"e;Recent Advances in Intelligent Control Systems"e; gathers contributions from workers around the world and presents them in four categories according to the style of control employed: fuzzy control; neural control; fuzzy neural control; and intelligent control.
Design of Observer-based Compensators facilitates and adds transparency to design in the frequency domain which is not as well-established among control engineers as time domain design.
Converse Lyapunov function theory guarantees the existence of strict Lyapunov functions in many situations, but the functions it provides are often abstract and nonexplicit, and therefore may not lend themselves to engineering applications.
Hopping, climbing and swimming robots, nano-size neural networks, motorless walkers, slime mould and chemical brains - "e;Artificial Life Models in Hardware"e; offers unique designs and prototypes of life-like creatures in conventional hardware and hybrid bio-silicon systems.
Controlling Chaos achieves three goals: the suppression, synchronisation and generation of chaos, each of which is the focus of a separate part of the book.
Anti-personnel Landmine Detection for Humanitarian Demining reports on state-of-the-art technologies developed during a Japanese National Research Project (2002-2007).
Model Predictive Control System Design and Implementation Using MATLAB(R) proposes methods for design and implementation of MPC systems using basis functions that confer the following advantages: - continuous- and discrete-time MPC problems solved in similar design frameworks; - a parsimonious parametric representation of the control trajectory gives rise to computationally efficient algorithms and better on-line performance; and - a more general discrete-time representation of MPC design that becomes identical to the traditional approach for an appropriate choice of parameters.
Stability theory has allowed us to study both qualitative and quantitative properties of dynamical systems, and control theory has played a key role in designing numerous systems.
Real-time Iterative Learning Control demonstrates how the latest advances in iterative learning control (ILC) can be applied to a number of plants widely encountered in practice.
Defects in semiconductors have been studied for many years, in many cases with a view toward controlling their behaviour through various forms of "e;defect engineering"e;.
This book integrates a wide range of research topics related to and necessary for the development of proactive, smart, computers in the human interaction loop, including the development of audio-visual perceptual components for such environments; the design, implementation and analysis of novel proactive perceptive services supporting humans; the development of software architectures, ontologies and tools necessary for building such environments and services, as well as approaches for the evaluation of such technologies and services.
"e;Introduction to Embedded System Design Using Field Programmable Gate Arrays"e; provides a starting point for the use of field programmable gate arrays in the design of embedded systems.
Discontinuous Systems develops nonsmooth stability analysis and discontinuous control synthesis based on novel modeling of discontinuous dynamic systems, operating under uncertain conditions.
"e;Mechanics and Control of Soft-fingered Manipulation"e; introduces a new approach to the modeling of fingertips that have a soft pad and a hard back plate, similar to human fingers.
Modern technical advancements in areas such as robotics, multi-body systems, spacecraft, control, and design of complex mechanical devices and mechanisms in industry require the knowledge to solve advanced concepts in dynamics.
"e;Reliability and Risk Issues in Large Scale Safety-critical Digital Control Systems"e; provides a comprehensive coverage of reliability issues and their corresponding countermeasures in the field of large-scale digital control systems, from the hardware and software in digital systems to the human operators who supervise the overall process of large-scale systems.
Stabilization, Optimal and Robust Control develops robust control of infinite-dimensional dynamical systems derived from time-dependent coupled PDEs associated with boundary-value problems.
Optimal Control of Wind Energy Systems is a thorough review of the main control issues in wind power generation, covering many industrial application problems.
Nonlinear and Adaptive Control with Applications provides a detailed treatment of the design of robust adaptive controllers for nonlinear systems with uncertainties.
Here you’ll find a comprehensive insight into the intelligence and dexterity of robotic multi-fingered hands from both the physical and control-theoretic viewpoints.
Precision Motion Control focuses on enabling technologies for precision engineering - issues of direct importance to be addressed in the overall system design and realization: precision instrumentation and measurement, geometrical calibration and compensation, and motion control.
Information consensus guarantees that robot vehicles sharing information over a network topology have a consistent view of information critical to the coordination task.
Stochastic control is one of the methods being used to find optimal decision-making strategies in fields such as operations research and mathematical finance.
Recent rapid globalisation of manufacturing industries leads to a drive and thirst for rapid advancements in technological development and expertise in the fields of advanced design and manufacturing, especially at their interfaces.
Networked control systems (NCS) confer advantages of cost reduction, system diagnosis and flexibility, minimizing wiring and simplifying the addition and replacement of individual elements; efficient data sharing makes taking globally intelligent control decisions easier with NCS.
"e;Designing Inclusive Futures"e; reflects the need to explore, in a coherent way, the issues and practicalities that lie behind design that is intended to extend our active future lives.
Identification of Continuous-time Models from Sampled Data presents an up-to-date view of this active area of research, describing recent methods and software tools and offering new results in areas such as: time and frequency domain optimal statistical approaches to identification; parametric identification for linear, nonlinear and stochastic systems; identification using instrumental variable, subspace and data compression methods; closed-loop and robust identification; and continuous-time modeling from non-uniformly sampled data and for systems with delay.
