Control Design
The solution to complex nonlinear multivariable control problems,
like integrated chassis control and collision avoidance, requires the combination of the
advantages of a number of different control approaches. This is
due to the fact that most of the established approaches in control
theory only focus on certain aspects of the problem and thus will
not address it completely. For instance, nonlinear control methods
usually offer good solutions for global stabilisation and
adaptation but they only poorly address robustness and local
performance issues. On the other hand classical frequency domain
multivariable control techniques achieve excellent local
performance and robustness with respect to unmodelled dynamics but
nonlinear off-equilibrium global stability
and constraint handling are not addressed.
Consequently, the focus of the control part of the project will be on
the four complementary techniques described next.
Classical Multivariable Control Analysis and Design.
An appealing small-signal frequency-domain framework that holds
great promise for the integrated control of complex dynamical
systems such as embedded automotive systems is known as Individual
Channel Analysis and Design. The ICAD
methodology provides a framework within which control concepts and
methods from classical control engineering - Nyquist-Bode plots,
gain and phase robustness margins - may be rigorously applied to
strongly cross-coupled multi-input multi-output (MIMO) systems. It
thus preserves continuity with industrial practice while providing
much needed analytic insight of a graphical nature into both the
uncontrolled and controlled dynamics of growing complex systems.
How this works within ICAD is that, without loss of structural
information, an m-input m-output feedback control problem can be
decomposed into m individual single-input single-output (SISO)
channels; that is each controlled output is naturally paired to a
reference or command input. Each individual channel thereby has
its own SISO performance specification since the customer's
requirements are most clearly stated in terms of the dynamical
response of an output to its associated input.
ICAD is first and foremost an analysis capability of the potential and limitations for
the embedded control of complex systems. Moreover, ICAD, as well
as guiding control systems design for complex systems, can
integrate and assess the robustness and performance of other
subsystem designs (Classical, Explicit Constrained Optimal
Control, H-Infinity, LQR) within the overall composite system.
We have a range of previous applications of ICAD to the integrated control of large complex systems, including aerospace (helicopter and fixed
wing) control and distributed
embedded generation power systems. The aerospace
work is particularly relevant here in the context of embedded
automotive control. This is because there are similar control
requirements in the face of higher levels of systems integration
(flight control systems, engines, utilities), stronger
cross-coupling, many more inputs/outputs (control surfaces),
actuator redundancy; and not least, more demanding performance
requirements in the form of tighter control (manoeuvreability).
While, in principle, some of the theoretical issues associated
with ICAD have already been tackled, we can identify a number of
key theoretical developments which must take place for
exploitation of the approach within complex automotive
applications. Thus, further sub-objectives in line with
the theoretical and application-orientated
objectives of the project are identified:
- Which outputs are best controlled by which inputs? Develop
systematic methods for assigning input-output pairs based upon
multivariable structure elucidated by ICAD.
- Investigate issues of redundancy in actuators and actuator failure
compensation.
- Evaluate local controllers of all the partners for application studies.
Hybrid Control Systems
Vehicle control systems may have the following requirements:
- They must be designed to operate robustly in environments that are subject to abrupt change,
\item they should provide high performance over a wide range of operationg conditions and in the presence of severe actuator and state constraints and,
- they should be robust to component and subsystem failures.
These requirements imply the use of hybrid control techniques combining continuous and discontinuous control. The area has received much attention
form the academic community over the past decade. Within the project we will focus our investigation of hybrid control on two topics:
Multiple Controllers are used for stabilising systems with structural changes (caused by internal failures or external events) and severe nonlinearities and for improving performance in adaptive systems(see WP3.4). Important examples are graceful degradation in the event of component failures and fast response of the control system to abrupt changes such as varying road conditions or wheels loosing contact to the ground in the event of rollover.
In such events the control strategy will be changed by switching between different controllers or controller parameters. The two main issues arising in multiple controller approaches are stability of the overall system and the handling of transients which may be caused by the structural changes. Whith respect to the stability issue we will exploit recent approaches to control design and realisation techniques by adopting them to the automotive control setting. With respect to transient handling there are reference trajectory resetting techniques.
In addition to this, the fact that multiple actuators are available within
complex control problems (overactuation) introduces questions of
how to combine and coordinate multiple controllers in an optimal
way. Some key issues are:
- Investigate how to utilize overactuation to achieve maximal robustness
against time-variations (for example due to road conditions and
other traffic).
- Study how to design controllers that recover from undesired states
and integrate them with a stationary
controller for normal operation near a desired equilibrium (with
all four wheels utilized).
The items are highly relevant for the study of car dynamics.
Based on extending recent results, the overall objective is to combine local and global controllers to
achieve globally acceptable performance.
Constraint handling and anti-windup
Recent studies have shown
that the solution to a wide class of constrained dynamic
optimization problems can be explicitly computed and represented
as a piecewise linear state feedback. This can be exploited to
implement constrained optimal feedback control simply by
evaluating a piecewise linear mapping, or through lookup tables.
For automotive embedded systems where real-time optimization is
generally avoided due to high demands for computations and
software reliability issues, this is an interesting approach for
multi-variable constrained control problems. Currently, such
techniques have been tested in automotive applications. However, these methods are not
straightforward to apply in complex problems with a large number
of states and inputs, due to the rapid increase in complexity of
the solution when the dimension of the problem increases. Also,
the use of such methods for nonlinear problems is fairly
undeveloped. We will extend recently developed ideas
of explicit constrained control to be applied in more complex
automotive applications.
Control allocation is commonly used in advanced vehicle motion
control systems in order to generate a total longitudinal force,
lateral force, and yaw moment requested from a higher level
controller, using a redundant set of actuators. This
is useful in automotive vehicles for example in extreme maneuvers
during collision avoidance using a redundant combination of
steer-by-wire and brake-by-wire. One of the main objectives of the
control allocation module is to explicitly handle constraints such
that one is guaranteed to attain the requested total control force
whenever possible. This is important from a safety point of view
when the vehicle operates close to its physical limitations.
Another great benefit of control allocation is that it allows
simple reconfiguration in case of an actuator failure. Recent
research in this direction, indicate that
nonlinear control allocation can be implemented using some
versions of optimizaton-based control that can be implemented with
high reliability and low computational complexity, and is
therefore suited for embedded automotive real-time control
systems. Actuator position and rate constraints leads to a hybrid
behaviour of such control allocation solutions, since the strategy
will essentially switch when different combinations of actuators
saturate as a response to a time-varying total force request from
the higher level control system. We will extend the results
\cite{Joh04a} and provide reliable numerical implementation for
use in automotive applications.
Multivariable Control Systems with time delay
Loop shaping with delay robustness
The literature contains numerous criteria for robustness
analysis with respect to time-varying delays in a feedback system.
However most of the criteria are based on advanced optimization and
are difficult to use in controller design. Within the project we will
develop improved frequency domain
design criteria that also take into account a bound on delay variation rate.
Linear delay compensation schemes
Sometimes it is possible to put a time stamp on each measurement
signal that is sent over the network, so that the network induced delay can be
measured on arrival. Such information can be used to improve control
performance considerably. The objective in this
project would be to introduce a linear delay compensator in analogy with
anti-windup schemes. Intuitively, a measurement that arrives late
should have less impact on the control action than one that is very
fresh. Within WP3 this intuititive rule will be formalised and
its consequences will be analysed.
Non-linear compensation schemes for automotive applications
Nonlinear control loops in automotive applications offer very concrete
challenges where measurement delays can be crucial. One example is in
control of ABS brakes, where maximal braking force requires very fast
feedback in order to prevent wheel-lock. Another example is in the
stabilization of vehicle dynamics, where again fast feedback is
crucial under safety-critical circumstances. Consequently, an objective of
WP3 will be to quantify the delay margin in order to optimize
performance without sacrificing safety.
Nonlinear and adaptive control
Automotive vehicles are characterized by highly non-linear, uncertain
and time-varying dynamics. This is due to inherent dynamic properties
such as Coriolis forces that are significant in extreme maneuvers, but more importantly
it is due to the complex phenomena of tyre/road friction. In addition to being
characterized by strongly nonlinear characteristics, friction depends
on environmental properties such as the road conditions, and vehicle
properties such as tyre type, wear and pressure. Any advanced automotive
control system, such as collision avoidance or active body control,
must therefore either address this directly, or rely on lower-level decentralized control systems that
hide the nonlinearity and uncertainty from the perspective of the high-level
control function. The issue of adaptive and nonlinear control must therefore
be addressed explicitly at some level in the control hierarchy. The current
state-of-the-art is dominated by ad hoc solutions that are expensive
to maintain and requires considerable effort to redesign for a new vehicle
model or series.
Within the present project we will focus on model-based nonlinear and
adaptive control alternatives,
which has the benefit that the control software
is generic in the sense that it is parameterized in terms of vehicle parameter,
such that only a small effort is required for redesign.
Particular focus will be given to improving transient performance in adaptive control via switched control.
Adaptive control systems will adapt their paramters to any changes in the
dynamics or characteristics of the system under control or its environment.
A major challenge for any adaptive control system is to achieve fast response
to rapid, or instantaneous, changes in the system under control. The relevant
concepts to understand this is uncertainty and information, as the decision to
change the parameters of the controller will be based on uncertain information, due
to model structure errors, measurement errors and unknown external disturbances
acting on the system. In order to reduce sensitivity to such uncertainty, any practical
adaptive control systems will include a large degree of filtering and low adaptation
gain that will lead
to reduced speed of response due to the phase lags being introduced by the filters
and the low gain of the adaptation. In order to improve on the transient performance
in such cases, it has been suggested to switch parameter estimates within the adaptive
controller based on a model-based monitoring of the system under control and the references therein. Yet, the fundamental
issues related to robustness to uncertain and missing information are still
far from fully understood, and within the project we will seek to provide new
insight on how to design for high transient performance in nonlinear adaptive
control systems. Fault-tolerant control is a closely related issue that.
The methods will also enable the implementation of a systematic approach to
fault-tolerant control and automatic reconfigurability to accomodate sudden
changes in the vehicle and its environment, and failures in sensors, actuators, or
communication. This line of work may benefit strongly from the development of
nonlinear vehicle observers, as such observers can be used as an integral part
of the system performance monitoring, although alternative
estimation methods are also available.
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Vehicle Active Safety
Integrated Chassis Control
Control Design
Vehicle State Observation
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