Showing papers on "Robust control published in 2001"

Delay Effects on Stability: A Robust Control Approach

Abstract: Preliminaries.- Examples.- Stability sets and regions.- Reducible discrete delays and LTIs.- Liapunov's second method and LMIs.- Robustness issues in closed-loop.- Applications.

Modern Control Engineering

Abstract: Introduction to automatic control systems mathematical background mathematical models of systems classical time-domain analysis of control systems state-space analysis of control systems stability the root locus method frequency domain analysis classical control design methods state-space design methods optimal control digital control system identification adaptive control robust control fuzzy control. Appendices: Laplace transform tables the Z-transform transform tables.

Robust Control and Model Uncertainty

Abstract: The following sections are included:IntroductionA Benchmark Resource Allocation ProblemModel MisspecificationTwo Robust Control ProblemsRecursivity of the Multiplier FormulationTwo Preference OrderingsRecursivity of the Preference OrderingsConcluding Remarks

Positive 1D and 2D Systems

Abstract: Elements of Probability Theory Uncertain Linear Systems and Robustness Linear Robust Control Design Some Limits of the Robustness Paradigm Probabilistic Methods for Robustness Monte Carlo Methods Randomized Algorithms in Systems and Control Probability Inequalities Statistical Learning Theory and Control Design Sequential Algorithms for Probabilistic Robust Design Sequential Algorithms for LPV Systems Scenario Approach for Probabilistic Robust Design Random Number and Variate Generation Statistical Theory of Radial Random Vectors Vector Randomization Methods Statistical Theory of Radial Random Matrices Matrix Randomization Methods Applications of Randomized Algorithms

Nonlinear and Robust Control of PDE Systems: Methods and Applications to Transport-Reaction Processes

Abstract: Preface List of Figures List of Tables Introduction Feedback Control of Hyperbolic PDE Systems Robust Control of Hyperbolic PDE Systems Feedback Control of Hyperbolic PDE Systems Feedback Control of Parabolic PDE Systems Robust Control of Parabolic PDE Systems Nonlinear and Robust Control of Parabolic PDE Systems with Time-Dependent Spatial Domains Case Studies Proofs of Chapters (1-6) Karhunen-Loeve Expansion References Index

On an output feedback finite-time stabilization problem

Abstract: Studies the problem of finite-time output feedback stabilization for the double integrator system. A class of output feedback controllers that can achieve global finite-time stability for the double integrator system are constructed based on a "finite-time separation principle." Furthermore, it is shown that the closed-loop system resulting from our control law can maintain its local finite-time stability regardless of some nonlinear perturbations. Thus, our control law actually applies to a large class of nonlinear second order systems.

Nonlinear and Robust Control of PDE Systems

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Robust fuzzy control of nonlinear systems with parametric uncertainties

Abstract: Addresses the robust fuzzy control problem for nonlinear systems in the presence of parametric uncertainties. The Takagi-Sugeno (T-S) fuzzy model is adopted for fuzzy modeling of the nonlinear system. Two cases of the T-S fuzzy system with parametric uncertainties, both continuous-time and discrete-time cases are considered. In both continuous-time and discrete-time cases, sufficient conditions are derived for robust stabilization in the sense of Lyapunov asymptotic stability, for the T-S fuzzy system with parametric uncertainties. The sufficient conditions are formulated in the format of linear matrix inequalities. The T-S fuzzy model of the chaotic Lorenz system, which has complex nonlinearity, is developed as a test bed. The effectiveness of the proposed controller design methodology is finally demonstrated through numerical simulations on the chaotic Lorenz system.

Semi-global nonlinear output regulation with adaptive internal model

Abstract: We address the problem of output regulation for nonlinear systems driven by a linear, neutrally stable exosystem whose frequencies are not known a priori. We present a classical solution in terms of the parallel connection of a robust stabilizer and an internal model, where the latter is adaptively tuned to the device that reproduces the steady-state control necessary to maintain the output-zeroing condition. We obtain robust regulation (i.e. in presence of parameter uncertainties) with a semi-global domain of convergence for a significant class of nonlinear minimum-phase system.

Continuous-time analysis, eigenstructure assignment, and H/sub 2/ synthesis with enhanced linear matrix inequalities (LMI) characterizations

Abstract: This note describes a new framework for the analysis and synthesis of control systems, which constitutes a genuine continuous-time extension of results that are only available in discrete time. In contrast to earlier results the proposed methods involve a specific transformation on the Lyapunov variables and a reciprocal variant of the projection lemma, in addition to the classical linearizing transformations on the controller data. For a wide range of problems including robust analysis and synthesis, multichannel H/sub 2/ stateand output-feedback syntheses, the approach leads to potentially less conservative linear matrix inequality (LMI) characterizations. This comes from the fact that the technical restriction of using a single Lyapunov function is to some extent ruled out in this new approach. Moreover, the approach offers new potentials for problems that cannot be handled using earlier techniques. An important instance is the eigenstructure assignment problem blended with Lyapunov-type constraints which is given a simple and tractable formulation.

Control Lyapunov-Razumikhin functions and robust stabilization of time delay systems

Abstract: Motivated by control Lyapunov functions and Razumikhin theorems on stability of time delay systems, we introduce the concept of control Lyapunov-Razumikhin functions (CLRF). The main reason for considering CLRFs is construction of robust stabilizing control laws for time delay systems. Most existing universal formulas that apply to CLFs, are not applicable to CLRFs. It turns out that the domination redesign control law applies, achieving global practical stability and, under an additional assumption, global asymptotic stability. This additional assumption is satisfied in the practically important case when the quadratic part of a CLRF is itself a CLRF for the Jacobian linearization of the system. The CLRF based domination redesign possesses robustness to input unmodeled dynamics including an infinite gain margin. While, in general, construction of CLRFs is an open problem, we show that for several classes of time delay systems a CLRF can be constructed in a systematic way.

Model construction, rule reduction, and robust compensation for generalized form of Takagi-Sugeno fuzzy systems

Abstract: This paper presents a systematic procedure of fuzzy control system design that consists of fuzzy model construction, rule reduction, and robust compensation for nonlinear systems. The model construction part replaces the nonlinear dynamics of a system with a generalized form of Takagi-Sugeno fuzzy systems, which is newly developed by us. The generalized form has a decomposed structure for each element of A/sub i/ and B/sub i/ matrices in consequent parts. The key feature of this structure is that it is suitable for constructing IF-THEN rules and reducing the number of IF-THEN rules. The rule reduction part provides a successive procedure to reduce the number of IF-THEN rules. Furthermore, we convert the reduction error between reduced fuzzy models and a system to model uncertainties of reduced fuzzy models. The robust compensation part achieves the decay rate controller design guaranteeing robust stability for the model uncertainties. Finally, two examples demonstrate the utility of the systematic procedure developed.

A new controller architecture for high performance, robust, and fault-tolerant control

Abstract: We propose a new feedback controller architecture. The distinguished feature of our new controller architecture is that it shows structurally how the controller design for performance and robustness may be done separately which has the potential to overcome the conflict between performance and robustness in the traditional feedback framework. The controller architecture includes two parts: one part for performance and the other part for robustness. The controller architecture works in such a way that the feedback control system can be solely controlled by the performance controller when there is no model uncertainties and external disturbances and the robustification controller can only be active when there are model uncertainties or external disturbances.

Autonomous helicopter control using reinforcement learning policy search methods

Abstract: Many control problems in the robotics field can be cast as partially observed Markovian decision problems (POMDPs), an optimal control formalism. Finding optimal solutions to such problems in general, however is known to be intractable. It has often been observed that in practice, simple structured controllers suffice for good sub-optimal control, and recent research in the artificial intelligence community has focused on policy search methods as techniques for finding sub-optimal controllers when such structured controllers do exist. Traditional model-based reinforcement learning algorithms make a certainty equivalence assumption on their learned models and calculate optimal policies for a maximum-likelihood Markovian model. We consider algorithms that evaluate and synthesize controllers under distributions of Markovian models. Previous work has demonstrated that algorithms that maximize mean reward with respect to model uncertainty leads to safer and more robust controllers. We consider briefly other performance criterion that emphasize robustness and exploration in the search for controllers, and note the relation with experiment design and active learning. To validate the power of the approach on a robotic application we demonstrate the presented learning control algorithm by flying an autonomous helicopter. We show that the controller learned is robust and delivers good performance in this real-world domain.

Adaptive robust precision motion control of linear motors with negligible electrical dynamics: theory and experiments

Abstract: This paper studies the high performance robust motion control of an epoxy core linear motor, which has negligible electrical dynamics due to the fast response of the electrical subsystem. A discontinuous projection based adaptive robust controller (ARC) is first constructed. The controller theoretically guarantees a prescribed transient performance and final tracking accuracy in general, while achieving asymptotic tracking in the presence of parametric uncertainties. A desired compensation ARC scheme is then presented, in which the regressor is calculated using the reference trajectory information only. The resulting controller has several implementation advantages such as less online computation time, reduced effect of measurement noise, a separation of robust control design from parameter adaptation, and a faster adaptation rate. Both schemes are implemented and compared on an epoxy core linear motor. Extensive comparative experimental results are presented to illustrate the effectiveness and the achievable control performance of the two ARC designs.

Integrated active fault-tolerant control using IMM approach

Abstract: An integrated fault detection, diagnosis, and reconfigurable control scheme based on interacting multiple model (IMM) approach is proposed. Fault detection and diagnosis (FDD) is carried out using an IMM estimator. An eigenstructure assignment (EA) technique is used for reconfigurable feedback control law design. To achieve steady-state tracking, reconfigurable feedforward controllers are also synthesized using input weighting approach. The developed scheme can deal with not only actuator and sensor faults, but also failures in, system components. To achieve fast and reliable fault detection, diagnosis, and controller reconfiguration, new fault diagnosis and controller reconfiguration mechanisms have been developed by a suitable combination of the information provided by the mode probabilities from the IMM algorithm and an index related to the closed-loop system performance. The proposed approach is evaluated using an aircraft example, and excellent results have been obtained.

Scalable laws for stable network congestion control

Abstract: Discusses flow control in networks, in which sources control their rates based on feedback signals received from the network links, a feature present in current TCP protocols. We develop a congestion control system which is arbitrarily scalable, in the sense that its stability is maintained for arbitrary network topologies and arbitrary amounts of delay. Such a system can be implemented in a decentralized way with information currently available in networks plus a small amount of additional signaling.

Robust H/sub /spl infin// control of discrete-time Markovian jump linear systems with mode-dependent time-delays

Abstract: Considers the class of discrete-time Markovian jump linear system with norm-bounded uncertainties and time-delay, which is dependent on the system mode. Linear matrix inequality (LMI)-based sufficient conditions for the stability, stabilization and H/sub /spl infin// control are developed. A numerical example is worked out to show the usefulness of the theoretical results.

Perfect tracking control based on multirate feedforward control with generalized sampling periods

Abstract: In this paper, a novel perfect tracking control method based on multirate feedforward control is proposed. The advantages of the proposed method are that: (1) the proposed multirate feedforward controller eliminates the notorious unstable zero problem in designing the discrete-time inverse system; (2) the states of the plant match the desired trajectories at every sampling point of reference input; and (3) the proposed controller is completely independent of the feedback characteristics. Thus, highly robust performance is assured by the robust feedback controller. Moreover, by generalizing the relationship between the sampling period of plant output and the control period of plant input, the proposed method can be applied to various systems with hardware restrictions of these periods, which leads to higher performance. Next, it is shown that the structure of the proposed perfect tracking controller is very simple and clear. Illustrative examples of position control using a DC servomotor are presented, and simulations and experiments demonstrate the advantages of this approach.

Exact linearization and noninteracting control of a 4 rotors helicopter via dynamic feedback

Abstract: Presents a nonlinear dynamic model for a four rotors helicopter in a form suited for control design. We show that the input-output decoupling problem is not solvable for this model by means of a static state feedback control law. Then, a dynamic feedback controller is developed which renders the closed-loop system linear, controllable and noninteractive after a change of coordinates in the state-space. Finally, the stability and the robustness of the proposed control law in the presence of wind, turbulences and parametric uncertainties is analyzed through a simulated case study.

Robust H/spl infin/ filter design for uncertain linear systems with multiple time-varying state delays

Abstract: The problem of robust H/spl infin/ filtering for continuous-time uncertain linear systems with multiple time-varying delays in the state variables is investigated. The uncertain parameters are supposed to belong to a given convex bounded polyhedral domain. The aim is to design a stable linear filter assuring asymptotic stability and a prescribed H/spl infin/ performance level for the filtering error system, irrespective of the uncertainties and the time delays. Sufficient conditions for the existence of such a filter are established in terms of linear matrix inequalities, which can be efficiently solved by means of powerful convex programming tools with global convergence assured. An example illustrates the proposed methodology.

Nonlinear Control of Wheeled Mobile Robots

Abstract: Model development and control objectives.- Robust control.- Adaptive control.- Output feedback control.- Vision based control.- Robustness to kinematic disturbances.- Beyond wheeled mobile robots.

Robust H/sub /spl infin// control of distributed delay systems with application to combustion control

Abstract: The article is concerned with the H/sub /spl infin// analysis and synthesis of linear distributed delay systems An efficient stability and L/sub 2/-gain criterion is established It is based on a recent approach to the analysis and design of linear time delay systems which represents the system in an equivalent descriptor form The obtained criterion is used to derive an efficient state-feedback control design which stabilizes the distributed delay system and achieves a guaranteed disturbance attenuation level in spite of a polytopic uncertainty in the system parameters The new method is applied to the robust stabilization and control of combustion in rocket motor chambers

Stability of time-delay systems: equivalence between Lyapunov and scaled small-gain conditions

Abstract: It is demonstrated that many previously reported Lyapunov-based stability conditions for time-delay systems are equivalent to the robust stability analysis of an uncertain comparison system free of delays via the use of the scaled small-gain lemma with constant scales. The novelty of this note stems from the fact that it unifies several existing stability results under the same framework. In addition, it offers insights on how new, less conservative results can be developed.

Fuzzy sliding-mode controllers with applications

Abstract: This paper concerns the design of robust control systems using sliding-mode control that incorporates a fuzzy tuning technique. The control law superposes equivalent control, switching control, and fuzzy control. An equivalent control law is first designed using pole placement. Switching control is then added to guarantee that the state reaches the sliding mode in the presence of parameter and disturbance uncertainties. Fuzzy tuning schemes are employed to improve control performance and to reduce chattering in the sliding mode. The practical application of fuzzy logic is proposed here as a computational-intelligence approach to engineering problems associated with sliding-mode controllers. The proposed method can have a number of industrial applications including the joint control of a hydraulically actuated mini-excavator as presented in this paper. The control hardware is described together with simulated and experimental results. High performance and attenuated chatter are achieved. The results obtained verify the validity of the proposed control approach to dynamic systems characterized by severe uncertainties.

Digital repetitive learning controller for three-phase CVCF PWM inverter

Abstract: In this paper, a plug-in digital repetitive leaning control scheme is proposed for three-phase constant-voltage constant-frequency (CVCF) pulsewidth modulation inverters to achieve high-quality sinusoidal output voltages. In the proposed control scheme, the repetitive controller (RC) is plugged into the stable one-sampling-ahead-preview-controlled three-phase CVCF inverter system using only two voltage sensors. The RC is designed to eliminate periodic disturbance and/or track periodic reference signal with zero tracking error, The design theory of plug-in repetitive learning controller is described systematically and the stability analysis or overall system is discussed. The merits of the controlled systems include features of minimized total harmonic distortion, robustness to parameter uncertainties, fast response, and fewer sensors. Simulation and experimental results are provided to illustrate the effectiveness of the proposed scheme.

Neural-network control of mobile manipulators

Abstract: In this paper, a neural network (NN)-based methodology is developed for the motion control of mobile manipulators subject to kinematic constraints. The dynamics of the mobile manipulator is assumed to be completely unknown, and is identified online by the NN estimators. No preliminary learning stage of NN weights is required. The controller is capable of disturbance-rejection in the presence of unmodeled bounded disturbances. The tracking stability of the closed-loop system, the convergence of the NN weight-updating process and boundedness of NN weight estimation errors are all guaranteed. Experimental tests on a 4-DOF manipulator arm illustrate that the proposed controller significantly improves the performance in comparison with conventional robust control.

Modeling, control, and design of input-series-output-parallel-connected converter for high-speed-train power system

Abstract: In this paper, a charge control with an input voltage feedforward is proposed for an input-series-output-parallel-connected converter configuration for the high-speed-train power system application. This control scheme accomplishes the output current sharing. For the output-parallel-connected modules as well as the input voltage sharing for the input-series-connected modules for all operating conditions including the transients. It also offers the robustness for the input voltage sharing control according to the component value mismatches among the modules. This configuration enables the usage of a MOSFET for a high-voltage system allowing a higher switching frequency for a lighter system weight and smaller size. The performance of the proposed scheme is verified through the experimental results.