Rapid Control Prototyping Platform for the Design of Control Systems for Automotive Electromechanical Actuators

This article introduces and discusses the development of a low-cost Rapid Control Prototyping Platform (RCPP). The aim of RCPP is to automate design of control algorithm of electromechanical actuators and simultaneous implementation it into a target microprocessor. The RCPP is stand-alone system containing software tools and electronic hardware in order to provide all development steps from system identification, model-based control design and code generation up to hardware implementation. The system can be used for development of a torque, speed or position controller for low power electromechanical actuators especially in the area of automotive application. The hardware of the platform is based on a 16-bit microcontroller and includes essential power semiconductor switches, sensors and communication interfaces. The presented RCPP system supports Real-Time-Work interface of MATLAB/Simulink and Calibration Protocol for CAN-Bus communication

Advanced flight control system study

The architecture, requirements, and system elements of an ultrareliable, advanced flight control system are described. The basic criteria are functional reliability of 10 to the minus 10 power/hour of flight and only 6 month scheduled maintenance. A distributed system architecture is described, including a multiplexed communication system, reliable bus controller, the use of skewed sensor arrays, and actuator interfaces. Test bed and flight evaluation program are proposed

Adaptive and Robust Braking-Traction Control Systems

The designs of commercial Anti-Lock Braking Systems often rely on assumptions of a torsionally rigid tire-wheel system and heavily rely on hub-mounted wheel speed sensors to manage tire-road slip conditions. However, advancements in high-bandwidth braking systems, in-wheel motors, variations in tire/wheel designs, and loss of inflation pressure, have produced scenarios where the tire\u27s torsional dynamics could be easily excited by the braking system actuator. In these scenarios, the slip conditions for the tire-belt/ring will be dynamically different from what can be inferred from the wheel speed sensors. This dissertation investigates the interaction of tire torsional dynamics with ABS & traction controllers and offers new control designs that incorporate schemes for identifying and accommodating these dynamics. To this end, suitable braking system and tire torsional dynamics simulation models as well as experimental test rigs were developed. It is found that, indeed, rigid-wheel based controllers give degraded performance when coupled with low torsional stiffness tires. A closed-loop observer/nonlinear controller structure is proposed that adapts to unknown tire sidewall and tread parameters during braking events. It also provides estimates of difficult to measure state variables such as belt/ring speed. The controller includes a novel virtual damper emulation that can be used to tune the system response. An adaptive sliding-mode controller is also introduced that combines robust stability characteristics with tire/tread parameter and state estimation. The sliding mode controller is shown to be very effective at tracking its estimated target, at the expense of reducing the tire parameter adaptation performance. Finally, a modular robust state observer is developed that allows for robust estimation of the system states in the presence of uncertainties and external disturbances without the need for sidewall parameter adaptation

Qualitative validation approach using digital model for the health management of electromechanical actuators

An efficient and all-inclusive health management encompassing condition-based maintenance (CBM) environment plays a pivotal role in enhancing the useful life of mission-critical systems. Leveraging high fidelity digital modelling and simulation, scalable to digital twin (DT) representation, quadruples their performance prediction and health management regime. The work presented in this paper does exactly the same for an electric braking system (EBS) of a more-electric aircraft (MEA) by developing a highly representative digital model of its electro-mechanical actuator (EMA) and integrating it with the digital model of anti-skid braking system (ABS). We have shown how, when supported with more-realistic simulation and the application of a qualitative validation approach, various fault modes (such as open circuit, circuit intermittence, and jamming) are implemented in an EMA digital model, followed by their impact assessment. Substantial performance degradation of an electric braking system is observed along with associated hazards as different fault mode scenarios are introduced into the model. With the subsequent qualitative validation of an EMA digital model, a complete performance as well as reliability profile of an EMA can be built to enable its wider deployment and safe integration with a larger number of aircraft systems to achieve environmentally friendly objectives of the aircraft industry. Most significantly, the qualitative validation provides an efficient method of identifying various fault modes in an EMA through rapid monitoring of associated sensor signals and their comparative analysis. It is envisaged that when applied as an add-on in digital twin environment, it would help enhance its CBM capability and improve the overall health management regime of electric braking systems in more-electric aircraf

Global Chassis Control System Using Suspension, Steering, and Braking Subsystems

A novel Global Chassis Control (GCC) system based on a multilayer architecture with three levels: top: decision layer, middle: control layer, and bottom: system layer is presented. The main contribution of this work is the development of a data-based classification and coordination algorithm, into a single control problem. Based on a clustering technique, the decision layer classifies the current driving condition. Afterwards, heuristic rules are used to coordinate the performance of the considered vehicle subsystems (suspension, steering, and braking) using local controllers hosted in the control layer. The control allocation system uses fuzzy logic controllers. The performance of the proposed GCC system was evaluated under different standard tests. Simulation results illustrate the effectiveness of the proposed system compared to an uncontrolled vehicle and a vehicle with a noncoordinated control. The proposed system decreases by 14% the braking distance in the hard braking test with respect to the uncontrolled vehicle, the roll and yaw movements are reduced by 10% and 12%, respectively, in the Double Line Change test, and the oscillations caused by load transfer are reduced by 7% in a cornering situation

Advanced Motor Control for Improving the Trajectory Tracking Accuracy of a Low-Cost Mobile Robot

This research was funded by the Grant PID2019-111278RB-C21 funded by MCIN/AEI/ 10.13039/501100011033 and “ERDF A way of making Europe”.Peer reviewedPublisher PD

A genetic-based prognostic method for aerospace electromechanical actuators

Prior awareness of impending failures of primary flight command electromechanical actuators (EMAs) utilizing prognostic algorithms can be extremely useful. Indeed, early detection of the degradation pattern might signal the need to replace the servomechanism before the failure manifests itself. Furthermore, such algorithms frequently use a model-based approach based on a direct comparison of the real (High Fidelity) and monitor (Low Fidelity) systems to discover fault characteristics via optimization methods. The monitor model enables the gathering of accurate and exact data while requiring a minimal amount of processing. This work describes a novel simplified monitor model that accurately reproduces the dynamic response of a typical aerospace EMA. The task of fault detection and identification is carried out by comparing the output signal of the reference system (the high fidelity model) with that acquired from the monitor model. The Genetic Algorithm is then used to optimize the matching between the two signals by iteratively modifying the fault parameters, getting the global minimum of a quadratic error function. Once this is found, the optimization parameters are connected with the assumed progressive failures to assess the system's health. The high-fidelity reference model examined in this study is previously conceptualized, developed, implemented in MATLAB-Simulink and finally experimentally confirmed