The Experts below are selected from a list of 6297 Experts worldwide ranked by ideXlab platform
Daniel Lechner - One of the best experts on this subject based on the ideXlab platform.
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embedded unknown input sliding mode observer to estimate the vehicle roll and road Bank Angles experimental evaluation
Intelligent Autonomous Vehicles, 2010Co-Authors: Lghani Menhour, Daniel LechnerAbstract:Abstract Driving safely can be achieved by better understanding critical situations. This can be achieved by a good knowledge of road attributes and vehicle dynamic parameters. Road Bank Angle has an important role on the vehicle lateral dynamic; unfortunately, this parameter is not measured by low cost embedded sensor. This paper presents a new estimation process which was designed to estimate the lateral wind force, the road Bank and vehicle roll Angles using an unknown input sliding mode observer and a linear vehicle model with variant parameters. The vehicle model used here is relatively simple, but it offers a sufficient approximation of the lateral dynamics of the vehicle in normal driving situations. This observer uses the sensor measurements such as the steering Angle, the vehicle sideslip Angle, the roll rate and the yaw rate. Experimental evaluation proves that the estimation scheme is giving appropriate estimation of the vehicle roll and road Bank Angles. These tests are carried out using the data acquired on the laboratory vehicle Peugeot 307 developed by INRETS-MA.
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embedded unknown input sliding mode observer to estimate the vehicle roll and road Bank Angles experimental evaluation
Intelligent Autonomous Vehicles, 2010Co-Authors: Lghani Menhour, Daniel LechnerAbstract:Abstract Driving safely can be achieved by better understanding critical situations. This can be achieved by a good knowledge of road attributes and vehicle dynamic parameters. Road Bank Angle has an important role on the vehicle lateral dynamic; unfortunately, this parameter is not measured by low cost embedded sensor. This paper presents a new estimation process which was designed to estimate the lateral wind force, the road Bank and vehicle roll Angles using an unknown input sliding mode observer and a linear vehicle model with variant parameters. The vehicle model used here is relatively simple, but it offers a sufficient approximation of the lateral dynamics of the vehicle in normal driving situations. This observer uses the sensor measurements such as the steering Angle, the vehicle sideslip Angle, the roll rate and the yaw rate. Experimental evaluation proves that the estimation scheme is giving appropriate estimation of the vehicle roll and road Bank Angles. These tests are carried out using the data acquired on the laboratory vehicle Peugeot 307 developed by INRETS-MA.
Lghani Menhour - One of the best experts on this subject based on the ideXlab platform.
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embedded unknown input sliding mode observer to estimate the vehicle roll and road Bank Angles experimental evaluation
Intelligent Autonomous Vehicles, 2010Co-Authors: Lghani Menhour, Daniel LechnerAbstract:Abstract Driving safely can be achieved by better understanding critical situations. This can be achieved by a good knowledge of road attributes and vehicle dynamic parameters. Road Bank Angle has an important role on the vehicle lateral dynamic; unfortunately, this parameter is not measured by low cost embedded sensor. This paper presents a new estimation process which was designed to estimate the lateral wind force, the road Bank and vehicle roll Angles using an unknown input sliding mode observer and a linear vehicle model with variant parameters. The vehicle model used here is relatively simple, but it offers a sufficient approximation of the lateral dynamics of the vehicle in normal driving situations. This observer uses the sensor measurements such as the steering Angle, the vehicle sideslip Angle, the roll rate and the yaw rate. Experimental evaluation proves that the estimation scheme is giving appropriate estimation of the vehicle roll and road Bank Angles. These tests are carried out using the data acquired on the laboratory vehicle Peugeot 307 developed by INRETS-MA.
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embedded unknown input sliding mode observer to estimate the vehicle roll and road Bank Angles experimental evaluation
Intelligent Autonomous Vehicles, 2010Co-Authors: Lghani Menhour, Daniel LechnerAbstract:Abstract Driving safely can be achieved by better understanding critical situations. This can be achieved by a good knowledge of road attributes and vehicle dynamic parameters. Road Bank Angle has an important role on the vehicle lateral dynamic; unfortunately, this parameter is not measured by low cost embedded sensor. This paper presents a new estimation process which was designed to estimate the lateral wind force, the road Bank and vehicle roll Angles using an unknown input sliding mode observer and a linear vehicle model with variant parameters. The vehicle model used here is relatively simple, but it offers a sufficient approximation of the lateral dynamics of the vehicle in normal driving situations. This observer uses the sensor measurements such as the steering Angle, the vehicle sideslip Angle, the roll rate and the yaw rate. Experimental evaluation proves that the estimation scheme is giving appropriate estimation of the vehicle roll and road Bank Angles. These tests are carried out using the data acquired on the laboratory vehicle Peugeot 307 developed by INRETS-MA.
Ashok Joshi - One of the best experts on this subject based on the ideXlab platform.
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trajectory design of re entry vehicles using combined pigeon inspired optimization and orthogonal collocation method
IFAC-PapersOnLine, 2018Co-Authors: Gangireddy Sushnigdha, Ashok JoshiAbstract:Abstract This paper presents an orthogonal collocation based entry trajectory solution strategy using Pigeon Inspired Optimization (PIO). PIO is a swarm algorithm based on the homing behavior of pigeons. For the unpowered re-entry vehicle, Bank Angle modulation is considered as the primary control with a predefined nominal Angle of attack profile. In this approach, Bank Angle is approximated using a higher order polynomial. This control variable is discretized at Chebyshev Lobatto collocation points. The value of Bank Angle at these points is obtained using PIO algorithm. The terminal constraints of entry trajectory are part of the objective function. After generating the entry trajectory referred to as reference trajectory, Linear Quadratic Regulator (LQR) control is used to track the reference trajectory for dispersions in the initial states at entry interface. Advantages of PIO algorithm are that it does not require an initial guess and that inequality constraints can be incorporated. This method is demonstrated by applying it to Common Aero Vehicle (CAV-H) with high lift to drag ratio.
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evolutionary method based integrated guidance strategy for reentry vehicles
Engineering Applications of Artificial Intelligence, 2017Co-Authors: Gangireddy Sushnigdha, Ashok JoshiAbstract:Abstract In this paper, the guidance problem of winged re-entry vehicle with path constraints has been solved using an integrated guidance strategy that combines evolutionary method based pigeon inspired optimization (PIO) with gradient based Gauss Newton (GN) optimization algorithm. Re-entry phase is an unpowered flight that has Bank Angle modulation as the primary control variable. The Bank Angle is parametrized to be linear with respect to energy. This reduces the guidance problem to single parameter search problem. In the first phase of the integrated guidance scheme, PIO is used to find a Bank Angle that satisfies a predefined objective function. The corresponding Bank Angle is further updated by the GN algorithm to minimize the terminal error in the range-to-go. GN algorithm is used as a part of predictor–corrector guidance algorithm that requires an initial guess of the Bank Angle in each guidance cycle. The choice of initial guess has been eliminated in the proposed algorithm by incorporating PIO. Results of the proposed algorithm have been compared with the traditional predictor–corrector (PC) algorithm. It has been observed that the performance of proposed algorithm is as good as that of PC algorithm with added advantage of being insensitive to initial guess requirement and also overcomes the divergence issues.
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evolutionary method based hybrid entry guidance strategy for reentry vehicles
IFAC-PapersOnLine, 2016Co-Authors: Gangireddy Sushnigdha, Ashok JoshiAbstract:Abstract This paper presents a hybrid approach combining Pigeon Inspired Optimization (PIO) with Gauss-Newton method for entry guidance of winged vehicles. The Bank Angle modulation is considered as the primary control. In the hybrid guidance approach, PIO algorithm is initially used to find a Bank Angle that satisfies a predefined cost function. In the second phase, the corresponding Bank Angle is updated to correct the terminal errors using Gauss-Newton algorithm. Advantages of PIO algorithm are that it does not require an initial guess and that equality and inequality constraints can be incorporated, apart from the fact that it has global convergence and randomness. Gauss-Newton method, however, is deterministic and ensures global convergence with high accuracy given an initial guess. Thus, hybrid guidance algorithm exploits the benefits of both and determines an optimal Bank Angle profile that steers the vehicle to destination accurately, satisfying the path constraints. The simulation results show effectiveness of the proposed algorithm.
Gangireddy Sushnigdha - One of the best experts on this subject based on the ideXlab platform.
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trajectory design of re entry vehicles using combined pigeon inspired optimization and orthogonal collocation method
IFAC-PapersOnLine, 2018Co-Authors: Gangireddy Sushnigdha, Ashok JoshiAbstract:Abstract This paper presents an orthogonal collocation based entry trajectory solution strategy using Pigeon Inspired Optimization (PIO). PIO is a swarm algorithm based on the homing behavior of pigeons. For the unpowered re-entry vehicle, Bank Angle modulation is considered as the primary control with a predefined nominal Angle of attack profile. In this approach, Bank Angle is approximated using a higher order polynomial. This control variable is discretized at Chebyshev Lobatto collocation points. The value of Bank Angle at these points is obtained using PIO algorithm. The terminal constraints of entry trajectory are part of the objective function. After generating the entry trajectory referred to as reference trajectory, Linear Quadratic Regulator (LQR) control is used to track the reference trajectory for dispersions in the initial states at entry interface. Advantages of PIO algorithm are that it does not require an initial guess and that inequality constraints can be incorporated. This method is demonstrated by applying it to Common Aero Vehicle (CAV-H) with high lift to drag ratio.
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evolutionary method based integrated guidance strategy for reentry vehicles
Engineering Applications of Artificial Intelligence, 2017Co-Authors: Gangireddy Sushnigdha, Ashok JoshiAbstract:Abstract In this paper, the guidance problem of winged re-entry vehicle with path constraints has been solved using an integrated guidance strategy that combines evolutionary method based pigeon inspired optimization (PIO) with gradient based Gauss Newton (GN) optimization algorithm. Re-entry phase is an unpowered flight that has Bank Angle modulation as the primary control variable. The Bank Angle is parametrized to be linear with respect to energy. This reduces the guidance problem to single parameter search problem. In the first phase of the integrated guidance scheme, PIO is used to find a Bank Angle that satisfies a predefined objective function. The corresponding Bank Angle is further updated by the GN algorithm to minimize the terminal error in the range-to-go. GN algorithm is used as a part of predictor–corrector guidance algorithm that requires an initial guess of the Bank Angle in each guidance cycle. The choice of initial guess has been eliminated in the proposed algorithm by incorporating PIO. Results of the proposed algorithm have been compared with the traditional predictor–corrector (PC) algorithm. It has been observed that the performance of proposed algorithm is as good as that of PC algorithm with added advantage of being insensitive to initial guess requirement and also overcomes the divergence issues.
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evolutionary method based hybrid entry guidance strategy for reentry vehicles
IFAC-PapersOnLine, 2016Co-Authors: Gangireddy Sushnigdha, Ashok JoshiAbstract:Abstract This paper presents a hybrid approach combining Pigeon Inspired Optimization (PIO) with Gauss-Newton method for entry guidance of winged vehicles. The Bank Angle modulation is considered as the primary control. In the hybrid guidance approach, PIO algorithm is initially used to find a Bank Angle that satisfies a predefined cost function. In the second phase, the corresponding Bank Angle is updated to correct the terminal errors using Gauss-Newton algorithm. Advantages of PIO algorithm are that it does not require an initial guess and that equality and inequality constraints can be incorporated, apart from the fact that it has global convergence and randomness. Gauss-Newton method, however, is deterministic and ensures global convergence with high accuracy given an initial guess. Thus, hybrid guidance algorithm exploits the benefits of both and determines an optimal Bank Angle profile that steers the vehicle to destination accurately, satisfying the path constraints. The simulation results show effectiveness of the proposed algorithm.
Sun Guoqing - One of the best experts on this subject based on the ideXlab platform.
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high velocity vehicle entry trajectory planning based on Bank Angle control
Computer Simulation, 2012Co-Authors: Sun GuoqingAbstract:The high velocity vehicles make turns by changing heading Angle and it will result in big radius of turning circle and reduces maneuverability.A trajectory design method based on Bank Angle control was proposed to solve this problem.First,a flight dynamic model was built up and then the dynamic pressure,loads and heating constraints were modeled.The equilibrium glide constraint was also considered.Secondly,the inequality path constraints were converted into Bank Angle constraint to achieve turning with small radius while all the constraints were satisfied.The simulation shows that this method is more precise than pure geometry planning method and the trajectory is convenient to be tracked by control system.The proposed method is practical in trajectory planning problems.
