Showing papers on "Robust control published in 2012"

Randomized Algorithms for Analysis and Control of Uncertain Systems: With Applications

Abstract: The presence of uncertainty in a system description has always been a critical issue in control. The main objective of Randomized Algorithms for Analysis and Control of Uncertain Systems, with Applications (Second Edition) is to introduce the reader to the fundamentals of probabilistic methods in the analysis and design of systems subject to deterministic and stochastic uncertainty. The approach propounded by this text guarantees a reduction in the computational complexity of classical control algorithms and in the conservativeness of standard robust control techniques. The second edition has been thoroughly updated to reflect recent research and new applications with chapters on statistical learning theory, sequential methods for control and the scenario approach being completely rewritten. Features: self-contained treatment explaining Monte Carlo and Las Vegas randomized algorithms from their genesis in the principles of probability theory to their use for system analysis; development of a novel paradigm for (convex and nonconvex) controller synthesis in the presence of uncertainty and in the context of randomized algorithms; comprehensive treatment of multivariate sample generation techniques, including consideration of the difficulties involved in obtaining identically and independently distributed samples; applications of randomized algorithms in various endeavours, such as PageRank computation for the Google Web search engine, unmanned aerial vehicle design (both new in the second edition), congestion control of high-speed communications networks and stability of quantized sampled-data systems. Randomized Algorithms for Analysis and Control of Uncertain Systems (second edition) is certain to interest academic researchers and graduate control students working in probabilistic, robust or optimal control methods and control engineers dealing with system uncertainties. The present book is a very timely contribution to the literature. I have no hesitation in asserting that it will remain a widely cited reference work for many years. M. Vidyasagar

Quadrotor vehicle control via sliding mode controller driven by sliding mode disturbance observer

Abstract: Over the last decade, considerable interest has been shown from industry, government and academia to the design of Vertical Take-Off and Landing (VTOL) autonomous aerial vehicles. This paper uses the recently developed sliding mode control driven by sliding mode disturbance observer (SMC-SMDO) approach to design a robust flight controller for a small quadrotor vehicle. This technique allows for a continuous control robust to external disturbance and model uncertainties to be computed without the use of high control gain or extensive computational power. The robustness of the control to unknown external disturbances also leads to a reduction of the design cost as less pre-flight analyses are required. The multiple-loop, multiple time-scale SMC-SMDO flight controller is designed to provide robust position and attitude control of the vehicle while relying only on knowledge of the limits of the disturbances. Extensive simulations of a 6 DOF computer model demonstrate the robustness of the control when faced with external disturbances (including wind, collision and actuator failure) as well as model uncertainties.

A Compact Rotary Series Elastic Actuator for Human Assistive Systems

Abstract: Precise and large torque generation, back drivability, low output impedance, and compactness of hardware are important requirements for human assistive robots. In this paper, a compact rotary series elastic actuator (cRSEA) is designed considering these requirements. To magnify the torque generated by an electric motor in the limited space of the compact device, a worm gear is utilized. However, the actual torque amplification ratio provided by the worm gear is different from the nominal speed reduction ratio due to friction, which makes the controller design challenging. In this paper, the friction effect is considered in the model of cRSEA, and a robust control algorithm is designed to precisely control the torque output in the presence of nonlinearities such as the friction. The mechanical design and dynamic model of the proposed device and the design of a robust control algorithm are discussed, and actuation performance is verified by experiments. Experimental results with a human subject are also presented to show the performance of the cRSEA while interacting with humans.

Second-Order Sliding Mode Control of a Doubly Fed Induction Generator Driven Wind Turbine

Abstract: This paper deals with power extraction maximization of a doubly fed induction generator (DFIG)-based wind turbine. These variable speed systems have several advantages over the traditional wind turbine operating methods, such as the reduction of the mechanical stress and an increase in the energy capture. To fully exploit this latest advantage, many control schemes have been developed for maximum power point tracking (MPPT) control schemes. In this context, this paper proposes a second-order sliding mode to control the wind turbine DFIG according to references given by an MPPT. Traditionally, the desired DFIG torque is tracked using control currents. However, the estimations used to define current references drive some inaccuracies mainly leading to nonoptimal power extraction. Therefore, using robust control, such as the second-order sliding mode, will allow one to directly track the DFIG torque leading to maximum power extraction. Moreover, the proposed control strategy presents attractive features such as chattering-free behavior (no extra mechanical stress), finite reaching time, and robustness with respect to external disturbances (grid) and unmodeled dynamics (generator and turbine). Simulations using the wind turbine simulator FAST and experiments on a 7.5-kW real-time simulator are carried out for the validation of the proposed high-order sliding mode control approach.

Robust Control: The Parameter Space Approach

Abstract: * Parametric Plants and Controllers: A Crane Example * Boundary Crossing and Parameter Space Approach * Eigenvalue Specifications * Boundary Mapping in Parameter Space * Frequency Domain Analysis and Design * Case Studies in Car Steering * Case Studies in Flight Control * Robustness Analysis by Value Sets * Values Sets for Non-linear Co-efficient Functions * The Stability Radius * Robustness of Sampled-Data Control Systems A Polynominals and Polynominals Equations, Resultant Method B Introduction to PARADISE Bibliography

Persistent Robotic Tasks: Monitoring and Sweeping in Changing Environments

Abstract: In this paper, we present controllers that enable mobile robots to persistently monitor or sweep a changing environment. The environment is modeled as a field that is defined over a finite set of locations. The field grows linearly at locations that are not within the range of a robot and decreases linearly at locations that are within range of a robot. We assume that the robots travel on given closed paths. The speed of each robot along its path is controlled to prevent the field from growing unbounded at any location. We consider the space of speed controllers that are parametrized by a finite set of basis functions. For a single robot, we develop a linear program that computes a speed controller in this space to keep the field bounded, if such a controller exists. Another linear program is derived to compute the speed controller that minimizes the maximum field value over the environment. We extend our linear program formulation to develop a multirobot controller that keeps the field bounded. We characterize, both theoretically and in simulation, the robustness of the controllers to modeling errors and to stochasticity in the environment.

A Decentralized Robust Control Strategy for Multi-DER Microgrids—Part I: Fundamental Concepts

Abstract: This paper presents fundamental concepts of a central power-management system (PMS) and a decentralized, robust control strategy for autonomous mode of operation of a microgrid that includes multiple distributed energy resource (DER) units. The DER units are interfaced to the utility grid through voltage-sourced converters (VSCs). The frequency of each DER unit is specified by its independent internal oscillator and all oscillators are synchronized by a common time-reference signal received from a global positioning system. The PMS specifies the voltage set points for the local controllers. A linear, time-invariant, multivariable, robust, decentralized, servomechanism control system is designed to track the set points. Each control agent guarantees fast tracking, zero steady-state error, and robust performance despite uncertainties of the microgrid parameter, topology, and the operating point. The theoretical concept of the proposed control strategy, including the existence conditions, design of the controller, robust stability analysis of the closed-loop system, time-delay tolerance, tolerance to high-frequency effects and its gain-margins, are presented in this Part I paper. Part II reports on the performance of the control strategy based on digital time-domain simulation and hardware-in-the-loop case studies.

Fuzzy-Model-Based Robust Fault Detection With Stochastic Mixed Time Delays and Successive Packet Dropouts

Abstract: This paper is concerned with the network-based robust fault detection problem for a class of uncertain discrete-time Takagi-Sugeno fuzzy systems with stochastic mixed time delays and successive packet dropouts. The mixed time delays comprise both the multiple discrete time delays and the infinite distributed delays. A sequence of stochastic variables is introduced to govern the random occurrences of the discrete time delays, distributed time delays, and successive packet dropouts, where all the stochastic variables are mutually independent but obey the Bernoulli distribution. The main purpose of this paper is to design a fuzzy fault detection filter such that the overall fault detection dynamics is exponentially stable in the mean square and, at the same time, the error between the residual signal and the fault signal is made as small as possible. Sufficient conditions are first established via intensive stochastic analysis for the existence of the desired fuzzy fault detection filters, and then, the corresponding solvability conditions for the desired filter gains are established. In addition, the optimal performance index for the addressed robust fuzzy fault detection problem is obtained by solving an auxiliary convex optimization problem. An illustrative example is provided to show the usefulness and effectiveness of the proposed design method.

Observer-Based Piecewise Affine Output Feedback Controller Synthesis of Continuous-Time T–S Fuzzy Affine Dynamic Systems Using Quantized Measurements

Abstract: This paper is concerned with the problem of robust H∞ output feedback control for a class of continuous-time Takagi-Sugeno (T-S) fuzzy affine dynamic systems using quantized measurements. The objective is to design a suitable observer-based dynamic output feedback controller that guarantees the global stability of the resulting closed-loop fuzzy system with a prescribed H∞ disturbance attenuation level. Based on common/piecewise quadratic Lyapunov functions combined with S-procedure and some matrix inequality convexification techniques, some new results are developed to the controller synthesis for the underlying continuous-time T-S fuzzy affine systems with unmeasurable premise variables. All the solutions to the problem are formulated in the form of linear matrix inequalities (LMIs). Finally, two simulation examples are provided to illustrate the advantages of the proposed approaches.

Robust Model Predictive Current Control of Three-Phase Voltage Source PWM Rectifier With Online Disturbance Observation

Abstract: This paper presents a robust model predictive current controller with a disturbance observer (DO-MPC) for three-phase voltage source PWM rectifier. The new algorithm is operated with constant switching frequency (CF-MPC). In order to minimize instantaneous d- and q-axes current errors in every sampling period, CF-MPC is implemented by selecting appropriate voltage vector sequence and calculating duty cycles. The fundamental of this algorithm is discussed and the instantaneous variation rates of d- and q-axes currents are deduced when each converter voltage vector is applied in six different sectors. A Luenberger observer is constructed for parameter mismatch and model uncertainty which affect the performance of the MPC. The gains of the disturbance observer are determined by root-locus analysis. Moreover, the stability of the disturbance observer is analyzed when there are errors in the inductor filter parameter. The proposed method has an inherent rapid dynamic response as a result of the MPC controller, as well as robust control performance with respect to the disturbance due to use of the combined observation algorithm. Simulation and experimental results on a 1.1 kW VSR are conducted to validate the effectiveness of the proposed solution.

Optimal Adaptive Control and Differential Games by Reinforcement Learning Principles

Abstract: This book gives an exposition of recently developed approximate dynamic programming (ADP) techniques for decision and control in human engineered systems ADP is a reinforcement machine learning technique that is motivated by learning mechanisms in biological and animal systems It is connected from a theoretical point of view with both adaptive control and optimal control methods The book shows how ADP can be used to design a family of adaptive optimal control algorithms that converge in real-time to optimal control solutions by measuring data along the system trajectories Generally, in the current literature adaptive controllers and optimal controllers are two distinct methods for the design of automatic control systems Traditional adaptive controllers learn online in real time how to control systems, but do not yield optimal performance On the other hand, traditional optimal controllers must be designed offline using full knowledge of the systems dynamics It is also shown how to use ADP methods to solve multi-player differential games online Differential games have been shown to be important in H-infinity robust control for disturbance rejection, and in coordinating activities among multiple agents in networked teams The focus of this book is on continuous-time systems, whose dynamical models can be derived directly from physical principles based on Hamiltonian or Lagrangian dynamics

Linear Active Stabilization of Converter-Dominated DC Microgrids

Abstract: DC microgrids are gaining high momentum under the smart grid environment. DC microgrid stability can be an issue under high penetration of tightly regulated power converters used to interface distributed resources and loads. This paper addresses dc microgrid stability under high penetration of tightly regulated power electronic converters; and proposes three simple and computationally efficient active damping solutions that can be implemented to stabilize a controlled voltage-source converter (VSC) interfacing a dc- microgrid to an ac system. The proposed active damping methods depend on reshaping the VSC impedance by injecting internal-model-based active damping signal at the outer, intermediate and inner control loops of the voltage-oriented VSC interface. Small signal analysis is conducted to assess the system stability under different compensation schemes. Moreover, the reshaped source impedance of the VSC interface and the modified voltage-tracking dynamics are derived under different compensation schemes. Sensitivity and robustness analyses are provided to assess the dynamic coupling among active damping and voltage tracking controllers. Evaluation results, based on a detailed model of a dc microgrid with multiple tightly regulated converter-interfaced loads, are provided to validate the developed models and demonstrate the effectiveness and robustness of proposed techniques.

Fixed Switching Frequency Sliding Mode Control for Single-Phase Unipolar Inverters

Abstract: Sliding mode control (SMC) is recognized as robust controller with a high stability in a wide range of operating conditions, although it suffers from chattering problem. In addition, it cannot be directly applied to multiswitches power converters. In this paper, a high performance and fixed switching frequency sliding mode controller is proposed for a single-phase unipolar inverter. The chattering problem of SMC is eliminated by smoothing the control law in a narrow boundary layer, and a pulsewidth modulator produces the fixed frequency switching law for the inverter. The smoothing procedure is based on limitation of pulsewidth modulator. Although the smoothed control law limits the performance of SMC, regulation and dynamic response of the inverter output voltage are in an acceptable superior range. The performance of the proposed controller is verified by both simulation and experiments on a prototype 6-kVA inverter. The experimental results show that the total harmonic distortion of the output voltage is less than 1.1% and 1.7% at maximum linear and nonlinear load, respectively. Furthermore, the output dynamic performance of the inverter strictly conforms the standard IEC62040-3. Moreover, the measured efficiency of the inverter in the worst condition is better than 95.5%.

Autonomous Platoon Control Allowing Range-Limited Sensors

Abstract: This paper investigates control design for the platoon of automated vehicles whose sensors have limited sensing capability. A novel hybrid platoon model is established, in which actuator delay (e.g., the fueling and braking delay) and the effect of sensing range limitation are involved. Based on the new model, a framework of guaranteed-cost controller design is presented, which can robustly stabilize the platoon of vehicles with a given level of disturbance attenuation. The obtained controller is complemented by additional conditions that were established to guarantee string stability and zero steady-state spacing error, yielding a useful string-stable platoon control algorithm. The effectiveness and advantage of the presented methodology is demonstrated by both numerical simulations and experiments with laboratory-scale Arduino cars.

Robust Nonfragile $H_\infty$ Filtering of Fuzzy Systems With Linear Fractional Parametric Uncertainties

Abstract: This paper is concerned with the H∞ filtering problem for continuous-time Takagi-Sugeno (T-S) fuzzy systems. Different from existing results for fuzzy H∞ filtering, the proposed ones are toward uncertain fuzzy systems with linear fractional parametric uncertainties. Attention is focused on the design of a fuzzy filter such that the filtering error system preserves a prescribed H∞ performance, where the filter to be designed is assumed to have gain variations. By a descriptor representation approach, two sufficient conditions for the H∞ filter design are proposed in terms of linear matrix inequalities (LMIs). When these LMIs are feasible, an explicit expression of the desired filter is given. A simulation example will be given to show the efficiency of the proposed methods.

Using Full Order and Reduced Order Observers for Robust Sensorless Predictive Torque Control of Induction Motors

Abstract: In this paper, two kinds of observer-based sensorless predictive torque control methods are proposed. The predictive method is based on examining feasible voltage vectors (VVs) in a prescribed cost function. The VV that minimizes the cost function is selected. A novel robust prediction model is presented. The prediction model includes sliding mode feedbacks. The feedback gains are assigned by the H-inf method. Two kinds of observers are applied for flux and speed estimation, i.e., sliding mode full order observer and reduced order observer. In order to verify the proposed method, simulation and experimental results are presented in wide speed range. A comparison of the two methods is performed based on the results.

LMI Solution for Robust Static Output Feedback Control of Discrete Takagi–Sugeno Fuzzy Models

Abstract: This paper deals with the stabilization problem of discrete-time Takagi-Sugeno (T-S) fuzzy systems via static output controller (SOFC). The proposed method uses the descriptor approach to study this problem and leads to strict linear matrix inequality (LMI ) formulation. In contrast with the existing results, the method allows coping with multiple output matrices, as well as uncertainties. Moreover, the new proposed method can lead to less conservative results by introducing slack variables and considering multiple Lyapunov matrices. A robust SOFC for uncertain T-S fuzzy models is also derived in strict LMI terms. Numerical examples are given to illustrate the effectiveness of the proposed design results.

Parameterized Tube Model Predictive Control

Abstract: This paper develops a parameterized tube model predictive control (MPC) synthesis method. The most relevant novel feature of our proposal is the online use of a single tractable linear program that optimizes parameterized, Minkowski decomposable, state and control tubes and an associated, fully separable, nonlinear, control policy. The induced control policy enjoys a higher degree of nonlinearity than existing tube MPC and robust MPC using disturbance affine control policy. Our proposal offers greater generality than the state of the art robust MPC methods. It is conjectured, and also established in three cases, that our proposal is equivalent, feasibility-wise, to dynamic programming (DP). It is also shown that, under natural assumptions, our method is computationally efficient while it possesses rather strong system theoretic properties.

Fuzzy Sliding Mode Speed Controller for PM Synchronous Motors With a Load Torque Observer

Abstract: This paper investigates the robust stabilization problem of a permanent magnet synchronous motor (PMSM). A fuzzy sliding mode speed controller with a load torque observer is designed, which can effectively mitigate chattering and guarantee robust speed control of a PMSM under model parameter and load torque variations. Furthermore, the proposed control method considers the disturbance inputs representing the system nonlinearity or the unmodeled uncertainty. The proposed control algorithm is implemented using a TMS320F28335 floating point DSP. Finally, simulation and experimental results are presented to validate the effectiveness of the proposed scheme.

Robust control of uncertain Markov Decision Processes with temporal logic specifications

Abstract: We present a method for designing a robust control policy for an uncertain system subject to temporal logic specifications. The system is modeled as a finite Markov Decision Process (MDP) whose transition probabilities are not exactly known but are known to belong to a given uncertainty set. A robust control policy is generated for the MDP that maximizes the worst-case probability of satisfying the specification over all transition probabilities in this uncertainty set. To this end, we use a procedure from probabilistic model checking to combine the system model with an automaton representing the specification. This new MDP is then transformed into an equivalent form that satisfies assumptions for stochastic shortest path dynamic programming. A robust version of dynamic programming solves for a e-suboptimal robust control policy with time complexity O(log1/e) times that for the non-robust case.

A Robust Adaptive Control Strategy of Active Power Filters for Power-Factor Correction, Harmonic Compensation, and Balancing of Nonlinear Loads

Abstract: This paper introduces a robust adaptive control strategy of shunt active power filters (SAPF) for power-factor correction, harmonic compensation, and balancing of nonlinear loads. The proposed control scheme is implemented without load harmonic detection. The compensation constraints are obtained by regulating indirectly the currents of the power mains. The reference currents of are generated by the dc-link voltage controller based on the active power balance of system. They are aligned to the phase angle of the power mains voltage vector, by using a phase-locked loop system. The current control strategy is implemented by an adaptive pole-placement control strategy integrated to a variable structure control scheme. This control scheme uses the internal model principle of reference currents for achieving the zero steady-state tracking error. Experimental results are shown for determining the effectiveness of an -proposed control system.

Control-Relevant Models for Glucose Control Using A Priori Patient Characteristics

Abstract: One of the difficulties in the development of a reliable artificial pancreas for people with type 1 diabetes mellitus (T1DM) is the lack of accurate models of an individual's response to insulin. Most control algorithms proposed to control the glucose level in subjects with T1DM are model-based. Avoiding postprandial hypoglycemia ( ;180 mg/dl) has shown to be difficult in a closed-loop setting due to the patient-model mismatch. In this paper, control-relevant models are developed for T1DM, as opposed to models that minimize a prediction error. The parameters of these models are chosen conservatively to minimize the likelihood of hypoglycemia events. To limit the conservatism due to large intersubject variability, the models are personalized using a priori patient characteristics. The models are implemented in a zone model predictive control algorithm. The robustness of these controllers is evaluated in silico, where hypoglycemia is completely avoided even after large meal disturbances. The proposed control approach is simple and the controller can be set up by a physician without the need for control expertise.

A Quasi-Sliding Mode Approach for Robust Control and Speed Estimation of PM Synchronous Motors

Abstract: This paper presents a discrete-time variable-structure-based control and a speed estimator designed for a permanent-magnet synchronous motor (PMSM). A cascade control scheme is proposed which provides accurate speed tracking performance. In this control scheme the speed estimator is a robust digital differentiator that provides the first derivative of the encoder position measurement. The analysis of the control stability is given and the ultimate boundedness of the speed tracking error is proved. The control scheme is experimentally tested on a commercial PMSM drive. Reported experimental evidence shows that the proposed solution produces good speed trajectory tracking performance and it is robust in the presence of disturbances affecting the system.

Robust Nonlinear Predictive Controller for Permanent-Magnet Synchronous Motors With an Optimized Cost Function

Abstract: A robust nonlinear predictive controller for permanent-magnet synchronous motors is proposed. The nonlinear predictive control law is formulated by optimizing a novel cost function. A key feature of the proposed control is that it does not require the knowledge of the external perturbation and parameter uncertainties to enhance the robustness. A zero steady-state error is guaranteed by an integral action of the controller. The stability of the closed-loop system is ensured by convergence of the output-tracking error to the origin. The proposed control strategy is verified via simulation and experiment. High performance with respect to speed tracking and current control of the motor has been demonstrated.

Robust Adaptive Control of MEMS Triaxial Gyroscope Using Fuzzy Compensator

Abstract: In this paper, a robust adaptive control strategy using a fuzzy compensator for MEMS triaxial gyroscope, which has system nonlinearities, including model uncertainties and external disturbances, is proposed. A fuzzy logic controller that could compensate for the model uncertainties and external disturbances is incorporated into the adaptive control scheme in the Lyapunov framework. The proposed adaptive fuzzy controller can guarantee the convergence and asymptotical stability of the closed-loop system. The proposed adaptive fuzzy control strategy does not depend on accurate mathematical models, which simplifies the design procedure. The innovative development of intelligent control methods incorporated with conventional control for the MEMS gyroscope is derived with the strict theoretical proof of the Lyapunov stability. Numerical simulations are investigated to verify the effectiveness of the proposed adaptive fuzzy control scheme and demonstrate the satisfactory tracking performance and robustness against model uncertainties and external disturbances compared with conventional adaptive control method.

Robust Adaptive Boundary Control of a Vibrating String Under Unknown Time-Varying Disturbance

Abstract: In this paper, robust adaptive boundary control is developed for a class of flexible string-type systems under unknown time-varying disturbance. The dynamics of the string system is represented by a nonhomogeneous hyperbolic partial differential equation (PDE) and two ordinary differential equations. Boundary control is proposed at the right boundary of the string based on the original distributed parameter system model (PDE) to suppress the vibration excited by the external unknown disturbance. Adaptive control is designed to compensate the system parametric uncertainty. With the proposed robust adaptive boundary control, all the signals in the closed-loop system are guaranteed to be uniformly ultimately bounded. The state of the string system is proven to converge to a small neighborhood of zero by appropriately choosing design parameters. Simulations are provided to illustrate the effectiveness of the proposed control.

High-Precision Motion Control Techniques: A Promising Approach to Improving Motion Performance

Abstract: In this article, the state of the art on high-precision motion control techniques is surveyed by referring to recent publications, mainly in the transactions and conferences of the IEEEIndustrial Electronics Society (IES), where a 2-degree-of-freedom (DoF) control framework is considered a practical and promising approach to improving motion performance. The actual issues and relevant solutions for each component in the 2-DoF control structure are clarified. Next, one of the examples, a 2-DoF controller design for robust vibration suppression positioning, is presented as an application to industrial high-precision positioning devices. Precise modeling and identification for the target mechatronic systems should be indispensable from the standpoint of more accurate model-based feedforward compensation and/or more progressive design of feedback controllers.

Decentralized Adaptive Robust Control of Robot Manipulators Using Disturbance Observers

Abstract: In this paper, we propose a decentralized adaptive robust controller for trajectory tracking of robot manipulators. In each local controller, a disturbance observer (DOB) is introduced to compensate for the low-passed coupled uncertainties, and an adaptive sliding mode control term is employed to handle the fast-changing components of the uncertainties beyond the pass-band of the DOB. In contrast to most of the local controllers using DOB for robot manipulators that are based on linear control theory, in this study, by some special nonlinear damping terms, the boundedness of the signals of the overall nonlinear system is first ensured. This paves the way to analyze how the DOB and adaptive sliding mode control play in a cooperative way in each local subsystem to achieve an excellent control performance. Simulation results are provided to support the theoretical results.

Wide-Area Robust Coordination Approach of HVDC and FACTS Controllers for Damping Multiple Interarea Oscillations

Abstract: A robust coordination approach for the controller design of multiple high-voltage direct-current (HVDC) and flexible ac transmission systems (FACTS) wide-area controls (WACs) is presented in this paper and has the aim of stabilizing multiple interarea oscillation modes in large-scale power systems. The suitable wide-area control signals, which are given to HVDC and FACTS wide-area controllers, respectively, are chosen from a large number of candidate items. Then, a sequential robust design approach is planned for the wide-area controller coordination of HVDC and FACTS devices. This approach is based on the robust control theory and is formulated as a standard problem of multiobjective mixed H2/H∞ output-feedback control with regional pole placement constraints. The linear matrix inequality (LMI) theory is applied to solve such a robust control problem. A case study on the 16-machine 5-area system, which is modified with one HVDC interconnected transmission, one shunt-FACTS device (SVC), and one series-FACTS device (TCSC), is performed to validate the robust performance in terms of multiple oscillations damping under various operating conditions.