Improved guaranteed cost control and quantum adaptive control are developed in this study for a quadrotor helicopter with state
delay and actuator faults. Improved guaranteed cost control is designed to eliminate disturbance effects and guarantee the robust stability of a
quadrotor helicopter with state delay. The inapplicability of guaranteed cost control to the quadrotor linear model is addressed by combining
guaranteed cost control with a model reference linear quadratic regulator. In the event of actuator faults, quadrotor tracking performance is
maintained through quantum adaptive control. Finally, the availability of the proposed scheme is verified through numerical simulation
The 4.0 kbit/s speech codec described in this paper is based on a
Frequency Domain Interpolative (FDI) coding technique, which
belongs to the class of prototype waveform Interpolation (PWI)
coding techniques. The codec also has an integrated voice
activity detector (VAD) and a noise reduction capability. The
input signal is subjected to LPC analysis and the prediction
residual is separated into a slowly evolving waveform (SEW) and
a rapidly evolving waveform (REW) components. The SEW
magnitude component is quantized using a hierarchical
predictive vector quantization approach. The REW magnitude is
quantized using a gain and a sub-band based shape. SEW and
REW phases are derived at the decoder using a phase model,
based on a transmitted measure of voice periodicity. The spectral
(LSP) parameters are quantized using a combination of scalar
and vector quantizers. The 4.0 kbits/s coder has an algorithmic
delay of 60 ms and an estimated floating point complexity of
21.5 MIPS. The performance of this coder has been evaluated
using in-house MOS tests under various conditions such as
background noise. channel errors, self-tandem. and DTX mode
of operation, and has been shown to be statistically equivalent to
ITU-T (3.729 8 kbps codec across all conditions tested.
This book addresses two aspects of network operation quality; namely, resource
management and fault management.
Network operation quality is among the functions to be fulfilled in order to offer
quality of service, QoS, to the end user. It is characterized by four parameters:
– packet loss;
– delay;
– jitter, or the variation of delay over time;
– availability.
Resource management employs mechanisms that enable the first three parameters
to be guaranteed or optimized. Fault management aims to ensure continuity of service.
It is more than a decade since GSM was first commercially available. After some unexpected delay, it
seems that finally UMTS is here to stay as a 3G system standardised by 3GPP, at least for another ten
years. UMTS will enable multi-service, multi-rate and flexible IP native-based mobile technologies to be
used in wide area scenarios and also pave the way for a smooth transition from circuit switched voice
networks to mobile packet services.
Mobile radio communications are evolving from pure telephony systems to multimedia
platforms offering a variety of services ranging from simple file transfers and audio and
video streaming, to interactive applications and positioning tasks. Naturally, these services
have different constraints concerning data rate, delay, and reliability (quality-of-service
(QoS)). Hence, future mobile radio systems have to provide a large flexibility and scal-
ability to match these heterogeneous requirements.
With the proliferation of cloud computing and Internet online services, more and
more data and computation are migrated to geographical distributed Internet data
centers (IDCs), which can provide reliability, management, and cost benefits.
However, IDC operators encounter several major problems in IDC operations, such
as huge energy consumption and energy cost, and high carbon emission. To deal
with the above problems, IDC operators have to efficiently manage the way of
energy consumption and energy supply. Considering the potential of smart grid, we
focus on the energy management of IDCs in smart grid from several perspectives,
i.e., power outage, carbon emission, heterogeneous service delay guarantees, and
operation risk.
In this chapter we give a quick overview of control theory, explaining why
integral feedback control works, describing PID controllers, and summariz-
ing some of the currently available techniques for PID controller design.
This background will serve to motivate our results on PID control, pre-
sented in the subsequent chapters.
