Adaptive Cruise Control System: Comparing Gain-Scheduling PI and LQ Controllers

Shakouri, Payman; Ordys, Andrzej; Laila, Dina Shona; Askari, Mohamad R.

doi:10.3182/20110828-6-it-1002.02250

Cited by 86 publications

(40 citation statements)

References 5 publications

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“…velocity tracking (CC) and distance tracking [3], [6], [7]. The switching rules for transition between CC and ACC modes are illustrated in Table IV.…”

Section: A P Id Parametersmentioning

confidence: 99%

“…The teaching methodology, overall teaching plan (including the formal lectures on control design for distance tracking based on the classical controllers [3], hands-on exercises, and associated assessment task) are presented in Section II. The rest of the paper provides all of the information required by instructors for course delivery, including the solution of the assessment, as follows.…”

Section: Introductionmentioning

confidence: 99%

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Teaching control using NI Starter Kit Robot

Shakouri

Collier

Ordys

2012

Proceedings of 2012 UKACC International Conference on Control

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Teaching engineering concepts using demonstrations and experiments on real hardware is always engaging and well received by students. This paper provides reference materials (both theoretical and test results), to be used in Control teaching and assessment using a laboratory experiment, with a real time single board computer based robotic vehicle (National Instruments Robotics Starter Kit). This robotic vehicle is programmed using a graphical programming environment. The Adaptive Cruise Control (ACC) algorithm based on Proportional-Integral (PI) and Proportional -Integral -Derivative (PID) Control are deployed on a field programmable gate array (FPGA), included in the robot's architecture. The robot model (based on a given second order transfer function) is controlled using the same method. The results obtained are compared for the simulation model and a real robot.The performance comparison demonstrates a good correlation between theory and implementation, whilst demonstrating problems and discrepancies introduced by a real system.

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“…velocity tracking (CC) and distance tracking [3], [6], [7]. The switching rules for transition between CC and ACC modes are illustrated in Table IV.…”

Section: A P Id Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Teaching control using NI Starter Kit Robot

Shakouri

Collier

Ordys

2012

Proceedings of 2012 UKACC International Conference on Control

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“…In Goodrich, M.A, a human-centered approach to determine throttle and brake actuation was proposed [2], while in [3], [4], and [5] a model-based lower-level controller is used whose control inputs are estimated using vehicle parameters and inverse dynamics. In [6], the design of a gain-scheduling linear quadratic controller for throttle and brake actuation has been demonstrated using a linearized vehicle model. Most of these methods rely on an accurate mathematical model of the vehicle (plant) to determine which, is a difficult task.…”

Section: Introductionmentioning

confidence: 99%

A novel approach to the design of controllers in an automotive cruise-control system

Vedam

Díaz-Rodríguez

Bhattacharyya

2014

IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society

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A complete stabilizing PID set is developed without the need for an identified analytical model, for an automotive cruise-control system from its frequency response. The resulting set serves as a framework and is used to determine the PID gains satisfying certain performance indices. These performance measures are derived from the need for efficient tracking and disturbance rejection. This ensures that the controller is tuned with the most appropriate PID gains, yielding the desired closedloop response. Also, this serves as a viable alternative to the iterative method of estimating stabilizing PID gains.

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“…The switching rules ( [3], [5]) for transition between CC and ACC modes are illustrated in Table 1.. If the ultrasonic sensor of the follower detects a slower moving robot in front, the controller adjusts the velocity to maintain the clearance inter-distance (desired distance).…”

Section: Control Designmentioning

confidence: 99%

“…A comprehensive study on the ACC was carried out by [2]. Several model-based control approaches and architectures have been suggested and developed for designing ACC systems from the classical to the nonlinear advanced control methods, such as PID control and linear quadratic control (LQC) taking the gain scheduling approach [3][4], model predictive control (MPC) and nonlinear MPC (NMPC) [5][6], and the sliding mode controller [7] among others. The practical implementation of the ACC system using the three control methodologies, MPC, fuzzy PID, and conventional PID control, in the application to the real-time single board computer based robotic vehicle is presented in this paper.…”

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confidence: 99%

Robotic Implementation of the Adaptive Cruise Control-Comparison of Three Control Methods

2014

Self Cite

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Abstract. This paper explores the practical implementation of the Adaptive Cruise Control (ACC) system on a real-time single board computer based robotic vehicle (National Instruments Robotics Starter Kit). The ACC algorithm based on three control methodologies, the fuzzy PID control, model predictive control (MPC) and conventional PID control, is deployed on a field programmable gate array (FPGA), included in the robot's architecture. The results are compared both in the simulation and using the real robot. The comparison of the performance demonstrates a good correlation between theory and real implementation, whilst highlighting problems introduced by a real system. IntroductionAdaptive cruise control (ACC) system, cruise control (CC) system and emergency stop are the more common longitudinal applications, which have been studied in the field of the robotics and intelligent transportation system (ITS) [1]. The ACC system is an extension of the cruise control system, which not only controls the velocity of the vehicle but also is it capable of controlling the distance between the leader and follower vehicles to retain a safe distance. A comprehensive study on the ACC was carried out by [2]. Several model-based control approaches and architectures have been suggested and developed for designing ACC systems from the classical to the nonlinear advanced control methods, such as PID control and linear quadratic control (LQC) taking the gain scheduling approach [3][4], model predictive control (MPC) and nonlinear MPC (NMPC) [5][6], and the sliding mode controller [7] among others. The practical implementation of the ACC system using the three control methodologies, MPC, fuzzy PID, and conventional PID control, in the application to the real-time single board computer based robotic vehicle is presented in this paper. Furthermore, the results of those controllers are compared both in the simulation and using the real robot. The paper is organized as follows: Section 2 describes the hardware and the associated system transfer function. Section 3 describes the ACC

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Adaptive Cruise Control System: Comparing Gain-Scheduling PI and LQ Controllers

Cited by 86 publications

References 5 publications

Teaching control using NI Starter Kit Robot

Teaching control using NI Starter Kit Robot

A novel approach to the design of controllers in an automotive cruise-control system

Robotic Implementation of the Adaptive Cruise Control-Comparison of Three Control Methods

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