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| A | B | C | D | E | F |
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| [104] | PSO has been used to overcome the nonlinearity in the MPC | Kinematic parameters, dynamic parameters | Simulation | Optimized MPC, reduced the computation time | N/A |
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| [106] | Proposed an optimal guidance scheme (improved PSO) based on MPC in the design of the kinematics controller | Kinematics parameter, curvature of the path, rotation transformation | Simulation | Helped to avoid obstacles meeting curvature constraints | This approach can also be extended to path planning and following other unmanned vehicles |
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| [107] | Proposed a PSO-based nonlinear-MPC (NMPC) technique to calculate the yaw moment of the vehicle | Kinematic parameters, dynamic parameters | Simualtion | Optimized the steering performance of a vehicle | The effectiveness of the proposed method is only verified under the single-lane manoeuvre |
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| [108] | NMPC with QPSO has been proposed for the dynamic steering control of the vehicle | Kinematic parameters, dynamic parameters, wheel steering angle. | MATLAB | The concurrent design greatly improved the speed of optimization | Deviation has been noticed in the reference trajectory |
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| [109] | Developed a model-free PID controller with derivative filter (PDF) parameter tuning method by using PSO | Dynamic parameter | Simulation | Yielded a good transient response with no steady-state error | The higher the number of particles, the longer algorithm takes to complete its iteration but the result sometimes is not even better than the previous run |
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| [110] | Discussed how the PID controller is tuned to control angular and linear motion | Kinematic parameters, dynamic parameters, vehicle mass, radius wheelbase | MATLAB | The controller optimally tuned the angular motion of the car by selecting the most appropriate values of the PID | The control algorithm could not search more than one path and chose the one among them in case of obstacles in the road |
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| [111] | This paper compares five kinds of tuning methods of a parameter for the PID controller, such as FA, PSO, ACO, BA, and ICA | Kinematic parameters, dynamic parameters, vehicle mass, radius wheelbase | Simulation | Provided correct results as compared to the PID controller | This research needs to be extended to check its performance on real vehicle conditions |
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| [113] | Proposed an optimized design of FOPID using PSO and GA | Kinematic and dynamic parameters | MATLAB | Improved the steering control of the AV | Other methods to tune the parameters of a FOPID controller which could be tested on an actual system |
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| [115] | Proposed a supertwisting algorithm to tune the control parameters of the higher-order SMC using PSO | Steering wheel angle, kinematic and dynamic parameters, cornering stiffness | MATLAB | The dynamic variables obtained by SMC with PSO are better than the results obtained by SMC | Only theoretical study is carried out |
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| [82] | A novel approach for four-wheel steer and drive vehicle has been presented which helps to track a path using SMC | Kinematic parameters, initial heading error θ | Simulation | The proposed method showed the accurate path followed and accurate reference velocity and acceleration profile followed under varying terrain conditions | Experiments will be carried out to verify the validity of the proposed method |
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| [116] | Devised a path tracking technique for automatic steering control of a vehicle based on Stanley controller | Kinematics and dynamic parameters | Simulation | In general, both modified controllers performed well in guiding the vehicle to follow the intended path | The control parameters still need to be optimized for better steering control of the vehicle |
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| [117] | QPSO is employed to optimize the track control. A steering control model has been devised by using adaptive parallel series | Dynamic parameters, steer angle | N/A | The tracking control is effectively achieved in the semiautonomous driver assistance system | Needs to be applied to the real system, such as senior vehicles and autonomous vehicles |
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