems with Fixed Initial Shifts

This paper deals with the problem of iterative learning control for a class of linear continuous-time switched systems in the presence of a fixed initial shift. Here, the considered switched systems are operated during a finite time interval repetitively. According to the characteristics of the systems, a PD-type learning scheme is proposed for such switched systems with arbitrary switching rules, and the corresponding output limiting trajectories under the action of the PD-type learning scheme are given. Based on the contraction mapping method, it is shown that this scheme can guarantee the outputs of the systems converge uniformly to the output limiting trajectories of the systems over the whole time interval. Furthermore, the initial rectifying strategies are applied to the systems for eliminating the effect of the fixed initial shift. When the learning scheme is applied to the systems, the outputs of the systems can converge to the desired reference trajectories over a pre-specified interval. Finally, simulation examples illustrate the effectiveness of the proposed method.

Investigation into the Independent Metering Control Performance of a Twin Spools Valve with Switching Technology-controlled Pilot Stage

In hydraulic area,independent metering control(IMC)technology is an effective approach to improve system efficiency and control flexibility.In addition,digital hydraulic technology(DHT)has been verified as a reasonable method to optimize system dynamic performance.Integrating these two technologies into one component can combine their advantages together.However,few works focused on it.In this paper,a twin spools valve with switching technologycontrolled pilot stage(TSVSP)is presented,which applied DHT into its pilot stage while appending IMC into its main stage.Based on this prototype valve,a series of numerical and experiment analysis of its IMC performance with both simulated load and excavator boom cylinder are carried out.Results showed fast and robust performance of pressure and flow compound control with acceptable fluctuation phenomenon caused by switching technology.Rising time of flow response in excavator cylinder can be controlled within 200 ms,meanwhile,the recovery time of rod chamber pressure under suddenly changed condition is optimized within 250 ms.IMC system based on TSVSP can improve both dynamic performance and robust characteristics of the target actuator so it is practical in valve-cylinder system and can be applied in mobile machineries.

Nonlinear adaptive switching control for a class of non-affine nonlinear systems

An improved nonlinear adaptive switching control method is presented to relax the assumption on the higher order nonlinear terms of a class of discrete-time non-affine nonlinear systems. The proposed control strategy is composed of a linear adaptive controller, a neural network(NN) based nonlinear adaptive controller and a switching mechanism. An incremental model is derived to represent the considered system and an improved robust adaptive law is chosen to update the parameters of the linear adaptive controller. A new performance criterion of the switching mechanism is designed to select the proper controller. Using this control scheme, all the signals in the system are proved to be bounded. Numerical examples verify the effectiveness of the proposed algorithm.