Alexander Bogdanov - Academia.edu (original) (raw)
Papers by Alexander Bogdanov
In this work possibility of improvement of algorithms of neurocontrol of anthropomorphic manipula... more In this work possibility of improvement of algorithms of neurocontrol of anthropomorphic manipulators is researched. Problems solved include: synthesis of neural stabilizing and optimal control algorithms with improved performance and robustness; and simulation of achieved results. New algorithms of optimal in time neural control of manipulators are based on global decomposition of dynamic model, considering the constraints on accelerations of the robot joints. The proposed combination of traditional nonlinear control algorithms and neural algorithms of dynamic model approximation ensures improved control quality (required transient parameters). The proposed method makes possible to compensate dynamics approximation errors, thus providing robust control. Obtained robustness estimates for developed neurocontrol algorithms establish relation between transients quality and parameter disturbances, caused by inaccurate approximation. The earlier obtained results (1996) are generalized an...
Defense Transformation and Net-Centric Systems 2008, 2008
Increased vehicle autonomy, survivability and utility can provide an unprecedented impact on miss... more Increased vehicle autonomy, survivability and utility can provide an unprecedented impact on mission success and are one of the most desirable improvements for modern autonomous vehicles. We propose a general architecture of intelligent resource allocation, reconfigurable control and system restructuring for autonomous vehicles. The architecture is based on fault-tolerant control and lifetime prediction principles, and it provides improved vehicle survivability, extended service intervals, greater operational autonomy through lower rate of time-critical mission failures and lesser dependence on supplies and maintenance. The architecture enables mission distribution, adaptation and execution constrained on vehicle and payload faults and desirable lifetime. The proposed architecture will allow managing missions more efficiently by weighing vehicle capabilities versus mission objectives and replacing the vehicle only when it is necessary.
AIAA Infotech@Aerospace 2010, 2010
This paper describes a dual-loop control design for a helicopter model using the statedependent R... more This paper describes a dual-loop control design for a helicopter model using the statedependent Riccati equation (SDRE) technique. The dual-loop design decouples vehicle dynamics into translational and attitude parts. In the dual-loop design, the outer loop (guidance loop) controller tracks the desired position and velocity of the vehicle and generates desired roll and pitch as inputs for the inner loop controller. The inner loop controller provides the desired attitude tracking. In this paper, both controllers are based on the augmented SDRE approach, which employs means of mitigating effects of vehicle dynamics approximations in the SDRE design. The dual-loop SDRE performance is compared to the full-state single-loop SDRE design, in which the whole system dynamics is manipulated into a state-dependent coefficient form.
Proceedings of the 45th IEEE Conference on Decision and Control, 2006
ABSTRACT We consider a linear quadratic optimal regulation problem of a servo motor in the presen... more ABSTRACT We consider a linear quadratic optimal regulation problem of a servo motor in the presence of stochastic load disturbance subject to a constraint that establishes a desired motor winding lifetime. To satisfy the constraint, a family of LQR control designs is parameterized with a single scalar performance weight that establishes a trade-off between performance and control power. Power analysis approach is then used to find the optimal value of the parameter that provides maximum disturbance rejection control in the given LQR family subject to the desired motor lifetime constraint
Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148), 2001
In this paper we present a method for optimal control of MIMO non-linear systems based on a combi... more In this paper we present a method for optimal control of MIMO non-linear systems based on a combination of a neural network (NN) feedback controller and a state-dependent Riccati equation (SDRE) controller. Optimization of the NN is performed within a receding horizon model predictive control (MPC) framework, subject to dynamic and kinematic constraints. The SDRE controller augments the NN controller by providing an initial feasible solution and improving stability. The resulting technique is applied to a 6 degree of freedom (DoF) model of an autonomous helicopter. This work was sponsored by DARPA under grant F33615-98-C-3516 with principal co-investigators Richard Kieburtz, Eric Wan, and Antonio Baptista. We also would like to express special thanks to Ying Long Zhang, Andy Moran and Magnus Carlsson for assistance with the helicopter model programming.
In this report a number of algorithms for optimal control of a double inverted pendulum on a cart... more In this report a number of algorithms for optimal control of a double inverted pendulum on a cart (DIPC) are investigated and compared. Modeling is based on Euler-Lagrange equations derived by specifying a Lagrangian, dierence between kinetic and potential energy of the DIPC system. This results in a system of nonlinear dieren tial equations consisting of three 2-nd order equations. This system of equations is then transformed into a usual form of six 1-st order ordinary dieren tial equations (ODE) for control design pur- poses. Control of a DIPC poses a certain challenge, since unlike a robot, the system is underactuated: one controlling force per three degrees of freedom (DOF). In this report, problem of optimal control minimizing a quadratic cost functional is addressed. Several approaches are tested: linear quadratic regulator (LQR), state-dependent Riccati equation (SDRE), optimal neural network (NN) control, and combinations of the NN with the LQR and the SDRE. Simulations reveal superior performance of the SDRE over the LQR and improvements provided by the NN, which compensates for model inadequacies in the LQR. Limited capa- bilities of the NN to approximate functions over the wide range of arguments prevent it from signican tly improving the SDRE performance, providing only marginal benets at larger pendulum deections.
Abstract: This paper presents the vision-only navigation and control of a small autonomous helico... more Abstract: This paper presents the vision-only navigation and control of a small autonomous helicopter given only measurements from a video camera fixed on the ground. The goal is to develop an alternative to traditional INS/GPS and on-board vision aided systems. The ...
2006 IEEE Aerospace Conference, 2006
The harder an actuator is pushed to its performance limits, the shorter its lifetime becomes. Exi... more The harder an actuator is pushed to its performance limits, the shorter its lifetime becomes. Existing actuator controllers are typically designed to optimize performance and robustness, without considering the operational lifetime of the actuator. However, it is often desirable to trade off performance for extended lifetime in order to reduce vehicle maintenance cost and improve vehicle safety and mission readiness.
AIAA Guidance, Navigation, and Control Conference and Exhibit, 2003
This paper is an initial report on flight experiments with a small, unmanned helicopter using a s... more This paper is an initial report on flight experiments with a small, unmanned helicopter using a state dependent Riccati Equation (SDRE) controller for autonomous, agile maneuvering. The control design is based upon a full, 6-DoF, analytic nonlinear dynamic model, which is manipulated into a pseudo-linear form in which system matrices are given explicitly as a function of the current state. A standard Riccati equation is then solved numerically in each frame of a 50 Hz. control loop to design the state feedback control law on-line. Several flights have been flown with the helicopter to evaluate the accuracy of tracking under SDRE control in comparison with simulation results.
this paper we consider general multi-input-multi-output (MIMO) nonlinear systems with tracking er... more this paper we consider general multi-input-multi-output (MIMO) nonlinear systems with tracking error costs of the form L k ## k ; # k ### k ## k # # k ## k ### k (10.2) where # k # # k # # k , with corresponding to a desired reference state trajectory. The last term assesses a penalty for
Defense Transformation and Net-Centric Systems 2008, 2008
ABSTRACT Increased vehicle autonomy, survivability and utility can provide an unprecedented impac... more ABSTRACT Increased vehicle autonomy, survivability and utility can provide an unprecedented impact on mission success and are one of the most desirable improvements for modern autonomous vehicles. We propose a general architecture of intelligent resource allocation, reconfigurable control and system restructuring for autonomous vehicles. The architecture is based on fault-tolerant control and lifetime prediction principles, and it provides improved vehicle survivability, extended service intervals, greater operational autonomy through lower rate of time-critical mission failures and lesser dependence on supplies and maintenance. The architecture enables mission distribution, adaptation and execution constrained on vehicle and payload faults and desirable lifetime. The proposed architecture will allow managing missions more efficiently by weighing vehicle capabilities versus mission objectives and replacing the vehicle only when it is necessary.
AIAA Infotech@Aerospace Conference, Apr 2010
This paper describes a dual-loop control design for a helicopter model using the state-dependent ... more This paper describes a dual-loop control design for a helicopter model using the state-dependent Riccati equation (SDRE) technique. The dual-loop design decouples vehicle dynamics into translational and attitude parts. In the dual-loop design, the outer loop (guidance loop) controller tracks the desired position and velocity of the vehicle and generates desired roll and pitch as inputs for the inner loop controller. The inner loop controller provides the desired attitude tracking. In this paper, both controllers are based on the augmented SDRE approach, which employs means of mitigating effects of vehicle dynamics
approximations in the SDRE design. The dual-loop SDRE performance is compared to the full-state single-loop SDRE design, in which the whole system dynamics is manipulated
into a state-dependent coefficient form.
Proc. SPIE 6981, Defense Transformation and Net-Centric Systems 2008, 2008
Increased vehicle autonomy, survivability and utility can provide an unprecedented impact on miss... more Increased vehicle autonomy, survivability and utility can provide an unprecedented impact on mission success and are one of the most desirable improvements for modern autonomous vehicles. We propose a general architecture of intelligent resource allocation, reconfigurable control and system restructuring for autonomous vehicles. The architecture is based on fault-tolerant control and lifetime prediction principles, and it provides improved vehicle survivability, extended service intervals, greater operational autonomy through lower rate of time-critical mission failures and lesser dependence on supplies and maintenance. The architecture enables mission distribution, adaptation and execution constrained on vehicle and payload faults and desirable lifetime. The proposed architecture will allow managing missions more efficiently by weighing vehicle capabilities versus mission objectives and replacing the vehicle only when it is necessary.
This paper presents a flight control approach based on a state-dependent Riccati equation (SDRE) ... more This paper presents a flight control approach based on a state-dependent Riccati equation (SDRE)
and its application to autonomous helicopters. For our experiments, we used two different platforms, an
XCell-90 small hobby helicopter and a larger vehicle based on the Yamaha R-Max. The control design uses a
six-degree-of-freedom nonlinear dynamic model that is manipulated into a pseudo-linear form where system
matrices are given explicitly as a function of the current state. A standard Riccati equation is then solved
numerically at each step of a 50 Hz control loop to design the nonlinear state feedback control law on-line.
In addition, the SDRE control is augmented with a nonlinear compensator that addresses issues with the
mismatch between the original nonlinear dynamics and its pseudo-linear transformation.
ION National Technical Meeting, Jan 2007
This paper presents the vision-only navigation and control of a small autonomous helicopter give... more This paper presents the vision-only navigation and control
of a small autonomous helicopter given only
measurements from a video camera fixed on the ground.
The goal is to develop an alternative to traditional
INS/GPS and on-board vision aided systems.
The autonomous navigation and control of the helicopter
is achieved using a nonlinear state estimator and a state-dependent
controller. A key difference to INS/GPS
navigation is that measurements of the helicopter’s
accelerations and angular velocities are not directly
available. The state estimation combines the vision
measurements with a dynamic model of the vehicle in a
recursive filtering procedure using a Sigma-Point Kalman
Filter (SPKF). The estimation of the helicopter’s current
state (position, attitude, velocity, and angular velocity) is
then fed back in real-time to a state-dependent Riccati
equation (SDRE) controller to generate radio control
commands to the helicopter.
Simulations are provided comparing performance relative
to INS/GPS navigation. Experiments also show that an
accurate dynamic model of the vehicle is necessary for
closed-loop stability. Our results indicate the feasibility of
designing a vision-only estimation and control system
capable of stabilizing and maneuvering a small unmanned
helicopter.
Other than simple on-board avionics for low level
actuator control, the ground station is responsible for
video capture, state-estimation, and state-feedback flight
control.
Conference on Decision and Control, 2006
We consider a linear quadratic optimal regulation problem of a servo motor in the presence of st... more We consider a linear quadratic optimal regulation
problem of a servo motor in the presence of stochastic
load disturbance subject to a constraint that establishes a
desired motor winding lifetime. To satisfy the constraint, a
family of LQR control designs is parameterized with a single
scalar performance weight that establishes a trade-off between
performance and control power. Power analysis approach is
then used to find the optimal value of the parameter that
provides maximum disturbance rejection control in the given
LQR family subject to the desired motor lifetime constraint.
In this work possibility of improvement of algorithms of neurocontrol of anthropomorphic manipula... more In this work possibility of improvement of algorithms of neurocontrol of anthropomorphic manipulators is researched. Problems solved include: synthesis of neural stabilizing and optimal control algorithms with improved performance and robustness; and simulation of achieved results. New algorithms of optimal in time neural control of manipulators are based on global decomposition of dynamic model, considering the constraints on accelerations of the robot joints. The proposed combination of traditional nonlinear control algorithms and neural algorithms of dynamic model approximation ensures improved control quality (required transient parameters). The proposed method makes possible to compensate dynamics approximation errors, thus providing robust control. Obtained robustness estimates for developed neurocontrol algorithms establish relation between transients quality and parameter disturbances, caused by inaccurate approximation. The earlier obtained results (1996) are generalized an...
Defense Transformation and Net-Centric Systems 2008, 2008
Increased vehicle autonomy, survivability and utility can provide an unprecedented impact on miss... more Increased vehicle autonomy, survivability and utility can provide an unprecedented impact on mission success and are one of the most desirable improvements for modern autonomous vehicles. We propose a general architecture of intelligent resource allocation, reconfigurable control and system restructuring for autonomous vehicles. The architecture is based on fault-tolerant control and lifetime prediction principles, and it provides improved vehicle survivability, extended service intervals, greater operational autonomy through lower rate of time-critical mission failures and lesser dependence on supplies and maintenance. The architecture enables mission distribution, adaptation and execution constrained on vehicle and payload faults and desirable lifetime. The proposed architecture will allow managing missions more efficiently by weighing vehicle capabilities versus mission objectives and replacing the vehicle only when it is necessary.
AIAA Infotech@Aerospace 2010, 2010
This paper describes a dual-loop control design for a helicopter model using the statedependent R... more This paper describes a dual-loop control design for a helicopter model using the statedependent Riccati equation (SDRE) technique. The dual-loop design decouples vehicle dynamics into translational and attitude parts. In the dual-loop design, the outer loop (guidance loop) controller tracks the desired position and velocity of the vehicle and generates desired roll and pitch as inputs for the inner loop controller. The inner loop controller provides the desired attitude tracking. In this paper, both controllers are based on the augmented SDRE approach, which employs means of mitigating effects of vehicle dynamics approximations in the SDRE design. The dual-loop SDRE performance is compared to the full-state single-loop SDRE design, in which the whole system dynamics is manipulated into a state-dependent coefficient form.
Proceedings of the 45th IEEE Conference on Decision and Control, 2006
ABSTRACT We consider a linear quadratic optimal regulation problem of a servo motor in the presen... more ABSTRACT We consider a linear quadratic optimal regulation problem of a servo motor in the presence of stochastic load disturbance subject to a constraint that establishes a desired motor winding lifetime. To satisfy the constraint, a family of LQR control designs is parameterized with a single scalar performance weight that establishes a trade-off between performance and control power. Power analysis approach is then used to find the optimal value of the parameter that provides maximum disturbance rejection control in the given LQR family subject to the desired motor lifetime constraint
Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148), 2001
In this paper we present a method for optimal control of MIMO non-linear systems based on a combi... more In this paper we present a method for optimal control of MIMO non-linear systems based on a combination of a neural network (NN) feedback controller and a state-dependent Riccati equation (SDRE) controller. Optimization of the NN is performed within a receding horizon model predictive control (MPC) framework, subject to dynamic and kinematic constraints. The SDRE controller augments the NN controller by providing an initial feasible solution and improving stability. The resulting technique is applied to a 6 degree of freedom (DoF) model of an autonomous helicopter. This work was sponsored by DARPA under grant F33615-98-C-3516 with principal co-investigators Richard Kieburtz, Eric Wan, and Antonio Baptista. We also would like to express special thanks to Ying Long Zhang, Andy Moran and Magnus Carlsson for assistance with the helicopter model programming.
In this report a number of algorithms for optimal control of a double inverted pendulum on a cart... more In this report a number of algorithms for optimal control of a double inverted pendulum on a cart (DIPC) are investigated and compared. Modeling is based on Euler-Lagrange equations derived by specifying a Lagrangian, dierence between kinetic and potential energy of the DIPC system. This results in a system of nonlinear dieren tial equations consisting of three 2-nd order equations. This system of equations is then transformed into a usual form of six 1-st order ordinary dieren tial equations (ODE) for control design pur- poses. Control of a DIPC poses a certain challenge, since unlike a robot, the system is underactuated: one controlling force per three degrees of freedom (DOF). In this report, problem of optimal control minimizing a quadratic cost functional is addressed. Several approaches are tested: linear quadratic regulator (LQR), state-dependent Riccati equation (SDRE), optimal neural network (NN) control, and combinations of the NN with the LQR and the SDRE. Simulations reveal superior performance of the SDRE over the LQR and improvements provided by the NN, which compensates for model inadequacies in the LQR. Limited capa- bilities of the NN to approximate functions over the wide range of arguments prevent it from signican tly improving the SDRE performance, providing only marginal benets at larger pendulum deections.
Abstract: This paper presents the vision-only navigation and control of a small autonomous helico... more Abstract: This paper presents the vision-only navigation and control of a small autonomous helicopter given only measurements from a video camera fixed on the ground. The goal is to develop an alternative to traditional INS/GPS and on-board vision aided systems. The ...
2006 IEEE Aerospace Conference, 2006
The harder an actuator is pushed to its performance limits, the shorter its lifetime becomes. Exi... more The harder an actuator is pushed to its performance limits, the shorter its lifetime becomes. Existing actuator controllers are typically designed to optimize performance and robustness, without considering the operational lifetime of the actuator. However, it is often desirable to trade off performance for extended lifetime in order to reduce vehicle maintenance cost and improve vehicle safety and mission readiness.
AIAA Guidance, Navigation, and Control Conference and Exhibit, 2003
This paper is an initial report on flight experiments with a small, unmanned helicopter using a s... more This paper is an initial report on flight experiments with a small, unmanned helicopter using a state dependent Riccati Equation (SDRE) controller for autonomous, agile maneuvering. The control design is based upon a full, 6-DoF, analytic nonlinear dynamic model, which is manipulated into a pseudo-linear form in which system matrices are given explicitly as a function of the current state. A standard Riccati equation is then solved numerically in each frame of a 50 Hz. control loop to design the state feedback control law on-line. Several flights have been flown with the helicopter to evaluate the accuracy of tracking under SDRE control in comparison with simulation results.
this paper we consider general multi-input-multi-output (MIMO) nonlinear systems with tracking er... more this paper we consider general multi-input-multi-output (MIMO) nonlinear systems with tracking error costs of the form L k ## k ; # k ### k ## k # # k ## k ### k (10.2) where # k # # k # # k , with corresponding to a desired reference state trajectory. The last term assesses a penalty for
Defense Transformation and Net-Centric Systems 2008, 2008
ABSTRACT Increased vehicle autonomy, survivability and utility can provide an unprecedented impac... more ABSTRACT Increased vehicle autonomy, survivability and utility can provide an unprecedented impact on mission success and are one of the most desirable improvements for modern autonomous vehicles. We propose a general architecture of intelligent resource allocation, reconfigurable control and system restructuring for autonomous vehicles. The architecture is based on fault-tolerant control and lifetime prediction principles, and it provides improved vehicle survivability, extended service intervals, greater operational autonomy through lower rate of time-critical mission failures and lesser dependence on supplies and maintenance. The architecture enables mission distribution, adaptation and execution constrained on vehicle and payload faults and desirable lifetime. The proposed architecture will allow managing missions more efficiently by weighing vehicle capabilities versus mission objectives and replacing the vehicle only when it is necessary.
AIAA Infotech@Aerospace Conference, Apr 2010
This paper describes a dual-loop control design for a helicopter model using the state-dependent ... more This paper describes a dual-loop control design for a helicopter model using the state-dependent Riccati equation (SDRE) technique. The dual-loop design decouples vehicle dynamics into translational and attitude parts. In the dual-loop design, the outer loop (guidance loop) controller tracks the desired position and velocity of the vehicle and generates desired roll and pitch as inputs for the inner loop controller. The inner loop controller provides the desired attitude tracking. In this paper, both controllers are based on the augmented SDRE approach, which employs means of mitigating effects of vehicle dynamics
approximations in the SDRE design. The dual-loop SDRE performance is compared to the full-state single-loop SDRE design, in which the whole system dynamics is manipulated
into a state-dependent coefficient form.
Proc. SPIE 6981, Defense Transformation and Net-Centric Systems 2008, 2008
Increased vehicle autonomy, survivability and utility can provide an unprecedented impact on miss... more Increased vehicle autonomy, survivability and utility can provide an unprecedented impact on mission success and are one of the most desirable improvements for modern autonomous vehicles. We propose a general architecture of intelligent resource allocation, reconfigurable control and system restructuring for autonomous vehicles. The architecture is based on fault-tolerant control and lifetime prediction principles, and it provides improved vehicle survivability, extended service intervals, greater operational autonomy through lower rate of time-critical mission failures and lesser dependence on supplies and maintenance. The architecture enables mission distribution, adaptation and execution constrained on vehicle and payload faults and desirable lifetime. The proposed architecture will allow managing missions more efficiently by weighing vehicle capabilities versus mission objectives and replacing the vehicle only when it is necessary.
This paper presents a flight control approach based on a state-dependent Riccati equation (SDRE) ... more This paper presents a flight control approach based on a state-dependent Riccati equation (SDRE)
and its application to autonomous helicopters. For our experiments, we used two different platforms, an
XCell-90 small hobby helicopter and a larger vehicle based on the Yamaha R-Max. The control design uses a
six-degree-of-freedom nonlinear dynamic model that is manipulated into a pseudo-linear form where system
matrices are given explicitly as a function of the current state. A standard Riccati equation is then solved
numerically at each step of a 50 Hz control loop to design the nonlinear state feedback control law on-line.
In addition, the SDRE control is augmented with a nonlinear compensator that addresses issues with the
mismatch between the original nonlinear dynamics and its pseudo-linear transformation.
ION National Technical Meeting, Jan 2007
This paper presents the vision-only navigation and control of a small autonomous helicopter give... more This paper presents the vision-only navigation and control
of a small autonomous helicopter given only
measurements from a video camera fixed on the ground.
The goal is to develop an alternative to traditional
INS/GPS and on-board vision aided systems.
The autonomous navigation and control of the helicopter
is achieved using a nonlinear state estimator and a state-dependent
controller. A key difference to INS/GPS
navigation is that measurements of the helicopter’s
accelerations and angular velocities are not directly
available. The state estimation combines the vision
measurements with a dynamic model of the vehicle in a
recursive filtering procedure using a Sigma-Point Kalman
Filter (SPKF). The estimation of the helicopter’s current
state (position, attitude, velocity, and angular velocity) is
then fed back in real-time to a state-dependent Riccati
equation (SDRE) controller to generate radio control
commands to the helicopter.
Simulations are provided comparing performance relative
to INS/GPS navigation. Experiments also show that an
accurate dynamic model of the vehicle is necessary for
closed-loop stability. Our results indicate the feasibility of
designing a vision-only estimation and control system
capable of stabilizing and maneuvering a small unmanned
helicopter.
Other than simple on-board avionics for low level
actuator control, the ground station is responsible for
video capture, state-estimation, and state-feedback flight
control.
Conference on Decision and Control, 2006
We consider a linear quadratic optimal regulation problem of a servo motor in the presence of st... more We consider a linear quadratic optimal regulation
problem of a servo motor in the presence of stochastic
load disturbance subject to a constraint that establishes a
desired motor winding lifetime. To satisfy the constraint, a
family of LQR control designs is parameterized with a single
scalar performance weight that establishes a trade-off between
performance and control power. Power analysis approach is
then used to find the optimal value of the parameter that
provides maximum disturbance rejection control in the given
LQR family subject to the desired motor lifetime constraint.