Robust adaptive model tracking for distributed parameter control of linear infinite-dimensional systems in Hilbert space

This paper proposes a nonlinear fighter aircraft pitch rate tracking control scheme based on a Multiple Fuzzy Reference Model Adaptive Controller. The scheme consists of a direct Model Reference Adaptive Control (MRAC) with the reference model generated online using a fuzzy logic algorithm. The proposed control provides a soft multiple reference model switching for the aircraft multiple modes of operation, without prohibitive computational complexities or explicit system identification. In case of aircraft mode swings or sudden jumps, the reference model will be changed or generated based on the fuzzy logic scheme looking at the plant output and auxiliary parameters. Further the MRAC adaptively controls the plant and tracks the input pitch rate command signal effectively. The main advantage of the proposed scheme is the use of fuzzy generator to change the reference model as opposed to changing the controllers. The effectiveness of the proposed technique is assessed by simulation studies based on a 6- DOF high performance fighter aircraft undergoing pitch rate control at a wide range of operating contingencies.

In this paper, we introduce a direct fractional order adaptive control design based on model reference adaptive control (MRAC) structure for a class of commensurate fractional order linear systems with an arbitrary relative degree, and whose parameters are unknown. By generalising the application of standard direct MRAC strategy to plants described by fractional order models, we develop a fractional adaptive control scheme (FOMRAC) based on the output feedback. We also define an adaptation control law ensuring the stability of the closed-loop system and the good tracking of the reference trajectory. The asymptotic stability of the fractional order control system is proven using an extension of the Lyapunov theorem. Simulation results show the effectiveness of the proposed control method even for plants with model parametric variations and additive noises.

Distributed model reference adaptive containment control of heterogeneous multi-agent systems with unknown uncertainties and directed topologies

Presents an approach to the design and real-time implementation of an adaptive controller for a robotic manipulator based on digital signal processors. The Texas Instruments DSP (TMS320C31) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for robotic manipulators. In the proposed scheme, adaptation laws are derived from the direct model reference adaptive control principle based on the improved Lyapunov second method. The proposed adaptive controller consists of an adaptive feedforward and feedback controller and PI-type time-varying auxiliary control elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for an industrial robot with four joints in the joint space and Cartesian space.

As control systems become integrated with structures in such applications as vibration suppression and structural shape modification, a damage tolerance/mitigation concern must be addressed. The fundamental issue of this concern is whether the controller is robust enough to remain stable after a step change in the structural parameters as a result of impact damage. A secondary issue is whether the controller can continue to perform its intended function (even if at some reduced level of effectiveness) following impact damage. Due to the complexity of the structural system such a controller must be lower-order than the structure that is controlled. This paper builds on previous research by Waters and Balas to demonstrate the effectiveness and limitations of a reduced- order direct model reference adaptive control (DMRAC) algorithm for damage mitigation. The reduced-order model matching conditions for implementing this algorithm and the theoretical stability results are presented. Also presented are simulation results demonstrating the effectiveness of the DMRAC algorithm in forcing a higher-order damaged plant to track a lower-ordered reference model. These simulation results look at matching a second-order plant to a first-order reference model, and a fourth-order plant to both a first- and second-order reference model. The results of these simulations indicate that a reduced-order DMRAC algorithm can, in some cases, effectively stabilize the system following severe damage to the structure, even if the system become inherently unstable. Additionally, the reduced-order DMRAC algorithm still allows for steady state tracking by the damaged smart structure of a reference input.

Bivalirudin is a direct thrombin inhibitor used in the cardiac intensive care unit when heparin is contraindicated due to heparin-induced thrombocytopenia. Since it is not a commonly used drug, clinical experience with its dosing is sparse. In earlier work [1], we developed a dynamic system model that accurately predicts the effect of bivalirudin given dosage over time and patient physiological characteristics. This paper develops adaptive dosage controllers that regulate its effect to desired levels. To that end, and in the case that bivalirudin model parameters are available, we develop a Model Reference Control law. In the case that model parameters are unknown, an indirect Model Reference Adaptive Control scheme is applied to estimate model parameters first and then adapt the controller. Alternatively, direct Model Reference Adaptive Control is applied to adapt the controller directly without estimating model parameters first. Our algorithms are validated using actual patient data from a large hospital in the Boston area.

In this paper, we develop a Direct Model Reference Adaptive Tracking Controller for linear systems with unknown delays, sometimes known as retarded equations. This controller can also reject bounded disturbances of known wave form but unknown amplitude, e.g. steps or sinusoids. We prove that the controller produces global asymptotic tracking with bounded controller gains when the delay-free open-loop plant is almost strictly positive real (equivalently, is minimum phase and has CB positive definite) and the internal delay terms satisfy a linear matrix inequality. The adaptive controller has no knowledge of the delay. An illustrative example is provided.

A parameterization for a linear system is presented to design a direct model reference adaptive pole placement controller. This parameterized model is one of the structured nonminimal models. The exponentially weighted least-squares algorithm is employed to estimate the control parameters. The direct adaptive controller has the exponential weighting properties by the proposed method of selecting the characteristic polynomials of the sensitivity function filters in connection with the reference model.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

It is frequently convenient to use specially structured nonminimal models for parameter estimation such as in the case of direct adaptive control where the model is parameterized in terms of the desired control law parameters. This is done, for example, in direct model reference adaptive control and in direct pole assignment adaptive control algorithms. It is shown that the parameters appearing in these nonminimal models can be uniquely estimated if and only if a certain design identity has a unique solution. The result is used to develop persistency of excitation results for these models.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

A multiple fuzzy reference model adaptive controller (MFRMAC) is proposed for nonlinear aircraft pitch-rate tracking. The controller is developed using a direct model reference adaptive control (MRAC) scheme with variable fuzzy logic reference model. The proposed controller provides a soft reference model switching for the multiple modes of operation of the aircraft without any prohibitive computation or explicit system identification. The effectiveness of the technique is assessed by simulation studies based on a 6-DOF high-performance fighter aircraft model undergoing pitch-rate control at a wide range of operating contingencies. It is demonstrated that the scheme performs extremely well when controlling multimodal dynamic systems, as opposed to conventional MRAC designs.

The force tracking error is dependent on both the position tracking error and the estimated parameter error so that, in constrained adaptive robot control, the convergence of the estimated parameter error becomes more important than in unconstrained adaptive robot control. However, in the direct adaptive controller, the parameter adaptation is driven only by the tracking error in the joint motion, while in the indirect adaptive controller, the parameter estimation is driven only by the prediction error in the joint torque. Based on this observation a new combined direct and indirect adaptive controller driven by both the tracking error and the prediction error is developed for constrained robots with inertia parameter uncertainty. Stability of the combined adaptive controllers is established in the Lyapunov sense. The combined control improves both position and force tracking performance compared with direct adaptive control. The computer simulations are presented to demonstrate the proposed schemes.

This paper describes the development of several controllers to handle a trajectory tracking problem for a differentially wheeled robot. Both simulations and tests on a real robot were performed. A simple kinematic controller has been implemented to calculate desired velocities based on current position and trajectory. In order to also consider the current velocities, i.e. the dynamics of the system, the output of this controller was used as input to a dynamic controller derived from a nonlinear model. The dynamic controller was made adaptive by using an on-line parameter estimation scheme to estimate the unknown parameters of the nonlinear model. Lastly, a direct model reference adaptive controller (MRAC) based on a linear model was derived and implemented as an alternative to the adaptive dynamic controller.

The modified positive position feedback (MPPF) controller, an active vibration control method that uses collocated piezoelectric actuator actuators and sensors, is developed using an adaptive controller. The adaptive mechanism consists of two main parts: (1) frequency adaptation and (2) adaptive controller. Frequency adaptation only tracks the frequency of vibrations using fast Fourier transforms. The obtained frequency is then fed to MPPF compensators and the adaptive controller. This provides a unique feature for MPPF by extending its domain of capabilities from controlling tonal vibrations to broadband disturbances. The adaptive controller mechanism consists of a reference model that is of the same order as the MPPF system and its compensators. The adaptive law provides the additional control force that is needed for controlling frequency changes caused by broadband vibrations. The experimental results show that the frequency adaptation method that is derived has worked quite well. The results also indicate that the MPPF can provide significant vibration reduction on a cantilever beam that is used throughout the experiments.

The problem of direct model reference adaptive control for multi input multi output (MIMO) uncertain plants with unknown high frequency gain matrix (HFGM) is addressed in the paper. Two schemes of adaptive control algorithms using augmented error estimators and relaxed assumption concerning HFGM are proposed. It is assumed that the minimum of modulus of HFGM determinant is known. The first scheme involves the resettable approximation of the inversion of HFGM estimate in control law. The second scheme is based on modification of conventional augmented error estimator by introduction of a switched projection mechanism. The proposed theoretical ideas are wrapped up by simulation examples.

A fiber laser is easily applied for micro welding owing to the excellent beam quality. Furthermore, a fiber laser is expected to be a promising heat source for adaptive control since the peak power is variable within sub-micro-second period. The objective of the research was to develop a new laser system with inprocess monitoring and adaptive control for the stable production of sound welds in thin sheets. The bead-on–plate welding of 0.1 mm-thick stainless steels was performed with a 75 W fiber laser beam of 1,090 nm wavelength. The stability of bead widths of laser welds made with or without monitoring and adaptive control was investigated in welding the sheet on the plate with a hole which should affect heat conduction and transfer. It was revealed that the heat radiation signal was sensitive to the increase in the bead width according to the change from heat transfer process to heat-insulated process. Moreover, the peak power was adaptively controlled in the minimum 50 ms-short period in order to produce stable weld bead width regardless of the existence or absence of the heat transfer plate. Consequently, it was confirmed that the fiber laser was an excellent oscillator for laser micro welding as well as for adaptive control.