This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

In this paper, we present two novel algorithms to realize a finite dimensional, linear time-invariant state-space model from input-output data. The algorithms have a number of common features. They are classified as one of the subspace model identification schemes, in that a major part of the identification problem consists of calculating specially structured subspaces of spaces defined by the input-output data. This structure is then exploited in the calculation of a realization. Another common feature is their algorithmic organization: an RQ factorization followed by a singular value decomposition and the solution of an overdetermined set (or sets) of equations. The schemes assume that the underlying system has an output-error structure and that a measurable input sequence is available. The latter characteristic indicates that both schemes are versions of the MIMO Output-Error State Space model identification (MOESP) approach. The first algorithm is denoted in particular as the (elementary MOESP scheme)...

Subspace model identification-Part 1. The output-error state-space model identification class of algorithms

We report experimental results that show a large and symmetric population of D and L crystals moving
into complete chiral purity, with one of the enantiomers completely disappearing. The results indicate (i) a
new symmetry breaking process incompatible with the hypothesis of an initial single chiral phase or
‘‘mother crystal,’’ (ii) that total symmetry breaking and complete chiral purity can be achieved from a
system that initially includes both enantiomers, and (iii) that this is achieved through a nonlinear
autocatalytic-recycling process.

Chiral Symmetry Breaking during Crystallization: Complete Chiral Purity induced by Nonlinear Autocatalysis and Recycling

In this paper, techniques from geometric mechanics and geometric nonlinear control theory are applied to modeling and construction of trajectory tracking algorithms for a free-swimming underwater vehicle that locomotes and maneuvers using a two-link actuated ldquotailrdquo and independently actuated ldquopectoral finrdquo bow planes. Restricting consideration of fluid forces to the simple effects of added mass and quasi-steady lift and drag, the resulting system model can be expressed in a control-affine structure. With particular choices of oscillatory actuation of the four system joints, maneuvers such as swimming forward, in and out of plane turning, surfacing, and diving can be constructed. Further, the vehicle and model can generate agile maneuvers such as snap turns. Trajectory tracking can then be produced using state error feedback. The methods are demonstrated both in simulation and in experiment using the University of Washington prototype fin-actuated underwater vehicle.

Geometric Methods for Modeling and Control of Free-Swimming Fin-Actuated Underwater Vehicles

The large-scale power systems are liable to performance deterioration due to the presence of sudden small load perturbations, parameter uncertainties, structural variations, etc. Due to this, modern control aspects are extremely important in load frequency control (LFC) design of power systems. In this paper, the LFC problem is illustrated as a typical disturbance rejection as well as large-scale system control problem. For this purpose, simple approach to LFC design for the power systems having parameter uncertainty and load disturbance is proposed. The approach is based on two-degree-of-freedom, internal model control (IMC) scheme, which unifies the concept of model-order reduction like Routh and Pade approximations, and modified IMC filter design, recently developed by Liu and Gao [24]. The beauty of this paper is that in place of taking the full-order system for internal-model of IMC, a lower-order, i.e., second-order reduced system model, has been considered. This scheme achieves improved closed-loop system performance to counteract load disturbances. The proposed approach is simulated in MATLAB environment for a single-area power system consisting of single generating unit with a non-reheated turbine to highlight the efficiency and efficacy in terms of robustness and optimality.

Load Frequency Control in Power Systems via Internal Model Control Scheme and Model-Order Reduction

A tutorial review on process identification from step or relay feedback test

Analytical design of two-degree-of-freedom control scheme for open-loop unstable processes with time delay

The paper extends a recently published Smith predictor scheme for controlling integrating and unstable processes with time delay, which results in a simpler control structure and improved tuning capacities for reference inputs and load disturbances. In the proposed scheme, a proportional controller is subtly employed to stabilise the setpoint response, and then an H2 optimal controller is analytically designed for setpoint tracking. To obtain the integral-squared-error (ISE) performance objective, a practically desired disturbance rejection transfer function is proposed to design the disturbance estimator in the inner closed loop of the proposed control structure. Essentially, the proposed control structure gives two-degrees-of-freedom (2DOF) control and correspondingly the setpoint and load disturbance responses can each be tuned conveniently by a single control parameter. Hence the setpoint response is decoupled from the load disturbance response, and both can be quantitatively estimated in terms of the proposed analytical tuning procedures. Simulation examples are included to show the superiority of the proposed method.

New modified Smith predictor scheme for integrating and unstable processes with time delay

IMC-based iterative learning control for batch processes with uncertain time delay

http://www.nt.ntnu.no/users/skoge/prost/proceedings/ifac11-proceedings/data/html/papers/1024.pdf

Tao Liu

Papers

A tutorial review on process identification from step or relay feedback test

Analytical design of two-degree-of-freedom control scheme for open-loop unstable processes with time delay

New modified Smith predictor scheme for integrating and unstable processes with time delay

IMC-based iterative learning control for batch processes with uncertain time delay

Robust two-dimensional iterative learning control for batch processes with state delay and time-varying uncertainties