System decomposition

The development process starts with the analysis phase and is then followed by the design phase (see the left part of the V-model in Figure 1-1). The development process starts with abstract and textual descriptions of the requirements, followed by translating them into technical specifications and then continues with detailed model-based system engineering design solutions (Nazareth & Siwy, 2013).

1.3.1.1 System Analysis

In the system analysis phase, the functional and non-functional requirements of the system are specified and then translated into technical specifications. According to the Automotive SPICE® RPM, the system analysis phase consists of the requirement elicitation and the requirement analysis steps (Automotive SIG, 2010).

The requirement elicitation (which is also referred to as customer requirements) is a textual documentation of the system behaviour extracted from customer’s needs and requirements analysis (Automotive SIG, 2010). The requirements are usually written in natural language and consist of two types of documents: the functional requirements which define the system anticipated functionalities and the non-functional requirements which define how these functionalities are expected to be performed. The non-functional requirements are the system qualitative behaviours such as price, fault tolerant, flexibility, robustness, scalability and so on (Glinz, 2007, October).

The requirements analysis (also referred to as System Specification) is the process of translating the customer requirements into a set of technical specifications that will guide the design of the system (Automotive SIG, 2010). The requirements are usually written in an informal language (what the user expects from the system) whereas the specifications are written in more formal and technical language and sometimes contain references to the standards and engineering norms ( Loucopoulos & Karakostas, 1995).

1.3.1.2 System design

System Design is a systematic process by which a technical solution for the system under development (SUD) is derived to satisfy the specified requirements (Ertas, 1996). The output of the design phase is being used in the system implementation and integration phases whereas the system specifications and requirements are being used for system validation and verification.

There are several methodologies that have been proposed for the design process of a system (Ertas, 1996). VDI 2206 is a widely-accepted guideline (including design stages) for mechatronic system development (VDI 2206, 2004) and Automotive SPICE®Process Reference Model (RPM) is a procedure developed by a joint group of top automotive manufacturers to unify and evaluate the process of embedded system development among automotive industries (Automotive SIG, 2010). The using of Model Based Development (MBD) methodology together with the V-model development process is a well- accepted approach for control system development ( Nicolescu & Mosterman, 2010). In the MBD approach, the mathematical formulation of the system dynamics are modelled and represented graphically in order to provide a common environment across different engineering disciplines, which lead to a simplified and more efficient design process. Moreover, the low-level machine codes can be seamlessly generated from the models causing a dramatic reduction in time and cost required for system implementation and testing. By taking the Model-Based development approach, a modified V-model for control system design of redundant systems is proposed in this dissertation. The proposed design process consists of five main steps and several feedback loops as shown in Figure 1-2.The main steps towards designing a (redundant) control system are as follow:

1. System architectural design 2. System modelling

3. High-Level Control Design 4. Control Allocation

Figure 1-2: : V-model for redundant system control system design

By considering the final product as a controlled plant (here, a vehicle), which has been equipped with several sensors, actuators and controllers, the purpose of the system architectural design is to define the main building blocks of the control system, design the system topology, specify the control logics among them and assign each block’s functionalities based on the system specifications (Gordon, Howell, & Brandao, 2003).

In the system modelling step, the conceptual and mathematical representations of the system dynamics are derived. The system modelling is the key step in model-based design (MBD) approach. To deal with the model complexity, the system dynamics could be decomposed into several hierarchical layers: the top layer is the (linear or non-linear) model of plant dynamics and the (linear or non- linear) models of actuators dynamics located in the following sub-layers. The accuracy of the derived models shall be verified by analysing the simulation results before using these models in the next control development stages (Bringmann & Krämer, 2008).

The purpose of the high-level control development is to design a feedback control law to make the top level model (plant dynamics) output track the desired reference value asymptotically. The output of the high-level controller is

a set of virtual force and moments without specifying how to generate them through the actual redundant actuators. In other word, to design the high-level control, the rigid body plant dynamics is considered and any actuator (low-level) dynamics is ignored.

In the real world these forces and moments are not generated directly, but through several actuators and effectors equipped in the system. Effectors are mechanical devices that can be used in order to generate time-varying mechanical forces and moments on the mechanical systems. Actuators are electromechanical devices that are used to control the magnitude and/or direction of forces and moments generated by the individual effectors (Johansen & Fossen, 2012). In case of system redundancy (i.e. the number of the available actuators is greater than the number of the generalised forces and moments intended to be controlled in the high-level control) a Control Allocation

(CA) scheme can be employed to optimally distribute the virtual forces and

moments in to each available actuator considering both actuation amplitude and rate constraints.

By assuming the output of control allocation as a reference for each of the available actuators and by considering the actuator dynamics, a control law is employed such that for any smooth reference path, the output of the low-level controllers will track the reference values asymptotically.