Rapid Control Prototyping Platform Research Articles

Experimental study on the double-skyhook controls of semi-active suspension with variable inertance and damping

As a conventional control approach, the skyhook damping control algorithm can respond to changes in road circumstances but not to those in load circumstances. The skyhook inertance control algorithm, a newly developed control approach, may adapt to changes in load circumstances rather than in road circumstances. The recent introduction of double-skyhook control algorithms has allowed vehicle suspension systems to accomplish both load and road adaptation. This paper presents an experimental investigation contrasting the performance of the double-skyhook configuration to that of the traditional skyhook damper configuration and the skyhook inerter configuration. By integrating the double-skyhook control strategy with semi-active devices with variable inertance and damping, the paper proposes two strategies for coordinating skyhook inertance and skyhook damping control. A controller using the double-skyhook control strategy is designed to employ the Development to Production rapid control prototyping platform. The controller mode is adjusted using MotoTune software to implement control methods. Three tests were conducted under various road conditions, load conditions, and impact conditions for semi-active suspension. Test results indicate that the double-skyhook configuration considerably enhances driving comfort compared to the single-skyhook configuration. Moreover, the greater the deterioration of road conditions and the decrease in load, the more pronounced the enhancement.

A flexible power electronic converter system with rapid control prototyping for research and teaching

A flexible power electronic converter embedding a rapid control prototyping platform suitable to be applied in research test setups and teaching laboratories is proposed and described in this paper. The electronic system is composed of three subsystems, namely, i) three half-bridge power boards, ii) a dc-link capacitor bank with a half-bridge power module for active dc-link control, iii) an interfacing board, called motherboard, to couple the power modules with a control unit, iv) a digital control unit with rapid control prototyping functionalities for controlling power electronic circuits. Power modules integrate sensors with related conditioning circuits, driving circuits for power switches, and protection circuits. Conversion circuits exploit GaN electronic switches for optimal performance. The architecture and implementation of the system are described in detail in this manuscript. Main applications are in the implementation of conversion circuits for supplying arbitrary ac or dc voltages or currents, testing of new control algorithms for power electronic converters, testing of systems of electronic converters in, for example, smart nanogrids or renewable energy applications, training of undergraduate and graduate students.

Accurate and robust state estimation for bicycles

Accurate estimates of the dynamical states of bicycles are crucial for many advanced rider assistance systems. However, systems that can provide an exact estimate of the system states (especially the system orientations) are often expensive and therefore cannot be used in mass production. In this work, a method is presented that estimates the dynamical states of a bicycle using measurements, provided by a cost-effective sensor configuration. The proposed method is based on a constrained extended Kalman filter and uses accelerometer, gyroscope and wheel speed measurements to estimate the vehicle dynamics. Since no bicycle model is required, the filter can be easily adapted for the use in a wide range of bicycles and other single-track vehicles like motorcycles. The filter is implemented on a rapid control prototyping platform and the results are compared to measurements of a reference sensor unit. Here, special attention is put on the roll angle and the velocity estimates, where the filter produces excellent results. In addition, the filter robustness to sensor errors and uncertain system parameters is evaluated.

Neural control of an induction motor with regenerative braking as electric vehicle architecture

This paper presents the synthesis of an induction motor neural controller and a regenerative braking controller for an electric vehicle architecture, based on two energy system, a Main Energy System (MES) and an Auxiliary Energy System (AES). Such controllers are based on system identification, trajectory tracking and state estimation. System identification uses a Recurrent High Order Neural Network (RHONN), trained with an Extended Kalman Filter (EKF). RHONN obtains an accurate motor model which is robust in presence of external disturbances and parameter variations. To force the motor to track a desired torque trajectory and to reject undesired disturbances, an inverse optimal controller based on the identified neural model is proposed. Therefore, the proposed scheme does not need a-priori knowledge of motor parameters. For state estimation a super-twisting observer is implemented to estimate the rotor magnetic fluxes. The regenerative braking controller addresses the issue when the battery is not capable to accept the generated energy due to braking; Therefore, an AES based on a super capacitor and a buck–boost converter is a solution to recover the braking energy and give power to the motor during acceleration. The regenerative braking controller is based on a PI control to regulate voltage and current of the super capacitor. Simulation and experimental results illustrate the performance of the proposed controllers which are implemented using a rapid control prototyping platform integrated by a dSPACE board. Experimental tests are carried out for a topology with and without AES to illustrate the improvement of the proposed EV architecture.

Nonlinear MPC-based slip control for electric vehicles with vehicle safety constraints

This paper presents a new slip control system for electric vehicles (EVs) equipped with four in-wheel motors, based on nonlinear model predictive control (nonlinear MPC) scheme. In order to ensure vehicle safety, wheel slip stable zone is considered as time-domain constraints of the nonlinear MPC. Besides, the motor output torque is limited by the motor maximum torque, which varies with motor angular velocity and battery voltage, so the motor maximum output torque limitation is considered as system time-varying constraints. The control objectives include: vehicle safety, good longitudinal acceleration and braking performance, preservation of driver comfort and lower power consumption. This paper utilizes nonlinear MPC to solve this complex optimization control problem subject to the constraints, and the vehicle safety objective is achieved by wheel slip stable zone constraints, the other objectives are realized by adding additional cost functions. In addition, a penalty on the slack variables is also added to ensure that the state constraints (wheel slip) do not cause infeasible problems. The effectiveness of the proposed controller is verified in the off-line co-simulation environment of AMESim and Simulink, and a rapid control prototyping platform based on Field programmable gate array (FPGA) and dSPACE is completed to evaluate the real time functionality and computational performance of the nonlinear MPC controller.

Rapid Control Prototyping Design of DSP-Based Motion Controller

This paper presents a Rapid Control Prototyping (RCP) development platform based on Matlab/Simulink, Real-Time Workshop and Embedded Target for C2000 and DSP development board. It also designs TMS320F2812 DSP-based motion controller under the proposed RCP. The controller using saturated integral PID algorithm produces PWM signal to control DC motor. Experimental results show that the designed controller can control motor accurately. Engineers can complete all design tasks such as modeling, automatic code generation, and download, running and parameters adjustment on this RCP platform when developing DSP application system. Thus the proposed RCP can shorten the DSP development cycle and improve the portability and modularity of program.

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.

Design of a networked traction control system using a real-time operating system

In this paper, a design procedure is proposed for networked control systems (NCSs) using an embedded real-time operating system (RTOS). In a conventional design of NCSs, well-designed control algorithms do not result in the intended control performance after an implementation because of time delays, such as network-induced delays and controller computation delays. The proposed design procedure shows how to minimize the degradation of the control performance caused by the time delays. A performance index (PI) is derived from the difference between the performance of a simulated system and the performance of an implemented system with time delays. By using the proposed PI, optimized periods and priorities of tasks and communication messages of NCSs were determined. The design procedure was verified by designing a networked traction control system (TCS) using a real-time operating system for automotive electronics, OSEK-OS. The designed TCS was realized and tested by using a rapid control prototyping platform and a hardware-in-the-loop simulation environment.

Target-identical rapid control prototyping platform for model-based engine control

Rapid control prototyping (RCP) is one of the most important technologies for speeding up the development process of the electronic control unit (ECU) used in the automotive control system. However, one big drawback of the conventional RCP platform is the transfer from RCP to target ECU implementation. In this study, a new RCP platform is proposed that provides a consistent environment for both the RCP development stage and the target ECU implementation stage. In order to make the rapid prototyping controller as similar to a production ECU as possible, the prototyping system follows the strictly layered architecture of the production ECU and separates the automatically generated code of software from the hand code. Finally, the feasibility of the developed target-identical RCP platform is evaluated through an air-to-fuel ratio (AFR) control application.