A new robust fault-tolerant controller for self-repairing flight control system

A new robust fault-tolerant controller scheme integrating a main controller and a compensator for the self-repairing flight control system is discussed. The main controller is designed for high performance of the original faultless system. The compensating controller can be seen as a standalone loop added to the system to compensate the effects of fault guaranteeing the stability of the system. A design method is proposed using nonlinear dynamic inverse control as the main controller and nonlinear extended state observer-based compensator. System robustness is greatly improved by using the new configuration controller. The stability of the whole closed-loop system is analyzed. Feasibility and validity of the new controller is demonstrated with an aircraft simulation example.     

Tracking controller design for random nonlinear benchmark system

This paper considers a benchmark system consisting of a rolling ball and a moving car in the oscillating surroundings. By using the Lagrange law, the dynamic model without disturbance is first constructed, then according to the relative motion principle, random oscillation of surroundings is transformed into the random noises in the constructed Lagrange equation. The special structure of the quasi-lower triangle of Lagrange equation motivates us to pay more attention to the vectorial backstepping technique. By selecting an appropriate Lyapunov-like function, a tracking controller with tunable parameters is designed such that all signals of the closed-loop system are bounded and track error can be made arbitrarily small.     

Synergetic governing controller design for the hydraulic turbine governing system with complex conduit system

The hydraulic turbine governing system plays an indispensable role in maintaining the stability of electrical power system. In this paper, synergetic control theory is introduced to enhance the regulating ability of the hydraulic turbine governing system. For the purpose of describing the characteristics of objective system and deducing the synergetic control rule, a nonlinear mathematic model of a hydraulic turbine governing system with long tail race and two surge tanks is established. Furthermore, the nonlinear characteristic of the hydraulic turbine is described by six variable partial derivatives. For further investigation, the hydraulic turbine governing system is conducted to running under load condition when its coaxial generator connects to an infinite bus. Simulation experiments have been made under both load disturbance and three-phase short circuit fault conditions to compare the dynamic performances of proposed synergetic governing controller and classic PID controller. The results indicate that the proposed synergetic governing controller is an effective alternative in normal condition and a superior one in emergency. Moreover, the robustness of synergetic governing controller has also been discussed at the end of this paper.     

Optimal synchronization controller design for complex dynamical networks with unknown system dynamics

In this paper, the optimal synchronization controller design problem for complex dynamical networks with unknown system internal dynamics is studied. A necessary and sufficient condition on the existence of the optimal control minimizing a quadratic performance index is given. The optimal control law consists of a feedback control and a compensated feedforward control, and the feedback control gain can be obtained by solving the well-known Algebraic Riccati Equation (ARE). Especially, in the presence of unknown system dynamics, a novel adaptive iterative algorithm using the information of system states and inputs is proposed to solve the ARE to get the optimal feedback control gain. Finally, a simulation example shows the effectiveness of the theoretical results.     

一个系统内部跨地区广域网的规划与设计

本文系统地介绍了如何利用IIS、Enterprise server等软件知识,并结合DDN专线、路由器、光缆、双绞线和X.25平台等硬件技术建设一个行业或系统内部跨地区的广域网络.并基本实现远程访问、资料共享、办公自动化、网络会议和网络培训等功能.     

Sliding mode controller design for linear systems with unmeasured states

This paper addresses the optimal controller problem for a linear system over linear observations with respect to different Bolza–Meyer criteria, where (1) the integral control and state energy terms are quadratic and the non-integral term is of the first degree or (2) the control energy term is quadratic and the state energy terms are of the first degree. The optimal solutions are obtained as sliding mode controllers, each consisting of a sliding mode filter and a sliding mode regulator, whereas the conventional feedback LQG controller fails to provide a causal solution. Performance of the obtained optimal controllers is verified in the illustrative example against the conventional LQG controller that is optimal for the quadratic Bolza–Meyer criterion. The simulation results confirm an advantage in favor of the designed sliding mode controllers.     

Direct synthesis-based controller design for integrating processes with time delay

Using the direct synthesis method, a PID controller in series with a lead/lag compensator is designed for control of open loop integrating processes with time delay. Set-point weighting is considered for reducing the undesirable overshoot. Guidelines are provided for selection of the desired closed loop tuning parameter in the direct synthesis method and set point weighting parameter. The method gives significant load disturbance rejection performances. Illustrative examples are considered to show the performances of the proposed method. Significant improvement is obtained when compared to recently reported methods.     

Passive fuzzy controller design for nonlinear systems with multiplicative noises

This paper proposes a passive fuzzy controller design methodology for nonlinear system with multiplicative noises. Applying the Itô's formula and the sense of mean square, the sufficient conditions are developed to analyze the stability and to design the controller for stochastic nonlinear systems which are represented by the Takagi-Sugeno (T-S) fuzzy models. The sufficient conditions derived in this paper belong to the Linear Matrix Inequality (LMI) forms which can be solved by the convex optimal programming algorithm. Besides, the passivity theory is applied to discuss the effect of external disturbance on system. Finally, some numerical simulation examples are provided to demonstrate the applications of the proposed fuzzy controller design technique.     

Adaptive fuzzy output feedback controller design for a HAGC system with input saturation and output error constraints

The comprehensive effect of external disturbance, measurement delay, unmeasurable states and input saturation makes the difficulties and challenges for a HAGC system. In this paper, an adaptive fuzzy output feedback control scheme is designed for a HAGC system under the simultaneous consideration of those factors. At the first place, by state transformation technique, the dynamic model of a HAGC system is simply expressed as a strict feedback form, where measurement delay is converted into input delay. Then, an auxiliary system is employed to compensate for the effect of input delay. Furthermore, an asymmetric barrier Lyapunov function (BLF) is constructed to ensure the output error constraint requirement of thickness error and the fuzzy observer is established to solve unmeasurable states, unknown nonlinear functions at the same time. With the aid of backstepping method, adaptive fuzzy controller is developed to assure that the closed-loop system is semi-globally boundedness and the output error of thickness error doesn’t violate its constraint. At the end, compared simulations are carried out to verify the efficiency of the proposed control scheme.     

Optimal location and controller design of STATCOM for power system stability improvement using PSO

The optimal location of a static synchronous compensator (STATCOM) and its coordinated design with power system stabilizers (PSSs) for power system stability improvement are presented in this paper. First, the location of STATCOM to improve transient stability is formulated as an optimization problem and particle swarm optimization (PSO) is employed to search for its optimal location. Then, coordinated design problem of STATCOM-based controller with multiple PSS is formulated as an optimization problem and optimal controller parameters are obtained using PSO. A two-area test system is used to show the effectiveness of the proposed approach for determining the optimal location and controller parameters for power system stability improvement. The nonlinear simulation results show that optimally located STATCOM improves the transient stability and coordinated design of STATCOM-based controller and PSSs improve greatly the system damping. Finally, the coordinated design problem is extended to a four-machine two-area system and the results show that the inter-area and local modes of oscillations are well damped with the proposed PSO-optimized controllers.     

Correntropy based model predictive controller with multi-constraints for robust path trajectory tracking of self-driving vehicle

Self-driving vehicles must be equipped with path tracking capability to enable automatic and accurate identification of the reference path. Model Predictive Controller (MPC) is an optimal control method that has received considerable attention for path tracking, attributed to its ability to handle control problems with multiple constraints. However, if the data acquired for determining the reference path is contaminated by non-Gaussian noise and outliers, the tracking performance of MPC would degrades significantly. To this end, Correntropy-based MPC (CMPC) is proposed in this paper to address the issue. Different from the conventional MPC model, the objective of CMPC is constructed using the robust metric Maximum Correntropy Criterion (MCC) to transform the optimization problem of MPC to a non-concave problem with multiple constraints, which is then solved by the Block Coordinate Update (BCU) framework. To find the solution efficiently, the linear inequality constraints of CMPC are relaxed as a penalty term. Furthermore, an iterative algorithm based on Fenchel Conjugate (FC) and the BCU framework is proposed to solve the relaxed optimization problem. It is shown that both objective sequential convergence and iterate sequence convergence are satisfied by the proposed algorithm. Simulation results generated by CarSim show that the proposed CMPC has better performance than conventional MPC in path tracking when noise and outliers exist.     

Linear controller analysis and design for systems with input hystereses nonlinearities

An output feedback control analysis and design framework for linear systems with input hystereses nonlinearities is developed. Specifically, by transforming the hystereses nonlinearities into dissipative input-output dynamical operators, dissipativity theory is used to analyze and design linear controllers for systems with hysteretic actuators. The overall framework guarantees partial asymptotic stability of the closed-loop system; that is, asymptotic stability with respect to part of the closed-loop system state associated with the plant and the controller. Furthermore, the remainder of the state associated with the hysteresis dynamics is shown to be semistable; that is, solutions of the hysteretic system converge to Lyapunov stable equilibrium points determined by the system initial conditions.     

Sliding mode controller design for linear stochastic systems with unknown parameters

This paper presents the sliding mode mean-square and mean-module controllers for linear stochastic systems with unknown parameters. In both cases, the controller equations are obtained using the separation principle, whose applicability to the considered problem is substantiated. Performance of the obtained controllers is verified in the illustrative example against the sliding mode mean-square and sliding mode controllers that are optimal for linear systems with known parameters. Simulation graphs demonstrating overall performance and computational accuracy of the designed optimal controller are included.     

Event-triggered controller design for positive T-S fuzzy systems with random time-delay

This paper is concerned with the design of event-triggered controller for positive Takagi-Sugeno (T-S) fuzzy systems with a random time-delay. The random time-delay is described as a Markov process. A controller switched at different event-triggered instant is proposed. By constructing a new event-triggered instant-dependent linear co-positive Lyapunov function, the design criteria of event-triggered controller is derived to ensure the positivity and stability of the closed-loop system. These criteria can be solved by linear programming (LP) technique. A positive lower bound on the inter-execution time is ensured, which means that there is Zeno-free phenomenon. Finally, the simulation has demonstrated the effectiveness and merit of the proposed results.     

A robust vector control for induction motor drives with an adaptive sliding-mode control law

A novel adaptive sliding-mode control system is proposed in order to control the speed of an induction motor drive. This design employs the so-called vector (or field oriented) control theory for the induction motor drives. The sliding-mode control is insensitive to uncertainties and presents an adaptive switching gain to relax the requirement for the bound of these uncertainties. The switching gain is adapted using a simple algorithm which does not imply a high computational load. Stability analysis based on Lyapunov theory is also performed in order to guarantee the closed loop stability. Finally, simulation results show not only that the proposed controller provides high-performance dynamic characteristics, but also that this scheme is robust with respect to plant parameter variations and external load disturbances.     

A PI controller configuration for robust control of a class of nonlinear systems

The PI control configuration for stabilization and signal tracking of nonlinear systems is investigated. Semiglobal asymptotic stability and semiglobal practical signal tracking of the controlled system are proven using results from the theory of nonlinear singularly perturbed systems.     

Adaptive controller design for spacecraft formation flying using sliding mode controller and neural networks

A spacecraft formation flying controller is designed using a sliding mode control scheme with the adaptive gain and neural networks. Six-degree-of-freedom spacecraft nonlinear dynamic model is considered, and a leader–follower approach is adopted for efficient spacecraft formation flying. Uncertainties and external disturbances have effects on controlling the relative position and attitude of the spacecrafts in the formation. The main benefit of the sliding mode control is the robust stability of the closed-loop system. To improve the performance of the sliding mode control, an adaptive controller based on neural networks is used to compensate for the effects of the modeling error, external disturbance, and nonlinearities. The stability analysis of the closed-loop system is performed using the Lyapunov stability theorem. A spacecraft model with 12 thrusts as actuators is considered for controlling the relative position and attitude of the follower spacecraft. Numerical simulation results are presented to show the effectiveness of the proposed controller.     

A novel controller design and evaluation for networked control systems with time-variant delays

A new delayed state-variable model for networked control systems is presented, upon which a linear quadratic regulator (LQR) is designed. A method of delays-estimation online is also given. A fuzzy logic with LQR controller is addressed for the difficulty on implementation of LQR in networked control systems (NCSs) with time-variant delays. Simulation results prove that the novel controller can make the system stable and robustly preserve the performance in terms of time-variant delays.     

Reachable set estimation and controller design for distributed delay systems with bounded disturbances

This paper is concerned with the problems of reachable set estimation and state-feedback controller design for linear systems with distributed delays and bounded disturbance inputs. The disturbance inputs are assumed to be either unit-energy bounded or unit-peak bounded. First, based on the Lyapunov–Krasovskii functional approach and the delay-partitioning technique, delay-dependent conditions for estimating the reachable set of the considered system are derived. These conditions guarantee the existence of an ellipsoid that contains the system state under zero initial conditions. Second, the reachable set estimation is taken into account in the controller design. Here, the purpose is to determine an ellipsoid and find a state-feedback controller such that the determined ellipsoid contains the reachable set of the resulting closed-loop system. Sufficient conditions for the solvability of the control synthesis problem are obtained. Based on these results, the problem of how to design a controller such that the state of the resulting closed-loop system is contained in a prescribed ellipsoid is studied. Finally, numerical examples and simulation results are provided to show the effectiveness of the proposed analysis and design methods.     

A robust distributed observer design for Lipschitz nonlinear systems with time-varying switching topology

This paper deals with state estimation for a class of Lipschitz nonlinear systems under a time-varying disconnected communication network. A distributed observer consists of some local observers that are connected to each other through a communication network. We consider a situation where a communication network does not remain connected all the time, and the network may be caused by intermittent communication link failure. Moreover, each local observer has access to a local measurement, which may be insufficient to ensure the system’s observability, but the collection of all measurements in the network ensures observability. In this condition, the purpose is to design a distributed observer where the estimated state vectors of all local observers converge to the state vector of the system asymptotically, while local observers exchange estimated state vectors through a communication network and use their local measurements. According to theoretical analysis, a nonlinear and a robust nonlinear distributed observer exist when in addition to the union of all communication topologies being strongly connected during a time interval, the component of each communication graph is also strongly connected during each subinterval. The existence conditions of the distributed observers are derived in terms of a set of linear matrix inequalities (LMIs). Finally, the effectiveness of the presented method is numerically verified using some simulation examples.