Gear Shift Coordinated Control Strategy Based on Motor Rotary Velocity Regulation for a Novel Hybrid Electric Vehicle

This paper proposes a novel hybrid power system to improve the shift quality of a hybrid electric vehicle (HEV). After selecting a typical shift scheme, the study focused on the motor rotary velocity control algorithm and coordinated control strategy for the motor and clutch. The effects of various control algorithms on different target rotary velocities were analyzed, and a proportional-integral-derivative (PID)–bang-bang–fuzzy compound intelligent algorithm for a motor rotary velocity control system was investigated. In addition, to address the problems of the long synchronizing time required for the rotary velocity and large sliding friction work, which affect the shift quality during the process of engaging the clutch, a coordinated control strategy for the motor rotary velocity and clutch oil pressure was investigated. The research results showed that, compared with a gear shift coordinated control strategy based on a PID control algorithm, the strategy based on the PID–bang-bang–fuzzy compound intelligent control algorithm proposed here reduced the shift time and clutch slipping friction work by 35.7% and 19.2%, respectively.

ROS-based Toolbox for Motor Parameter Identification of Robotic Manipulators

For many applications, a precise knowledge of the model of the robot is necessary for accurate and stable control. However, it is not always feasible or desirable to perform from scratch an in-depth study of the robot model, especially if it is not an element of concern for the respective application. In this article we present a methodology for identifying motor parameters of a robotic manipulator. We discuss the mathematical model and introduce an extensible toolbox with velocity-control based methodology for a fast identification of individual motor parameters. The results show that we can identify individual parameters even for joints that are commercialised as of the same type.

The Control Reversing Algorithm for Autonomous Vehicles with PSD-Controlled Trailers

Driving a vehicle with a passive trailer has been the subject of numerous studies. Current control strategies are mostly used by differential geometry, linear algebra, fuzzy regulators, and artificial neural networks. The objective of this study is to design an algorithm for autonomous control of the tractor-trailer system reversing based on an algorithm using a PSD controller and to verify it on a simulated mathematical model. All parameters listed in the models and experiments are performed based on the existing tractor-trailer system. Dynamic models of steering and velocity control were identified and incorporated into the simulation. Result includes a stable operation of the steering without oscillating. The proposed algorithm can be implemented in microcontrollers without the need for high computing power.

Speed Control with Indirect Field Orientation for Low Power Three-Phase Induction Machine with Squirrel Cage Rotor

Induction machines are widely used in the industry due to their many advantages compared to other industrial machines. This article presents the study and implementation of speed control applied to a Three-phase Induction Machine (MIT) of the squirrel cage type. The induction motor was modeled using the rotor flux in the synchronous reference to design Proportional-Integral (PI) type controllers for the current and velocity control loops. It is the objective of the article also to present in detail the development of converter hardware that comprises the stages of power, acquisition, and conditioning of engine signals. The system was simulated using computational tools and validated using a prototype designed, constructed, and commissioned.

Output-Based Tracking Control for a Class of Car-like Mobile Robot Subject to Slipping and Skidding Using Event-Triggered Mechanism

This paper presents an output-based tracking controller for a class of car-like mobile robot (CLMR) subject to slipping and skidding. The slipping and skidding are regarded as external disturbances, and an event-triggered extended state observer (ET-ESO) is utilized to recover the velocities as well as to estimate the uncertainties and disturbances. The constrained longitudinal velocity is established, conforming to the traffic flow theory on the kinematic level. The velocity control law and heading angle control law are developed on the dynamic level, respectively. The input to state stability (ISS) of the closed-loop system is analyzed via cascade theory. Simulation results are given to demonstrate the effectiveness of the proposed tracking controller for CLMR subject to slipping and skidding.

Closed-loop control of a prosthetic finger via evoked proprioceptive information

Objective. Proprioceptive information plays an important role for recognizing and coordinating our limb’s static and dynamic states relative to our body or the environment. In this study, we determined how artificially evoked proprioceptive feedback affected the continuous control of a prosthetic finger. Approach. We elicited proprioceptive information regarding the joint static position and dynamic movement of a prosthetic finger via a vibrotactor array placed around the subject’s upper arm. Myoelectric signals of the finger flexor and extensor muscles were used to control the prosthesis, with or without the evoked proprioceptive feedback. Two control modes were evaluated: the myoelectric signal amplitudes were continuously mapped to either the position or the velocity of the prosthetic joint. Main Results. Our results showed that the evoked proprioceptive information improved the control accuracy of the joint angle, with comparable performance in the position- and velocity-control conditions. However, greater angle variability was prominent during position-control than velocity-control. Without the proprioceptive feedback, the position-control tended to show a smaller angle error than the velocity-control condition. Significance. Our findings suggest that closed-loop control of a prosthetic device can potentially be achieved using non-invasive evoked proprioceptive feedback delivered to intact participants. Moreover, the evoked sensory information was integrated during myoelectric control effectively for both control strategies. The outcomes can facilitate our understanding of the sensorimotor integration process during human-machine interactions, which can potentially promote fine control of prosthetic hands.