Swarm-Intelligence Tuned Current Reduction for Power-Assisted Steering Control in Electric Vehicles

Hanifah, Rabiatuladawiah Abu; Toha, Siti Fauziah; Ahmad, Salmiah; Hassan, Mohd Khair

doi:10.1109/tie.2017.2784344

Cited by 47 publications

(28 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…because the controller parameters c 0 , c 1 and c 2 are given as (10)- (12). Since the characteristic polynomial family P is the denominator of the transfer function, it is given as…”

Section: Characteristic Polynomial Family Now Wementioning

confidence: 99%

See 1 more Smart Citation

Synthesis of robust PID Control systems using stability feeler and partial model matching

Matsuda

Nakamura

2019

IEEJ Transactions Elec Engng

View full text Add to dashboard Cite

In this paper, we propose a new method for the synthesis of robust proportional, integral, and derivative (PID) control systems. The proposed method is based on the idea of partial model matching. The stability feeler, a tool for robust stability analysis, is used to stabilize closed-loop systems with uncertainties. An advantage of the proposed method is that it guarantees robust stability of control systems. To clarify the effectiveness of the proposed method, two types of simulations are given. One is the case where the nominal plant is not stable. The other is the case where the plant is not robustly stable although the nominal plant is stable. The simulation results when the nominal plant is not stable show that the controller derived by the proposed method robustly stabilizes the closed-loop system, whereas that derived by conventional partial model matching method cannot stabilize it. Moreover, when the plant is not robustly stable, it can be seen that the controller by the proposed method can robustly stabilize the system. Therefore, it is shown that the proposed method enables one to derive PID controllers robustly stabilizing closed-loop systems.

show abstract

“…because the controller parameters c 0 , c 1 and c 2 are given as (10)- (12). Since the characteristic polynomial family P is the denominator of the transfer function, it is given as…”

Section: Characteristic Polynomial Family Now Wementioning

confidence: 99%

“…In Ref. [12], a PID controller for an electric vehicle is derived by particle swarm optimization (PSO) and ant colony optimization (ACO). PSO was also used for tuning a PID controller for a transportation system [13].…”

Section: Introductionmentioning

confidence: 99%

Synthesis of robust PID Control systems using stability feeler and partial model matching

Matsuda

Nakamura

2019

IEEJ Transactions Elec Engng

View full text Add to dashboard Cite

show abstract

“…In this scenario, metaheuristics such as genetic algorithms (GA) and particle swarm optimization (PSO) can be useful, as indicated in [22]. It is important to mention that GA and PSO algorithms have already been used in the design of PIDs in [23]- [25]. For instance, in [23] a PID control based on a multiobjective GA is proposed for a linear brushless DC motor, taking into account uncertainties, with an objective function based on the rise time, overshoot and steady-state error.…”

Section: Introductionmentioning

confidence: 99%

“…In [24], a PSO is used to determine the gains of an optimal PID for an automatic voltage regulator system, and a comparison with a GA method is presented in this case. In [25], a PSO is used to find optimum values of the gains of a PID controller in order to reduce the current to the powerassisted steering in electric vehicles, having the objective of minimizing a mean square error function. As remarked in [22], the majority of the publication with metaheuristics in power electronics is on power quality and circuitry optimization.…”

Section: Introductionmentioning

confidence: 99%

Robust PID Controllers Optimized by PSO Algorithm for Power Converters

Borin

Mattos

Osório

et al. 2019

2019 IEEE 15th Brazilian Power Electronics Conference and 5th IEEE Southern Power Electronics Conference (COBEP/SPEC)

View full text Add to dashboard Cite

This paper provides an automated design to provide robust PIDs with fixed control gains, suitable to be applied in power converters whose parameters belong to real intervals. Differently from conventional PIDs which use only a nominal model to obtain the fixed control gains and, a posteriori, verify robustness, the proposed approach ensures, a priori (i.e. during the design stage), robust performance for a set of plant parameters. To illustratethe proposed procedure, two conventional PID controllers are given, to achieve phase margin and crossover frequency for a nominal model of a buck converter. An objective function based on frequency domain specifications is proposed. A particle swarm optimization algorithm is then used to find PIDs, in a large search space that include stable and unstable controllers, allowing to optimize this function for all cases of combinations of plant parameters. A case study for the buck converter illustrates the improvements of performance with the proposed method when compared to the conventional PID controllers. Additionally, the design is used in a more challenging application, for a buck-boost converter suitable for small satellites application, becoming a simple alternative for benchmarks for robust control of power converters.

show abstract

“…The assist effort of EPS can vary with vehicle speed, which is conducive to improving handling stability. In addition, the motor in EPS provide steering assist effort directly, thus EPS hardly consumes electric energy under no-steering conditions, which is more energy saving [3,4]. Nevertheless, EPS is not suitable for heavy-duty commercial vehicles due to a large steering resistance torque and the power limitation of existing power supply systems in heavy-duty commercial vehicles, especially under the condition of pivot or low-speed steering [5].…”

Section: Introductionmentioning

confidence: 99%

Study on Low-Speed Steering Resistance Torque of Vehicles Considering Friction between Tire and Pavement

et al. 2019

View full text Add to dashboard Cite

Electric power steering (EPS) systems under existing vehicle power systems cannot provide enough power for heavy-duty commercial vehicles under pivot or low-speed steering conditions. To solve this problem, the paper proposes an EPS system that is based on the hybrid power system constituted by the vehicle power system and the supercapacitor in parallel. In order to provide a theoretical basis for the intervention and withdrawal mechanisms of a super-capacitor in the new EPS, the law of steering resistance torque at a low or extremely low vehicle speed should be explored. Firstly, the finite element model of tire/pavement was established to conduct the simulation and calculation of the low-speed steering friction force between the tire and pavement, and to obtain the fitting expression of the equivalent steering friction coefficient with the running speed of the tire. Secondly, the expression of the steering friction torque was deduced based on the calculus theory and mathematical model of the low-speed steering resistance torque, including the steering friction torque and aligning torques, established to conduct the simulation of the equivalent resistance torque applied on a steering column under low-speed condition. Subsequently, the real vehicle experiments were carried out and comparisons of the experimental results and simulation results was performed. The consistency indicated that the model of low-speed steering resistance torque had a high accuracy. Finally, the law of low-speed steering resistance torque with a vehicle speed and steering wheel angle were analyzed according to the 3D surface plot drawn from the simulation results.

show abstract

Swarm-Intelligence Tuned Current Reduction for Power-Assisted Steering Control in Electric Vehicles

Cited by 47 publications

References 20 publications

Synthesis of robust PID Control systems using stability feeler and partial model matching

Synthesis of robust PID Control systems using stability feeler and partial model matching

Robust PID Controllers Optimized by PSO Algorithm for Power Converters

Study on Low-Speed Steering Resistance Torque of Vehicles Considering Friction between Tire and Pavement

Contact Info

Product

Resources

About