Alexander Schirrer

Vibration Damping of a Flexible Car Body Structure Using Piezo-Stack Actuators

In this work piezo-stack actuators mounted in consoles are utilized to actively dampen vibrations of a flexible car body structure by introducing bending moments. Using an example of a heavy metro vehicle the complete design for the active vibration damping system is presented. Both analytical modeling and a system identification of the vehicle are described, issues of modal representation and model reduction are covered, and a robust controller design is motivated and explained. The excellent performance of the proposed method is documented by both experimental results from a scaled model and an extensive co-simulation of the overall system.

Overview and Motivation

The first chapter is introduced by a short motivation for the ACFA 2020 project given by the “ACARE vision 2020”. The ACFA 2020 project is presented in a concise way, listing the main goals and the associated deliverables together with some key numbers of the project. In order to set the background of the research work done, a section on the state of the art in aircraft configurations is contained. A special emphasis is given to European developments in advanced blended wing body (BWB) aircraft configurations, followed by a section on recent developments in aircraft conceptual design modeling and simulation methods. A section on control concepts for automatic flight control systems concludes the chapter, where both load alleviation and handling qualities are covered.

Cooperative Fuzzy Model-Predictive Control

In this paper, a cooperative fuzzy model-predictive control (CFMPC) is presented. The overall nonlinear plant is assumed to consist of several parallel input-coupled Takagi-Sugeno (T-S) fuzzy models. Each such T-S fuzzy subsystem is represented in the form of a local linear model network (LLMN). The control of each local linear model in each LLMN is realized by model-predictive control (MPC). For each LLMN, the outputs of the associated MPCs are blended by the fuzzy membership functions, which leads to a fuzzy model-predictive controller (FMPC). The resulting structure is one FMPC for each LLMN subsystem. Overall, a parallel combination of FMPCs results, which mutually affects all LLMN subsystems by their respective manipulated variables. To compensate detrimental cross-couplings in this setup, a cooperation between the FMPCs is introduced. For this cooperation, convergence is proven, and for the closed-loop system, a stability proof is given. It is demonstrated in a simulation example that the proposed input-constraint CFMPC algorithm achieves convergence of the fuzzy LLMNs within few cooperative iteration steps. Simulations are given to demonstrate the effectiveness of the theoretical results.

Linear parameter-varying control of a large blended wing body flexible aircraft

Abstract In this paper a linear parameter-varying (LPV) controller design approach is applied to the longitudinal dynamics of a large blended wing body aircraft. The method is based on parameter-dependent Lyapunov functions utilizing the information given by bounds for the maximum parameter rate of variation. The entire parameter space is approximated by a set of linearized models in trimmed operating points which leads to a finite-dimensional convex optimization problem. Typical design goals for flexible aircraft control such as handling qualities, loads and vibration reduction were considered with the Mach number as scheduling parameter. The obtained LPV controller is extensively tested, and the obtained results demonstrate the high potential of the methodology for flexible aircraft control.

A comprehensive robust control design and optimization methodology for complex flexible-structure systems

Robust control design for complex flexible structures involves many consecutive essential steps. Additionally, many design parameters arise, which turn design optimization into a cumbersome and difficult task. This paper presents a comprehensive robust ℋ∞-optimal control design methodology for this class of systems. It relies on a pragmatic approach: The control engineer produces an initial design and reuses it in subsequent design iterations and parameter optimization. The methodology is illustrated by a large transport aircraft model and shows high potential to obtain and tune robust high-performance controllers. Expert knowledge and design decisions are introduced in a natural, clearly structured way, while control engineers are relieved from repetitive design tasks which are safely automated.

LQ-based design of the inner loop lateral control for a large flexible BWB-type aircraft

Two LQ-based MIMO controllers (LQG and LQI architectures) for lateral inner loop flight control for a large BlendedWing Body (BWB) passenger aircraft pre-design model are presented. The main control goals are Dutch roll mode damping, coordinated turn, and roll response shaping. An open loop analysis shows that traditional SISO design faces fundamental limitations, so both controller variants are designed as MIMO controllers. Their performance is tuned and evaluated, and their specific properties are discussed and compared. The controllers are validated on various fuel and payload mass cases and fulfill all demanded goals. Ongoing and future research seeks to reduce structural loads and increase passenger comfort using robust control design methods.

Robust H∞ Control Design Parameter Optimization via Genetic Algorithm for Lateral Control of a BWB type Aircraft

Abstract This work presents a comprehensive, optimization-based robust control design approach: utilizing DK-iteration control synthesis and closed-loop evaluation via goal attainment, a genetic algorithm optimizes this design-and-validation process in its free design parameters. This method is applied to a lateral flight control design task for a flexible, large Blended Wing Body (BWB) aircraft configuration. Control goals include time-domain rigid-body response specifications and loads alleviation objectives. First optimization results yield a robust controller that, although not fulfilling all posed goals yet, strongly reduces structure loads compared to an initial design.

Robust Convex Lateral Feedback Control Synthesis for a BWB Aircraft

Abstract This paper presents the robust multi-objective design of a lateral feedback control law for a large flexible blended wing body (BWB) type passenger aircraft. An initial controller is synthesized and optimized using a convex synthesis approach based on the Youla parameterization and an LMI formulation. A multitude of both time- and frequency-domain design constraints are considered aiming to improve disturbance rejection. The obtained control law is numerically validated on several mass cases of the aircraft model, showing high loads alleviation and vibration reduction performance while obeying all stringent design constraints.

An advanced criterion for optimal actuator and sensor placement on complex flexible structures

Abstract In a comprehensive control design approach for flexible mechanic structures, such as lightweight vehicles or aircraft, a vital decision is the positioning and design of actuators and sensors for the control tasks. This paper proposes an optimal placement approach that exploits the special structure of flexible mechanical systems and incorporates controllability/observability based measures as well as further knowledge on actuator and sensor properties. It combines the advantages of state of the art positioning criteria such that a balance between low and high frequency modes is assured and at the same time applicability to complex systems in arbitrary system coordinates is guaranteed. These essential properties are illustrated on a clamped beam. The controlled system is studied in terms of the generalized plant description, as it is common in robust control design. Thus it serves as natural extension to the controller design process later on and enables comprehensive control design optimization at an early stage.

Dynamic matrix control applied to emission control of a diesel engine

In this paper we suggest a hierarchical control scheme, applicable to engine control. The chosen setup facilitates the simultaneous control of emissions and torque. On the top level a standard PID controller is installed, setting the injection quantity in order to reach the demand torque, which is a prerequisite to follow a given load profile. The second level is dedicated to the emission control. We apply dynamic matrix control (DMC), which is a specific form of model predictive control. DMC stands out by a very simple way of modeling the controlled process which is represented by step responses. Constraints on the absolute values and maximum rates of change are applied to the manipulable system inputs to cope with given hardware limitations. Moreover, we incorporate so-called operational constraints, thus constraining the input variables to certain polytopic operating regions. Thereby areas with high HC emissions can be excluded in advance. Furthermore we include the predefined demand torque as input to the DMC. With the known impact of transient torque changes on the emissions, the DMC can act in an optimal way with respect to the given load profile. To cope with the nonlinearities of a combustion engine, we apply a network of several DMCs, scheduled by engine speed and load as well as by the manipulable actuators. We also propose a procedure to reduce the amount of modeling data, by introducing a parameterized formulation of the measured step responses. The proposed control concept is then evaluated on a realistic, physically-based engine model for several representative driving sequences, amongst them the well-known New European Driving Cycle (NEDC) and the highly dynamic Worldwide Harmonized Light Duty Test Cycle (WLTC). The advantages of DMC against a conventional PID control are finally summarized and demonstrated on a typical load step.