Showing papers on "Robust control published in 2005"

The Control Handbook

Abstract: FUNDAMENTALS OF CONTROL Mathematical Foundations Ordinary Linear Differential and Difference Equations, B.P. Lathi The Fourier, Laplace, and Z-Transforms, E.W. Kamen Matrices and Linear Algebra, B.W. Dickinson Complex Variables, C.W. Gray Models for Dynamical Systems Standard Mathematical Models Input-Output Models, W.S. Levine State Space, J. Gillis Graphical Models Block Diagrams, D.K. Frederick and C.M. Close Signal Flow Graphs, N.S. Nise Determining Models Modeling from Physical Principles, F.E. Cellier, H. Elmqvist, and M. Otter System Identification When Noise is Negligible, W.S. Levine Analysis and Design Methods for Continuous-Time Systems Analysis Methods Time Response of Linear Time-Invariant Systems, R.T. Stefani Controllability and Observability, W.A. Wolovich Stability Tests The Routh-Hurwitz Stability Criterion, R.H. Bishop and R.C. Dorf The Nyquist Stability Test, C.E. Rohrs Discrete-Time and Sampled-Data Stability Tests, M. Mansour Gain Margin and Phase Margin, R.T. Stefani Design Methods Specification of Control Systems, J.-S. Yang and W.S. Levine Design Using Performance Indices, R.C. Dorf and R.H. Bishop Nyquist, Bode, and Nichols Plots, J.J. D'Azzo and C.H. Houpis The Root Locus Plot, W.S. Levine PID Control, K.J. Astrom and T. Hagglund State Space - Pole Placement, K. Ogata Internal Model Control, R.D. Braatz Time-Delay Compensation - Smith Predictor and Its Modifications, Z.J. Palmor Digital Control Discrete-Time Systems, M.S. Santina and A.R. Stubberud Sampled-Data Systems, A. Feuer and G.C. Goodwin Discrete-Time Equivalents to Continuous-Time Systems, M.S. Santina and A.R. Stubberud Design Methods for Discrete-Time Linear Time-Invariant Systems, M.S. Santina and A.R. Stubberud Quantization Effects, M.S. Santina and A.R. Stubberud Sample-Rate Selection, M.S. Santina and A.R. Stubberud Real Time Software for Implementation of Digital Control, D.M. Auslander, J.R. Ridgely, and J. Jones Programmable Controllers, G. Olsson Analysis and Design Methods for Nonlinear Systems Analysis Methods The Describing Function Method, D.P. Atherton The Phase Plane Method, D.P. Atherton Design Methods Dealing with Actuator Saturation, R.H. Middleton Bumpless Transfer, A. Ahlen and S.F. Graebe Linearization and Gain-Scheduling, J.S. Shamma Software for Control System Analysis and Design Numerical and Computational Issues in Linear Control and System Theory, R.V. Patel, A.J. Laub, and P.M. Van Dooren Software for Modeling and Simulating Control Systems, M. Otter and F.E. Cellier Computer-Aided Control Systems Design, C.M. Rimvall and C.P Jobling ADVANCED METHODS OF CONTROL Analysis Methods for MIMO Linear Systems Multivariable Poles, Zeros, and Pole/Zero Cancellations, J. Douglas and M. Athans Fundamentals of Linear Time-Varying Systems, E.W. Kamen Geometric Theory of Linear Systems, F. Hamano Polynomial and Matrix Fraction Descriptions, D.F. Delchamps Robustness Analysis with Real Parametric Uncertainty, R. Tempo and F. Blanchini MIMO Frequency Response Analysis and the Singular Value Decomposition, S.D. Patek and M. Athans Stability Robustness to Unstructured Uncertainty for Linear Time-Invariant Systems, A. Chao and M. Athans Tradeoffs and Limitations in Feedback Systems, D.P. Looze and J.S. Freudenberg Modeling Deterministic Uncertainty, J. Raisch and B.A. Francis The Use of Multivariate Statistics in Process Control, M.J. Piovoso and K.A. Kosanovich Kalman Filter and Observers Linear Systems and White Noise, W.S. Levine Kalman Filter, M. Athans Riccati Equations and Their Solution, V. Kucera Observers, B. Friedland Design Methods for MIMO LTI Systems Eigenstructure Assignment, K.M. Sobel, E.Y. Shapiro, and A.N. Andry, Jr. Linear Quadratic Regulator Control, L. Lublin and M. Athans H2 (LQG) and H8 Control, L. Lublin, S. Grocott, and M. Athens Robust Control: Theory, Computation, and Design, M. Dahleh The Structured Singular Value (m) Framework, G.J. Balas and A. Packard Algebraic Design Methods, V. Kucera Quantitative Feedback Theory (QFT) Technique, C.H. Houpis The Inverse Nyquist Array and Characteristic Locus Design Methods, N. Munro and J.M. Edmunds Robust Servomechanism Problem, E.J. Davidson Numerical Optimization-Based Design, V. Balakrishnan and A.L. Tits Optimal Control, F.L. Lewis Decentralized Control, M.E. Sezer and D.D. Siljak Decoupling, T. Williams and P.J. Antsaklis Predictive Control, A.W. Pike, M.J. Grimble, M.A. Johnson, A.W. Ordys, and S. Shakoor Adaptive Control Automatic Tuning of PID Controllers, T. Hagglund and K.J. Astrom Self-Tuning Control, D.W. Clarke Model Reference Adaptive Control, P.A. Ioannou Analysis and Design of Nonlinear Systems Analysis Methods The Lie Bracket and Control, V. Jurdjevic Two Time Scale and Averaging Methods, H.K. Khalil Volterra and Fliess Series Expansion for Nonlinear Systems, F. Lamnabi-Lagarrique Stability Lyapunov Stability, H.K. Khalil Input-Output Stability, A.R. Teel, T.T. Georgiou, L. Praly, and E. Sontag Design Methods Feedback Linearization of Nonlinear Systems, A. Isidori and M.D. Di Benedetto Nonlinear Zero Dynamics, A. Isidori and C.I. Byrnes Nonlinear Output Regulation and Tracking, A. Isidori Lyapunov Design, R.A. Freeman and P.V. Kokotovic Variable Structure and Sliding Mode Controller Design, R.A. De Carlo, S.H. Zak, and S.V. Drakunov Control of Bifurcation and Chaos, E.H. Abed, H.O. Wang, and A. Tesi Open-Loop Control Using Oscillatory Inputs, J. Baillieul and B. Lehman Adaptive Nonlinear Control, M. Krstic and P.V. Kokotovic Intelligent Control, K.M. Passino Fuzzy Control, K.M. Passino and S. Yurkovich Neural Control, J.A. Farrell System Identification System Identification, L. Ljung Stochastic Control Discrete Time Markov Processes, A. Schwartz Stochastic Differential Equations, J.A. Gubner Linear Stochastic Input-Output Models, T. Soderstrom Minimum Variance Control, M.R. Katebi and A.W. Ordys Dynamic Programming, P.R. Kumar Stability of Stochastic Systems, K.O. Loparo and X. Feng Stochastic Adaptive Control, T.E. Duncan and B. Pasik-Duncan Control of Distributed Parameter Systems Controllability of Thin Elastic Beams and Plates, J.E. Lagnese and G. Leugering Control of the Heat Equation, T.I. Seidman Observability of Linear Distributed Parameter Systems, D.L. Russell APPLICATIONS OF CONTROL Process Control Water Level Control for the Toilet Tank: A Historical Perspective, B.G. Coury Temperature Control in Large Buildings, C.C. Federspiel and J.E. Seem Control of pH, F.G. Shinskey Control of the Pulp and Paper-Making Process, W.L. Bialkowski Control for Advanced Semiconductor Device Manufacturing: A Case History, T. Kailath, C. Schaper, Y. Cho, P. Gyugyi, S. Norman, P. Park, S. Boyd, G. Franklin, K. Saraswat, M. Modehi, and C. Davis Mechanical Control Systems Automotive Control Systems Engine Control, J.A. Cook, J.W. Grizzle, and J. Sun Adaptive Automotive Speed Control, M.K. Liubakka, D.S. Rhode, J.R. Winkelman, and P.V. Kokotovic Aerospace Controls Flight Control of Piloted Aircraft, M. Pachter and C.H. Houpis Spacecraft Attitude Control, V.T. Coppola and N.H. McClamroch Control of Flexible Space Structures, S.M. Joshi and A.G. Kelkar Line-of-Sight Pointing and Stabilization Control Systems, D.A. Haessig Control of Robots and Manipulators Motion Control of Robotic Manipulators, M.W. Spong Force Control of Robotic Manipulators, J. De Schutter and H. Bruyninckx Control of Nonholonomic Systems, J.T.-Y. Wen Miscellaneous Mechanical Control Systems Friction Compensation, B. Armstrong-Helouvry and C. Canudas de Wit Motion Control Systems, J. Tal Ultra-High Precision Control, T.R. Kurfess and H. Jenkins Robust Control of a Compact Disc Mechanism, M. Steinbuch, G. Schootstra, and O.H. Bosgra Electrical and Electronic Control Systems Power Electronic Controls Dynamic Modeling and Control in Power Electronics, G.C. Verghese Motion Control with Electric Motors by Input-Output Linearization, D.G. Taylor Control of Electric Generators, T. Jahns and R.W. De Doncker Control of Electrical Power Control of Electrical Power Generating Plants, H.G. Kwatny and C. Maffezzoni Control of Power Transmission, J.J. Paserba, J.J. Sanchez-Gasca, and E.V. Larsen Control Systems Including Humans Human-in-the-Loop Control, R.A. Hess Index

The sector bound approach to quantized feedback control

Abstract: This paper studies a number of quantized feedback design problems for linear systems. We consider the case where quantizers are static (memoryless). The common aim of these design problems is to stabilize the given system or to achieve certain performance with the coarsest quantization density. Our main discovery is that the classical sector bound approach is nonconservative for studying these design problems. Consequently, we are able to convert many quantized feedback design problems to well-known robust control problems with sector bound uncertainties. In particular, we derive the coarsest quantization densities for stabilization for multiple-input-multiple-output systems in both state feedback and output feedback cases; and we also derive conditions for quantized feedback control for quadratic cost and H/sub /spl infin// performances.

Robust Control of Markov Decision Processes with Uncertain Transition Matrices

Abstract: Optimal solutions to Markov decision problems may be very sensitive with respect to the state transition probabilities In many practical problems, the estimation of these probabilities is far from accurate Hence, estimation errors are limiting factors in applying Markov decision processes to real-world problems We consider a robust control problem for a finite-state, finite-action Markov decision process, where uncertainty on the transition matrices is described in terms of possibly nonconvex sets We show that perfect duality holds for this problem, and that as a consequence, it can be solved with a variant of the classical dynamic programming algorithm, the "robust dynamic programming" algorithm We show that a particular choice of the uncertainty sets, involving likelihood regions or entropy bounds, leads to both a statistically accurate representation of uncertainty, and a complexity of the robust recursion that is almost the same as that of the classical recursion Hence, robustness can be added at practically no extra computing cost We derive similar results for other uncertainty sets, including one with a finite number of possible values for the transition matrices We describe in a practical path planning example the benefits of using a robust strategy instead of the classical optimal strategy; even if the uncertainty level is only crudely guessed, the robust strategy yields a much better worst-case expected travel time

Robust Control in Power Systems

Abstract: Power System Oscillations.- Linear Control in Power Systems.- Test System Model.- Power System Stabilizers.- Multiple-Model Adaptive Control Approach.- Simultaneous Stabilization.- Mixed-Sensitivity Approach Using Linear Matrix Inequalities.- Normalized ?? Loop-Shaping Using Linear Matrix Inequalities.- ?? Control For Time-Delayed Systems.

Robust control design with MATLAB

Abstract: Robust Control Design with MATLAB (second edition) helps the student to learn how to use well-developed advanced robust control design methods in practical cases. To this end, several realistic control design examples from teaching-laboratory experiments, such as a two-wheeled, self-balancing robot, to complex systems like a flexible-link manipulator are given detailed presentation. All of these exercises are conducted using MATLAB Robust Control Toolbox 3, Control System Toolbox and Simulink. By sharing their experiences in industrial cases with minimum recourse to complicated theories and formulae, the authors convey essential ideas and useful insights into robust industrial control systems design using major H-infinity optimization and related methods allowing readers quickly to move on with their own challenges. The hands-on tutorial style of this text rests on an abundance of examples and features for the second edition: rewritten and simplified presentation of theoretical and methodological material including original coverage of linear matrix inequalities; new Part II forming a tutorial on Robust Control Toolbox 3; fresh design problems including the control of a two-rotor dynamic system; and end-of-chapter exercises. Electronic supplements to the written text that can be downloaded from extras.springer.com/isbn include: M-files developed with MATLAB help in understanding the essence of robust control system design portrayed in text-based examples; MDL-files for simulation of open- and closed-loop systems in Simulink; and a solutions manual available free of charge to those adopting Robust Control Design with MATLAB as a textbook for courses. Robust Control Design with MATLAB is for graduate students and practising engineers who want to learn how to deal with robust control design problems without spending a lot of time in researching complex theoretical developments.

Digital Control Systems: Design, Identification and Implementation

Abstract: Continuous Control Systems: A Review -- Computer Control Systems -- Robust Digital Controller Design Methods -- Design of Digital Controllers in the Presence of Random Disturbances -- System Identification: The Bases -- System Identification Methods -- Practical Aspects of System Identification -- Practical Aspects of Digital Control -- Identification in Closed Loop -- Reduction of Controller Complexity.

Adaptive variable structure control of a class of nonlinear systems with unknown Prandtl-Ishlinskii hysteresis

Abstract: Control of nonlinear systems preceded by unknown hysteresis nonlinearities is a challenging task and has received increasing attention in recent years due to growing industrial demands involving varied applications. In the literature, many mathematical models have been proposed to describe the hysteresis nonlinearities. The challenge addressed here is how to fuse those hysteresis models with available robust control techniques to have the basic requirement of stability of the system. The purpose of the note is to show such a possibility by using the Prandtl-Ishlinskii (PI) hysteresis model. An adaptive variable structure control approach, serving as an illustration, is fused with the PI model without necessarily constructing a hysteresis inverse. The global stability of the system and tracking a desired trajectory to a certain precision are achieved. Simulation results attained for a nonlinear system are presented to illustrate and further validate the effectiveness of the proposed approach.

Swarm aggregations using artificial potentials and sliding-mode control

Abstract: In this paper, we consider a control strategy of multiagent systems, or simply, swarms, based on artificial potential functions and the sliding-mode control technique. First, we briefly discuss a "kinematic" swarm model in n-dimensional space introduced in an earlier paper. In that model, the interindividual interactions are based on artificial potential functions, and the motion of the individuals is along the negative gradient of the combined potential. After that, we consider a general model for vehicle dynamics of each agent (swarm member), and use sliding-mode control theory to force their motion to obey the dynamics of the kinematic model. In this context, the results for the initial model serve as a "proof of concept" for multiagent coordination and control (swarm aggregation), whereas the present results serve as a possible implementation method for engineering swarms with given vehicle dynamics. The presented control scheme is robust with respect to disturbances and system uncertainties.

Design methodologies for robust nano-positioning

Abstract: In this paper, we present a systematic control design and analysis for a two-dimensional nano-positioner. The primary emphasis of the paper is on the robustness of the closed-loop device as these flexure-stage-based, piezoactuated nano-positioners are nonlinear and operate in diverse conditions. To this end, we have used many tools from modern control theory to model devices and to quantify device resolution, bandwidth, and robustness. The implementation of this procedure for the simultaneous achievement of the objectives of robustness, high precision and high bandwidth is presented. The merits of the paradigm are demonstrated through experimental results.

Robust impulsive synchronization of uncertain dynamical networks

Abstract: This paper studies robust impulsive synchronization of uncertain dynamical networks. By utilizing the concept of impulsive control and the stability results for impulsive systems, several criteria for robust local and robust global impulsive synchronization are established for complex dynamical networks, in which the network coupling functions are unknown but bounded. Three examples are also worked through for illustrating the main results.

Automatic disturbances rejection controller for precise motion control of permanent-magnet synchronous motors

Abstract: A highly robust automatic disturbances rejection controller (ADRC) is developed to implement high-precision motion control of permanent-magnet synchronous motors. The proposed ADRC consists of a tracking differentiator (TD) in the feedforward path, an extended state observer (ESO), and a nonlinear proportional derivative control in the feedback path. The TD solves the difficulties posed by low-order reference trajectories which are quantized at the sensor resolution, and the ESO provides the estimate of the unmeasured system's state and the real action of the unknown disturbances only based on a measurement output of the system. Simulations and experimental results show that the proposed ADRC achieves a better position response and is robust to parameter variation and load disturbance. Furthermore, the ADRC is designed directly in discrete time with a simple structure and fast computation, which make it widely applicable to all other types of derives.

Robust H/sub /spl infin// control for uncertain discrete-time-delay fuzzy systems via output feedback controllers

Abstract: This work investigates the problem of robust output feedback H/sub /spl infin// control for a class of uncertain discrete-time fuzzy systems with time delays. The state-space Takagi-Sugeno fuzzy model with time delays and norm-bounded parameter uncertainties is adopted. The purpose is the design of a full-order fuzzy dynamic output feedback controller which ensures the robust asymptotic stability of the closed-loop system and guarantees an H/sub /spl infin// norm bound constraint on disturbance attenuation for all admissible uncertainties. In terms of linear matrix inequalities (LMIs), a sufficient condition for the solvability of this problem is presented. Explicit expressions of a desired output feedback controller are proposed when the given LMIs are feasible. The effectiveness and the applicability of the proposed design approach are demonstrated by applying this to the problem of robust H/sub /spl infin// control for a class of uncertain nonlinear discrete delay systems.

Direct adaptive controller for nonaffine nonlinear systems using self-structuring neural networks

Abstract: A direct adaptive state-feedback controller is proposed for highly nonlinear systems. We consider uncertain or ill-defined nonaffine nonlinear systems and employ a neural network (NN) with flexible structure, i.e., an online variation of the number of neurons. The NN approximates and adaptively cancels an unknown plant nonlinearity. A control law and adaptive laws for the weights in the hidden layer and output layer of the NN are established so that the whole closed-loop system is stable in the sense of Lyapunov. Moreover, the tracking error is guaranteed to be uniformly asymptotically stable (UAS) rather than uniformly ultimately bounded (UUB) with the aid of an additional robustifying control term. The proposed control algorithm is relatively simple and requires no restrictive conditions on the design constants for the stability. The efficiency of the proposed scheme is shown through the simulation of a simple nonaffine nonlinear system.

Mode-independent robust stabilization for uncertain Markovian jump nonlinear systems via fuzzy control

Abstract: This paper is concerned with the robust-stabilization problem of uncertain Markovian jump nonlinear systems (MJNSs) without mode observations via a fuzzy-control approach. The Takagi and Sugeno (T-S) fuzzy model is employed to represent a nonlinear system with norm-bounded parameter uncertainties and Markovian jump parameters. The aim is to design a mode-independent fuzzy controller such that the closed-loop Markovian jump fuzzy system (MJFS) is robustly stochastically stable. Based on a stochastic Lyapunov function, a robust-stabilization condition using a mode-independent fuzzy controller is derived for the uncertain MJFS in terms of linear matrix inequalities (LMIs). A new improved LMI formulation is used to alleviate the interrelation between the stochastic Lyapunov matrix and the system matrices containing controller variables in the derivation process. Finally, a simulation example is presented to illustrate the effectiveness of the proposed design method.

Delay-dependent robust H/sub /spl infin// control for T-S fuzzy systems with time delay

Abstract: This paper focuses on the problem of delay-dependent robust fuzzy control for a class of nonlinear delay systems via state feedback. The Takagi-Sugeno (T-S) fuzzy model is adopted for representing a nonlinear system with time delayed state. A delay-dependent stabilization criterion is first presented. Then, the methods of robust stabilization and robust H/sub /spl infin// control are developed, which are dependent on the size of the delay and are based on the solutions of linear matrix inequalities (LMIs). Finally, a design example of robust H/sub /spl infin// controller for uncertain nonlinear systems is given to illustrate the effectiveness of the approaches proposed in this paper.

Robust backstepping control for a class of time delayed systems

Abstract: In this note, the problem of robust output feedback control for a class of nonlinear time delayed systems is considered. The systems considered are in strict-feedback form. State observer is first designed, then based on the observed states the controller is designed via backstepping method. Both the designed observer and controller are independent of the time delays. Based on Lyapunov stability theory, we prove that the constructed controller can render the closed-loop system asymptotically stable. Simulation results further verify the effectiveness of the proposed approach.

Relaxations for Robust Linear Matrix Inequality Problems with Verifications for Exactness

Abstract: Robust semidefinite programming problems with rational dependence on uncertainties are known to have a wide range of applications, in particular in robust control. It is well established how to systematically construct relaxations on the basis of the full block S-procedure. In general, such relaxations are expected to be conservative, but for concrete problem instances they are often observed to be tight. The main purpose of this paper is to suggest novel computationally verifiable conditions for when general classes of linear matrix inequality relaxations do not involve any conservatism. If the convex set of uncertainties is finitely generated, we suggest a novel sequence of relaxations which can be proved to be asymptotically exact. Finally, our results are applied to the particularly relevant robustness analysis problem for linear time-invariant dynamical systems affected by uncertainties that are full ellipsoidal or repeated and contained in intersections of disks or circles. This leads to extensions of known results on relaxation exactness for small block structures, including an elementary proof for tightness of standard structured singular value computations for three full complex uncertainty blocks.

An improved robust predictive current regulation algorithm

Abstract: Current regulation techniques for pulsewidth-modulated (PWM) voltage source inverters (VSIs) can be classified as either linear or nonlinear. Linear techniques consist principally of either a proportional-integral (PI) or a predictive current control strategy, while nonlinear schemes are usually based on a hysteresis strategy. Of the two linear strategies, predictive current control offers the advantages of precise current tracking with minimal distortion and can also be fully implemented on a digital platform. However, the conventional implementation of the predictive current regulation (PCR) algorithm is sensitive to noise and errors in the load inductance estimate, particularly when the back EMF is also estimated. This paper presents an improved PCR algorithm that retains all the benefits associated with PCR while achieving significantly increased robustness to load parameter mismatch and reduced zero current clamped oscillation effects. It is also relatively insensitive to noise in the sampled current measurements. The algorithm is equally applicable to variable fundamental frequency applications such as variable speed drives and to fixed fundamental frequency applications such as PWM rectifier systems or active filters. Simulation and experimental results are presented to confirm the improved robustness of the new algorithm.

Realization of "Law of action and reaction" by multilateral control

Abstract: In recent years, the realization of a haptic system has been strongly desired in the fields of medical treatment and expert's skill acquisition. The key point of haptics is to realize a vivid presentation of reactive force, particularly in applications that involve touching action. In this paper, a realization of the "law of action and reaction" by multilateral control is introduced. First, an analysis and a design of bilateral control based on the disturbance observer are discussed. A disturbance observer is a basic technology for quarrying of disturbance torque and attainment of robust acceleration control. This paper shows that a four-channel controller which is composed of position control and force control in the acceleration dimension is decomposed into two modes: common and differential modes. A design of bilateral control is treated as position and force control in a single joint. The proposed method generates a good realization of reactive force for the slave side at the master side in bilateral force control. Second, bilateral control is extended and multilateral control is generalized. Multilateral control is designed similarly as bilateral control based on the modal decomposition. Robots with a haptic ability will have an important role in human adaptive mechatronics.

Modeling and control of cooperative teleoperation systems

Abstract: This paper presents a multilateral control architecture for teleoperation in multimaster/multislave environments. The proposed framework incorporates flow of position and force information between all master and slave robots, rather than merely between corresponding units. Within this architecture, cooperative performance measures are defined to enhance coordination among the operators and the robots for achieving the task objectives. A /spl mu/-synthesis-based methodology for cooperative teleoperation control is also introduced. This approach guarantees robust stability of cooperative teleoperation in the presence of dynamic interaction between slave robots, as well as unknown passive operators and environment dynamics. It also improves task coordination by optimizing relevant performance objectives. Experiments carried out with a two-master/two-slave single-axis system demonstrate the effectiveness of the proposed approach.

An improved robust fuzzy-PID controller with optimal fuzzy reasoning

Abstract: Many fuzzy control schemes used in industrial practice today are based on some simplified fuzzy reasoning methods, which are simple but at the expense of losing robustness, missing fuzzy characteristics, and having inconsistent inference. The concept of optimal fuzzy reasoning is introduced in this paper to overcome these shortcomings. The main advantage is that an integration of the optimal fuzzy reasoning with a PID control structure will generate a new type of fuzzy-PID control schemes with inherent optimal-tuning features for both local optimal performance and global tracking robustness. This new fuzzy-PID controller is then analyzed quantitatively and compared with other existing fuzzy-PID control methods. Both analytical and numerical studies clearly show the improved robustness of the new fuzzy-PID controller.

Robust nonlinear flight control of a high-performance aircraft

Abstract: This paper considers probabilistic robust control of nonlinear uncertain systems. A combination of stochastic robustness and dynamic inversion is proposed for general systems that have a feedback-linearizable nominal system. In this paper, the stochastic robust nonlinear control approach is applied to a highly nonlinear complex aircraft model, the high-incidence research model (HIRM). The model addresses a high-angle-of-attack enhanced manual control problem. The aim of the flight control system is to give good handling qualities across the specified flight envelope without the use of gain scheduling and also to provide robustness to modeling uncertainties. The proposed stochastic robust nonlinear control explores the direct design of nonlinear flight control logic. Therefore, the final design accounts for all significant nonlinearities in the aircraft's high-fidelity simulation model. The controller parameters are designed to minimize the probability of violating design specifications, which provides the design with good robustness in stability and performance subject to modeling uncertainties. The present design compares favorably with earlier controllers that were generated for a benchmark design competition.