Andrus Pedai

Control of hovering manoeuvres in unmanned helicopter for enhanced situational awareness

This paper focuses on a critical component of the situational awareness, the control of autonomous vertical flight for an unmanned aerial vehicle. Autonomous vertical flight is a challenging but important task for tactical unmanned aerial vehicles to achieve high level of autonomy under adverse conditions. With the situational awareness strategy, we proposed a three stage flight control procedure using three autonomous control subsystems to address the dynamics variation and performance requirement difference in initial and final stages of flight trajectory for a nontrivial nonlinear helicopter model. This control strategy for chosen helicopter model has been verified by simulation of hovering manoeuvres using software package Simulink and demonstrated good performance for fast situational awareness in real-time search-and-rescue operations.

Enhancing situational awareness by means of hybrid adaptive neural control of vertical flight in unmanned helicopter

This paper focuses on a critical component of the situational awareness, the neural control of autonomous vertical flight for an unmanned aerial vehicle. Autonomous vertical flight is a challenging but important task for tactical unmanned aerial vehicles to achieve high level of autonomy under adverse conditions. The fundamental requirement for vertical flight is the knowledge of the height above the ground, and a properly designed controller to govern the process. With the situational awareness strategy, we proposed a two stage flight control procedure using two adaptive neural networks to address the dynamics variation and performance requirement difference in initial and final stages of flight trajectory for a nontrivial small-scale helicopter model comprising five states, two inputs and two outputs. This control strategy for chosen helicopter model has been verified by simulation of descending and landing manoeuvres using software package Simulink and demonstrated good performance for fast situational awareness in real-time search-and-rescue operations.

Situational awareness based flight control of a drone

This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for an unmanned aerial vehicle (UAV). With the SA strategy, we proposed a two stage flight control procedure to address the dynamics variation and performance requirement difference in initial and final stages of flight trajectory for a nontrivial nonlinear model of four-rotor helicopter robot called drone. This control strategy for chosen drone model has been verified by simulation of hovering maneuvers using software package Simulink and demonstrated good performance for fast stabilization of engines in hovering, consequently, fast SA with economy in energy of batteries can be asserted during the flight.

Desired trajectory generation of a quadrotor helicopter using hybrid control for enhanced situational awareness

This paper focuses on a critical component of the situational awareness, the control of autonomous vertical flight for an unmanned aerial vehicle. Autonomous vertical flight is a challenging but important task for tactical unmanned aerial vehicles to achieve high level of autonomy under adverse conditions. With the situational awareness strategy, we proposed a two stage flight control procedure using three autonomous control subsystems to address the dynamics variation and performance requirement difference in initial and final stages of flight trajectory for a nontrivial nonlinear quadrotor helicopter model. This control strategy for chosen helicopter model has been verified by simulation of hovering manoeuvres using software package Simulink and demonstrated good performance for fast situational awareness in real-time search-and-rescue operations.

Three-rate neural control of TUAV with coaxial rotor and ducted fan configuration for enhanced situational awareness

This paper describes a critical component of the situational awareness (SA), the control of tactical unmanned aerial vehicle (TUAV) during autonomous flight operations. With the SA strategy, we proposed a three-rate flight control procedure using three autonomous decomposed control subsystems with single NARMA-L2 controller for an unmanned helicopter model with coaxial rotor and ducted fan configuration. This strategy for chosen model of TUAV has been verified by simulation of flight tests using Simulink environment and demonstrated valuable qualities for fast stabilization of TUAVs engines during flight, consequently, fast SA with economy in energy can be asserted during possible missions.

Two-rate neural control of TUAV with coaxial rotor and ducted fan configuration for enhanced situational awareness

This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for tactical unmanned aerial vehicle (TUAV). With the SA strategy, we proposed a two-rate flight control procedure using two autonomous control subsystems to address the dynamics variation and performance requirement difference in initial and final stages of flight trajectory for an unmanned helicopter model with coaxial rotor and ducted fan configuration. This control strategy for chosen model of TUAV has been verified by simulation of flight maneuvers using software package Simulink and demonstrated good performance for fast stabilization of engines during flight, consequently, fast SA with economy in energy can be asserted during search-and-rescue operations.

Enhanced situational awareness for AUV's stochastic model by multirate neural control

This paper focuses on a critical component of the situational awareness (SA), the neural control of depth flight of an autonomous underwater vehicle (AUV). Constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. The fundamental requirement for constant depth flight is the knowledge of the depth, and a properly designed controller to govern the process. With the SA strategy, we proposed a multirate depth control procedure to address the dynamics variation and performance requirement difference in various stages of AUVs trajectory for a nontrivial mid-small size AUV “r2D4” stochastic model. One neural network controller, named NARMA-L2 controller, is designed for fast and stable diving maneuvers of this AUV model. This control strategy for chosen AUV model has been verified by simulation of diving maneuvers using software package Simulink and demonstrated good performance for fast SA in real-time search-and-rescue operations.

Enhancing situational awareness through multirate control of an autonomous underwater vehicle

This paper focuses on a critical component of the situational awareness (SA), the neural control of depth flight of an autonomous underwater vehicle (AUV). Constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. The fundamental requirement for constant depth flight is the knowledge of the depth, and a properly designed controller to govern the process. With the SA strategy, we proposed a multirate depth control procedure to address the dynamics variation and performance requirement difference in various stages of AUVs trajectory for a nontrivial mid-small size AUV “r2D4” model. Two adaptive neural network controllers are designed for fast and stable diving maneuvers of this AUV model. This hybrid control strategy for chosen AUV model has been verified by simulation of diving maneuvers using software package Simulink and demonstrated good performance for fast SA in real-time search-and-rescue operations.

Situational awareness based on neural control of an autonomous helicopter during hovering manoeuvres

This paper focuses on a critical component of the situational awareness, the neural network control of autonomous vertical flight for an unmanned aerial vehicle. Application of the proposed two stage flight strategy which uses two autonomous adaptive neural dynamical feedback controllers was carried out for a nontrivial small-scale helicopter model comprising five states, two inputs and two outputs. This control strategy for chosen helicopter model has been verified by simulation of hovering manoeuvres using software package Simulink and demonstrated good performance for fast situational awareness in real-time search-and-rescue operations.