Multi-objective robust controller synthesis for discrete-time systems with convex polytopic uncertain domain

Multi-objective robust state-feedback controller synthesis problems for linear discrete-time uncertain systems are addressed. Based on parameter-dependent Lyapunov functions, the Gl2 and GH2 norm expressed in terms of LMI (Linear Matrix Inequality) characterizations are further generalized to cope with the robust analysis for convex polytopic uncertain system. Robust state-feedback controller synthesis conditions are also derived for this class of uncertain systems. Using the above results, multi-objective state-feedback controller synthesis procedures which involve the LMI optimization technique are developed and less conservative than the existing one. An illustrative example verified the validity of the approach.

Neural Network Based Robust Controller for Trajectory Tracking of Underwater Vehicles

A robust neural network controller （NNC） is presented for tracking control of underwater vehicles with uncertainties. The controller is obtained by using backstepping technique and Lyapunov function design in combination with neural network identification. Modeling errors and environmental disturbances are considered in the mathematical model. A twolayer neural network is introduced to compensate the modeling errors, while H∞ control strategy is used to achieve the L2-gain performance. The uniformly ultimately bounded （UUB） stabilities of tracking errors and NN weights are guaran- teed through the proposed controller. An on-line NN weights tuning algorithm is also propesed. Good performances of the tracking control system are illustrated bv the results of numerical simulations.

Robust Controller Design for Satellite Attitude Tracking System

The attitude tracking control problem for a satellite with parameter uncertainties and external disturbances is considered in this paper. For this class of multi-input multi-output uncertain nonlinear systems, a design method of robust output tracking controllers is proposed based on the upper-bounds of the uncertainties. Using the input/output feedback linearization approach and Lyapunov method, a control law is designed, which guarantees that the system output exponentially tracks the given desired output. The proposed controller is easy to compute and complement. Simulation results show that, in the closed-loop system, precise attitude control is accomplished in spite of the uncertainties in the system.

Robust Controller Synthesis and Analysis in Inverter-Dominant Droop-Controlled Islanded Microgrids

This work investigates the problem of controller design for the inverters in an islanded microgrid.Robust-synthesis controllers and local droop controllers are designed to regulate the output voltages of inverters and share power among them,respectively.The designed controllers alleviate the need for additional sensors to measure the states of the system by relying only on output feedback.It is shown that the designed-synthesis controller properly damps resonant oscillations,and its performance is robust to the control-loop time delay and parameter uncertainties.The stability of a droop-controlled islanded microgrid including multiple distributed generation(DG)units is analyzed by linearizing the nonlinear power flow model around the nominal operating point and applying theorems from linear algebra.It is indicated that the droop controller stabilizes the microgrid system with dominantly inductive tie-line impedances for all values of resistive-inductive loads,while for the case of resistive-capacitive loads the stability is conditioned on an upper bound on the load susceptances.The robust performance of the designed-synthesis controller is studied analytically,compared with the similar analysis in an control(benchmark)framework,and verified by simulations for a four DG benchmark microgrid.Furthermore,the robustness of the droop controllers is analyzed by Monte Carlo simulations in the presence of local voltage fluctuations and phase differences among neighboring DGs.

Robust Controller Design of a Class of Uncertain Switched Fuzzy Systems with Delays

The robust control problem for a class of uncertain switched fuzzy systems with delays is investigated. Firstly,the model of the switched fuzzy system is presented and the parallel distributed compensation( PDC) technology is employed to design fuzzy controllers. Then, based on the convex combination method, a sufficient condition for robust stabilization in terms of linear matrix inequalities( LMIs) is obtained and a switching law is presented.Meanwhile,the Lyapunov-Krasovskii functional is taken to deal with time varying delays. Moreover,an algorithm is applied to finding a solution for a group of convex combination coefficient. Finally,a numerical example is given to demonstrate the effectiveness of the proposed method.

Design of Robust Controller for Flexible Joint Robot with Nonlinear Friction Characteristics

A robust controller method for flexible joint robot considering the effect caused by nonlinear friction was presented.The nonlinear friction was denoted as inverse additive output uncertainty relative to the nominal model in our work,based on which the describing function was analyzed in frequency domain,and the weighting function of nonlinear friction was further calculated as well. By combining the friction uncertainty,the mixed sensitivity H∞optimization was proposed as the benchmark for controller design, which also leaded to good performance of robustness. Furthermore,unstructured perturbation to the system was analyzed so that the stability was guaranteed. Simulation results show that the proposed controller can provide excellent tracking and regulation performance.

Design of a Fixed-Order Robust Controller to Damp Inter-Area Oscillations in Power Systems

This paper presents the design of a robust fixed-order H∞ controller to damp out the inter-area oscillations and to enhance the stability of the power system. The proposed H∞ approach is based on shaping the open-loop transfer function in the Nyquist diagram through minimizing the quadratic error between the actual and the desired open loop transfer functions in the frequency domain under linear constraints that guarantee robustness and stability. The proposed approach is robust with respect to multi-model uncertainty closed-loop sensitivity functions in the Nyquist diagram through the constraints on their infinity norm. The H∞ constraints are linearized with the help of a desired open-loop transfer function. The controller is designed using the convex optimization techniques in which the difference between the open-loop transfer function and the desired one is minimized. The two-area four-machine test system is selected to evaluate the performance of the designed controller under different load conditions as well as different levels of wind penetrations.

Integrated Fuzzy Robust Controller for Flight Control Design

μ-synthesis is a practical design approach and has been applied successfully to achieve a nominal and robust performance objectives. However, this design method suffers from the complexity of its practical implementation and high computational demand due to its high order dynamics. To overcome this problem, the interaction between fuzzy logic control which is a part of intelligence control theory and p-synthesis controller is carried out. This is called integrated fuzzy robust controller in this paper. It is obtained by coupling fuzzy pd with p-synthesis controller through the outer loop. Using this design strategy, we can keep the system performance and robustness even a high order p-synthesis controller is reduced into second order model. In order to test the effectiveness of this design method, the linear simulation results for a launch vehicle＇s attitude control motion are presented at the end of this paper.

Optimizing PID controller parameters for robust automatic voltage regulator system through indirect design approach-2

Automatic voltage regulators(AVR)are designed to manipulate a synchronous generator’s voltage level automatically.Proportional integral derivative(PID)controllers are typically used in AVR systems to regulate voltage.Although advanced PID tuning methods have been proposed,the actual voltage response differs from the theoretical predictions due to modeling errors and system uncertainties.This requires continuous fine tuning of the PID parameters.However,manual adjustment of these parameters can compromise the stability and robustness of the AVR system.This study focuses on the online self-tuning of PID controllers called indirect design approach-2(IDA-2)in AVR systems while preserving robustness.In particular,we indirectly tune the PID controller by shifting the frequency response.The new PID parameters depend on the frequency-shifting constant and the previously optimized PID parameters.Adjusting the frequency-shifting constant modifies all the PID parameters simultaneously,thereby improving the control performance and robustness.We evaluate the robustness of the proposed online PID tuning method by comparing the gain margins(GMs)and phase margins(PMs)with previously optimized PID parameters during parameter uncertainties.The proposed method is further evaluated in terms of disturbance rejection,measurement noise,and frequency response analysis during parameter uncertainty calculations against existing methods.Simulations show that the proposed method significantly improves the robustness of the controller in the AVR system.In summary,online self-tuning enables automated PID parameter adjustment in an AVR system,while maintaining stability and robustness.

Robust fault-tolerant controller design for linear time-invariant systems with actuator failures:an indirect adaptive method

In this paper,indirect adaptive state feedback control schemes are developed to solve the robust fault-tolerant control （FTC） design problem of actuator fault and perturbation compensations for linear time-invariant systems.A more general and practical model of actuator faults is presented.While both eventual faults on actuators and perturbations are unknown,the adaptive schemes are addressed to estimate the lower and upper bounds of actuator-stuck faults and perturbations online,as well as to estimate control effectiveness on actuators.Thus,on the basis of the information from adaptive schemes,an adaptive robust state feed-back controller is designed to compensate the effects of faults and perturbations automatically.According to Lyapunov stability theory,it is shown that the robust adaptive closed-loop systems can be ensured to be asymptotically stable under the influence of actuator faults and bounded perturbations.An example is provided to further illustrate the fault compensation effectiveness.

Robust Non-fragile PID Controller Design for the Stroke Regulation of Metering Pumps

This job focuses on the stroke regulation of a class of high-precision metering pumps.A parametertuning method of robust non-fragile PID（proportional-integral-derivative）controllers is proposed with the assumption that a PID controller has additive gain perturbations.An H-infinite robust PID controller can be obtained by solving a linear matrix inequality.This approach can guarantee that the closed-loop control systems is asymptotically stable and the H-infinite norm of the transfer function from the disturbance to the output of a controlled system is less than a given constant to attenuate disturbances.The simulation case shows that the control performance of the proposed strategy is significantly better than the traditional PID approach in the situation with perturbations of controller parameters.

New robust fault-tolerant controller for self-repairing flight control systems

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.The stability of the whole closed-loop system is analyzed.Feasibility and validity of the new controller is demonstrated with an aircraft simulation example.

H_∞ Robust Fault-Tolerant Controller Design for an Autonomous Underwater Vehicle’s Navigation Control System

In order to improve the security and reliability for autonomous underwater vehicle （AUV） navigation, an H∞ robust fault-tolerant controller was designed after analyzing variations in state-feedback gain Operating conditions and the design method were then analyzed so that the control problem could be expressed as a mathematical optimization problem. This permitted the use of linear matrix inequalities （LMI） to solve for the Hv controller for the system. When considering different actuator failures, these conditions were then also mathematically expressed, allowing the H∞ robust controller to solve for these events and thus be fault-tolerant. Finally, simulation results showed that the H∞ robust fault-tolerant controller could provide precise AUV navigation control with strong robustness.

Robust adaptive controller design for a class of nonlinear systems with unknown high frequency gains

In this note, a robust adaptive control scheme is proposed for a class of nonlinear systems that have unknown multi-plicative terms. Unlike previous results, except for the unknown control directions, we do not require a priori bounds on the unknown parameters. We also allow the unknown parameters to be time-varying provided that they are bounded. Our proposed robust adaptive controller is designed to identify on-line the unknown control directions and is a switching type controller, in which the controller parameters are tuned in a switching manner via a switching logic. Global stability of the closed-loop systems have been proved.

LMI Approach to Robust H_∞/H_2 Controller Design with Regional Poles Constraint of a Pump-Motor System

The time domain guideposts requirements of a pump-motor system is transfered into a series of constraints which express the robust performance upper bound and regional poles limits of the closed loop system. Then the servo system control problem is transferred into the problem of robust performance optimizing under regional poles constrains described by linear matrix inequality （LMI）. These LMIs are easy to solve through the Matlab LMI-toolbox. Simulations indicate that the controller has excellent dynamic, static and disturbance rejection performance, and the control system is robust and has perfect H2 performance to the bounded external torque disturbance.

ON THE ROBUSTNESS OF A GENERALIZED PREDICTIVE CONTROLLER

In this paper, we present a quantitative analysis of the robustness of a generalized predictive controller. The result of stability analysis shows that, under a specific bounded modelling error, the closed-loop system is BIBO stable in the presence of unmodelled dynamics.

Design of decentralized robust H_∞ state feedback controller

The design of decentralized robust H_∞ state feedback controller for large-scale interconnected systems with value bounded uncertainties existing in the state, control input and interconnected matrices was investigated. Based on the bounded real lemma a sufficient condition for the existence of a decentralized robust H_∞ state feedback controller was derived. This condition is expressed as the feasibility problem of a certain nonlinear matrix inequality. The controller, which makes the closed-loop large-scale system robust stable and satisfies the given H_∞ performance, is obtained by the offered homotopy iterative linear matrix inequality method. A numerical example is given to demonstrate the effectiveness of the proposed method.

Randomized Algorithms for Probabilistic Optimal Robust Performance Controller Design

Polynomial-time randomized algorithms were constructed to approximately solve optimal robust performance controller design problems in probabilistic sense and the rigorous mathematical justification of the approach was given. The randomized algorithms here were based on a property from statistical learning theory known as (uniform) convergence of empirical means (UCEM). It is argued that in order to assess the performance of a controller as the plant varies over a pre-specified family, it is better to use the average performance of the controller as the objective function to be optimized, rather than its worst-case performance. The approach is illustrated to be efficient through an example.

Robust H_∞ controller design for a class of nonlinear fuzzy time-delay systems

The problem of fuzzy modeling for state and input time-delays systems with a class of nonlinear uncertainties by fuzzy T-S model is addressed.By using the linear matrix inequality（LMI） method, the problem of fuzzy robust H ∞ controller design for the system is studied.Assuming that the nonlinear uncertain functions in the model considered are gain-bounded, a sufficient condition for the robustly asymptotic stability of the closed-loop system is obtained via Lyapunov stability theory.By solving the LMI, a feedback control law which guarantees the robustly asymptotic stability of the closed-loop system is constructed and the effect of the disturbance input on the controlled output is ruduced to a prescribed level.

Adaptive Robust Servo Control for Vertical Electric Stabilization System of Tank and Experimental Validation

A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevarying but bounded uncertainty within the vertical electric stabilization system:model parameter uncertainty and uncertain nonlinearity.First,the vertical electric stabilization system is constructed as an uncertain nonlinear dynamic system that can reflect the practical mechanics transfer process of the system.Second,the dynamical equation in the form of state space is established by designing the angular tracking error.Third,the comprehensive parameter of system uncertainty is designed to estimate the most conservative effects of uncertainty.Finally,an adaptive robust servo control which can effectively handle the combined effects of complex nonlinearity and uncertainty is proposed.The feasibility of the proposed control strategy under the practical physical condition is validated through the tests on the experimental platform.This paper pioneers the introduction of the internal nonlinearity and uncertainty of the vertical electric stabilization system into the settlement of the tracking stability control problem,and validates the advanced servo control strategy through experiment for the first time.