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In this paper, an adaptive fuzzy moving sliding mode controller for unknown multivariable nonlinear dynamical system involving plant uncertainties and external disturbances is proposed. Two control techniques, i.e., adaptive fuzzy control scheme, and moving sliding mode control design, are incorporated to solve the robust nonlinear tracking problem. Due to universal approximation theorem, time delay...
In this study, a novel multiple model adaptive control scheme is designed and implemented for quadrotor unmanned aerial vehicles (UAVs). The proposed scheme involves a mixing adaptive controller that blends a set of pre-designed linear quadratic controllers. A particular goal of the design is guaranteeing robustness in lateral motion against modeling uncertainties. The designed controller scheme is...
Second level adaptation using multiple models for the adaptive control of linear systems with unknown parameters was introduced in [1], and its robustness properties were discussed in [2]. In both cases, the plant, the identification models, and the reference model were assumed to be described by state equations in companion form, with all state variables accessible.
To meet the high-performance motion accuracy requirement in current precision industry, an investigation on the combination of adaptive robust control (ARC) and iterative learning control (ILC) is conducted, which is inspired by our previous research on these two methods. It was theoretically and experimentally illustrated that ARC achieved good tracking performance and guaranteed transient performance...
Control of complex Vertical Take-Off and Landing (VTOL) aircraft traversing from hovering to wing born flight mode and back poses notoriously difficult modeling, simulation, control, and flight-testing challenges. This paper provides an overview of a robust adaptive control for autonomous flight of the GL- 10 tilt-wing, tilt-tail, long endurance, VTOL aircraft control system. The GL-10 prototype aircraft...
A challenging problem for adaptive control systems is the accurate characterization of the transient response in the presence of dynamic uncertainties such as a partially known actuator. Considering an actuator modelled as a first order filter with an uncertain control effectiveness and using a projection mechanism for parameters adaptation, we show that the tracking error dynamics behaves as a linear...
A design method of decentralized local robust state feedback controllers is presented for a class of uncertain large scale interconnected time-delay dynamical systems. In this paper, the upper bounds of delayed state perturbations, uncertainties, interconnection terms, and external disturbances are assumed to be completely unknown, and the delays are assumed to be any nonnegative constants. A class...
The adaptive-robust control strategy, proposed in this paper, combines the advantages of robust and adaptive control, while minimizing the computational load. Usually, a lot of mathematical operations are necessary, which limit the real time applicability of such strategies. By developing a simple, yet useful rule, the number of operations needed to determine if a new controller is needed has been...
The design of some adaptive and robust-adaptive control strategies for a microalgae fermentation process that is carried out inside a Continuous Stirred Tank Reactor (CSTR) is presented. Initially, an indirect adaptive controller is designed by coupling a linearizing controller with a new parameter estimator used for estimation of unknown kinetics. Afterwards, under the realistic assumption that the...
This paper is focused on the posture control of a 3 degree of freedom (3DOF) parallel manipulator driven by pneumatic muscles (PMDPM). The feedback linearization control and model reference adaptive control are developed to control the posture of the moving platform by changing the pressure inside the pneumatic muscles. The performances of the controllers to track step and sinusoidal reference inputs...
This paper presents a robust scheme for the indirect type of model reference adaptive control (MRAC) system, in the presence of unmodelled dynamics and measurement noise. This scheme is characterized by the use of adaptive law with dead zone and integral type of fixed compensator. Stability of the MRAC system is analyzed by employing the concept of L2δ norm and the Bellman-Gronwall lemma, based on...
This paper proposes a novel design method for the adaptive robust Ho, control problem of a class of nonlinear systems with parametric uncertainties and external disturbances, which combines adaptive control and robust H∞, control techniques. By the use of the parameter projection method in adaptive control, the adaptive control laws are derived. Based on Hamilton-Jacobi inequalities, the adaptive...
We consider robust adaptive control designs for relative degree one, minimum phase linear systems of known high frequency gain. The designs are based on the dead-zone and projection modifications, and we compare their performance w.r.t. a worst case transient cost functional penalising the L∞ norm of the output, control and control derivative. If a bound on the L∞ norm of the disturbance is known,...
This paper is concerned with the mixed H2/H∞ control problem. The purpose of this paper is to give an iterative algorithm for finding a sub-optimal static state feedback controller for the mixed H2/H∞ control problem. The key idea of our algorithm is to construct two “controller sets”: one is a set of controllers that improve the H2 norm of the closed loop map for a given controller and the other...
Adaptive control schemes are developed, which provide global asymptotic stability property with respect to state space vector of the plant with functional uncertainty. In the presence of disturbance these schemes ensure boundedness of all trajectories of the system. A switching modification of proposed schemes is considered.
This paper deals with the combination of sliding mode control (SMC) and fuzzy logic system (FLS) for a class of non-linear multi-input multi-output (MIMO) uncertain systems. An adaptive scheme for the fuzzy control is developed to approximate the unknown system functions. A SMC is then applied to reduce the effects of both approximation errors and external disturbances. Thanks to Lyapunov's theory,...
This paper addresses the stabilization problem of an uncertain intrinsically nonlinear SISO plant containing non-smooth nonlinearities (dead-zone, backlash, hysteresis) in the actuator device. A unified framework for its solution is here proposed, assuming that the parameters of the nonlinearities are uncertain as well. To this purpose, the hysteresis model used in [8] has been modified into an “extended”...
In this paper, the robustness limitations of current recursive identification algorithms are highlighted. Then, it is shown how a particular nonrecursive identification algorithm dramatically improves the robustness to bounded disturbances, noise and slowly time-varying parameters. only at the expense of performing an on-line eigenvalue decomposition on a symmetric semidefinite positive matrix. Furthermore,...
An output feedback robust controller based on sliding modes and indirect adaptive control called Indirect Variable Structure Model Reference Adaptive Control (IVS-MRAC) was recently proposed for relative degree one LTI plants, suggesting to be globally asymptotically stable with superior transient behavior and disturbance rejection properties. In this paper, some remarkable simplifications are carried...
Iterative Feedback Tuning (IFT) is a direct tuning method using closed loop experimental data. The method is based on numerical optimization and in each iteration an unbiased gradient estimate is used. In this contribution we show how to use IFT to do robust loopshaping. One method, based on the approach suggested by Glover and McFarlane [1], uses an approximate H∞ cost function and alternates between...
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