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A linear aircraft model for a rigid aircraft of constant mass flying over a flat, nonrotating earth is derived and defined. The derivation makes no assumptions of reference trajectory or vehicle symmetry. The linear system equations are derived and evaluated along a general trajectory and include both aircraft dynamics and observation variables.
An analysis is presented of two types of nonlinear gain-scheduled control systems: scheduling on a reference trajectory and scheduling on the plant output. Conditions are given which guarantee stability, robustness, and performance properties of the global gain-scheduled designs. These conditions confirm and formalize popular notions regarding gain-scheduled designs; e.g., that the scheduling variable should vary slowly and capture the plant's nonlinearities. These results extend the work of Shamma and Athans (1987), which addressed the case of linear plants whose dynamics depends on exogenous parameters.
A simple approach for controlling the manipulator configuration over the entire motion is presented, based on augmentation of the manipulator forward kinematics. User-defined kinematic functions and the end-effector Cartesian coordinates are combined to form a set of task-related configuration variables as generalized coordinates for the manipulator. A task-based adaptive scheme is then utilized to control the configuration variables and achieve tracking of the desired reference trajectories. This achieves the desired end-effector motion while utilizing redundancy to achieve any additional task. Simulation results for a direct-drive two-link arm are given to illustrate the proposed control scheme. The scheme has also been implemented for real-time control of three links of a PUMA 560 industrial robot. The simulation and experimental results validate the configuration control scheme and demonstrate its capabilities for performing various realistic tasks.
A new and simple approach to configuration control of redundant manipulators is presented. In this approach, the redundancy is utilized to control the manipulator configuration directly in task space, where the task will be performed. A number of kinematic functions are defined to reflect the desirable configuration that will be achieved for a given end-effector position. The user-defined kinematic functions and the end-effector Cartesian coordinates are combined to form a set of task-related configuration variables as generalized coordinates for the manipulator. An adaptive scheme is then utilized to globally control the configuration variables so as to achieve tracking of some desired reference trajectories. This accomplishes the basic task of desired end-effector motion, while utilizing the redundancy to achieve any additional task through the desired time variation of the kinematic functions. The control law is simple and computationally very fast, and does not require the complex manipulator dynamic model.
A simple approach to configuration control of redundant robots is presented. The redundancy is utilized to control the robot configuration directly in task space, where the task will be performed. A number of task-related kinematic functions are defined and combined with the end-effector coordinates to form a set of configuration variables. An adaptive control scheme is then utilized to ensure that the configuration variables track the desired reference trajectories as closely as possible. Simulation results are presented to illustrate the control scheme. The scheme has also been implemented for direct online control of a PUMA industrial robot, and experimental results are presented. The simulation and experimental results validate the configuration control scheme for performing various realistic tasks.
Gain scheduling has proven to be a successful design methodology in many engineering applications. In the absence of a sound theoretical analysis, these designs come with no guarantees of the robustness, performance, or even nominal stability of the overall gain-scheduled design. An analysis is presented for two types of nonlinear gain-scheduled control systems: (1) scheduling on a reference trajectory and (2) scheduling on the plant output. Conditions which guarantee stability, robustness, and performance properties of the global gain schedule designs are given. These conditions confirm and formalize popular notions regarding gain-scheduled designs, such as that the scheduling variable should vary slowly and capture the plant's nonlinearities.
A method and apparatus to control a robot or manipulator configuration over the entire motion based on augmentation of the manipulator forward kinematics is disclosed. A set of kinematic functions is defined in Cartesian or joint space to reflect the desirable configuration that will be achieved in addition to the specified end-effector motion. The user-defined kinematic functions and the end-effector Cartesian coordinates are combined to form a set of task-related configuration variables as generalized coordinates for the manipulator. A task-based adaptive scheme is then utilized to directly control the configuration variables so as to achieve tracking of some desired reference trajectories throughout the robot motion. This accomplishes the basic task of desired end-effector motion, while utilizing the redundancy to achieve any additional task through the desired time variation of the kinematic functions. The present invention can also be used for optimization of any kinematic objective function, or for satisfaction of a set of kinematic inequality constraints, as in an obstacle avoidance problem. In contrast to pseudoinverse-based methods, the configuration control scheme ensures cyclic motion of the manipulator, which is an essential requirement for repetitive operations. The control law is simple and computationally very fast, and does not require either the complex manipulator dynamic model or the complicated inverse kinematic transformation. The configuration control scheme can alternatively be implemented in joint space.
The requirements of nuclear thermal propulsion (NTP) are examined with respect to a specific mission scenario derived from Stafford Committee recommendations. The recommended mission scenario is a split/sprint opposition mission which includes a piloted vehicle and a cargo vehicle, and the baseline mission is developed from a reference trajectory. Key mision parameters are developed from the baseline mission, including engine-thrust levels, mission opportunity, and engine burn-time requirements. The impact of engine failure is also considered in terms of burn-time requirements, and other mission-performance issues considered include propulsion-technology assumptions, triple-perigee earth-departure burns, and Mars parking-orbit selection. The engine requirements call for a 50-75-klb engine-thrust level, maximum single burn time of 0.6 hours, and a maximum total-mission burn time of 1.7 hours. For a crew of 6, a 475-day total-mission trip with a 90-day stay at Mars is possible.
Four atmospheric guidance concepts have been adapted to control an interplanetary vehicle aerobraking in the Martian atmosphere. The first two offer improvements to the Analytic Predictor Corrector (APC) to increase its robustness to density variations. The second two are variations of a new Liapunov tracking exit phase algorithm, developed to guide the vehicle along a reference trajectory. These four new controllers are tested using a six degree of freedom computer simulation to evaluate their robustness. MARSGRAM is used to develop realistic atmospheres for the study. When square wave density pulses perturb the atmosphere all four controllers are successful. The algorithms are tested against atmospheres where the inbound and outbound density functions are different. Square wave density pulses are again used, but only for the outbound leg of the trajectory. Additionally, sine waves are used to perturb the density function. The new algorithms are found to be more robust than any previously tested and a Liapunov controller is selected as the most robust control algorithm overall examined.
A unified identification and control scheme capable of achieving space at form performance objectives under nominal or failure conditions is described. Preliminary results are also presented, showing that the methodology offers much promise for effective robust control of large space structures. The control method is a multivariable, adaptive, output predictive controller called Model Predictive Control (MPC). MPC uses a state space model and input reference trajectories of set or tracking points to adaptively generate optimum commands. For a fixed model, MPC processes commands with great efficiency, and is also highly robust. A key feature of MPC is its ability to control either nonminimum phase or open loop unstable systems. As an output controller, MPC does not explicitly require full state feedback, as do most multivariable (e.g., Linear Quadratic) methods. Its features are very useful in LSS operations, as they allow non-collocated actuators and sensors. The identification scheme is based on canonical variate analysis (CVA) of input and output data. The CVA technique is particularly suited for the measurement and identification of structural dynamic processes - that is, unsteady transient or dynamically interacting processes such as between aerodynamics and structural deformation - from short, noisy data. CVA is structured so that the identification can be done in real or near real time, using computationally stable algorithms. Modeling LSS dynamics in 1-g laboratories has always been a major impediment not only to understanding their behavior in orbit, but also to controlling it. In cases where the theoretical model is not confirmed, current methods provide few clues concerning additional dynamical relationships that are not included in the theoretical models. CVA needs no a priori model data, or structure; all statistically significant dynamical states are determined using natural, entropy-based methods. Heretofore, a major limitation in applying adaptive controllers to LSS problems has been the requirement for accurate models. We feel that MPC coupled with the CVA identification scheme will resolve this limitation. The results are based on research performed under an SBIR grant, administered by the Air Force Office of Scientific Research.
A real-time control architecture is developed for time-varying nonlinear brushless dc motors operating in a high performance drives environment. The developed control architecture possesses the capabilities of simultaneous on-line identification and control. The dynamics of the motor are modeled on-line and controlled using an artificial neural network, as the system runs. The control architecture combines the experience and dependability of adaptive tracking systems with potential and promise of the neural computing technology. The sensitivity of real-time controller to parametric changes that occur during training is investigated. Such changes are usually manifested by rapid changes in the load of the brushless motor drives. This sudden change in the external load is simulated for the sigmoidal and sinusoidal reference tracks. The ability of the neuro-controller to maintain reasonable tracking accuracy in the presence of external noise is also verified for a number of desired reference trajectories.
In this paper we consider the exact output tracking problem for systems with parameter jumps. Necessary and sufficient conditions are derived for the elimination of switching-introduced output transient. Previous works have studied this problem by developing a regulator that maintains exact tracking through parameter jumps (switches). Such techniques are, however, only applicable to minimum-phase systems. In contrast, our approach is applicable to nonminimum-phase systems and obtains bounded but possibly non-causal solutions. If the reference trajectories are generated by an exo-system, then we develop an exact-tracking controller in a feedback form. As in standard regulator theory, we obtain a linear map from the states of the exo-system to the desired system state which is defined via a matrix differential equation. The constant solution of this differential equation provides asymptotic tracking, and coincides with the feedback law used in standard regulator theory. The obtained results are applied to a simple flexible manipulator with jumps in the pay-load mass.
We consider the exact output tracking problem for systems with parameter jumps. Necessary and sufficient conditions are derived for the elimination of switching-introduced output transient. Previous works have studied this problem by developing a regulator that maintains exact tracking through parameter jumps (switches). Such techniques are, however, only applicable to minimum-phase systems. In contrast, our approach is applicable to non-minimum-phase systems and it obtains bounded but possibly non-causal solutions. If the reference trajectories are generated by an exosystem, then we develop an exact-tracking controller in a feed-back form. As in standard regulator theory, we obtain a linear map from the states of the exosystem to the desired system state which is defined via a matrix differential equation. The constant solution of this differential equation provides asymptotic tracking, and coincides with the feedback law used in standard regulator theory. The obtained results are applied to a simple flexible manipulator with jumps in the pay-load mass.
A distributed satellite formation, modeled as an arbitrary number of fully connected nodes in a network, could be controlled using a decentralized controller framework that distributes operations in parallel over the network. For such problems, a solution that minimizes data transmission requirements, in the context of linear-quadratic-Gaussian (LQG) control theory, was given by Speyer. This approach is advantageous because it is non-hierarchical, detected failures gracefully degrade system performance, fewer local computations are required than for a centralized controller, and it is optimal with respect to the standard LQG cost function. Disadvantages of the approach are the need for a fully connected communications network, the total operations performed over all the nodes are greater than for a centralized controller, and the approach is formulated for linear time-invariant systems. To investigate the feasibility of the decentralized approach to satellite formation flying, a simple centralized LQG design for a spacecraft orbit control problem is adapted to the decentralized framework. The simple design uses a fixed reference trajectory (an equatorial, Keplerian, circular orbit), and by appropriate choice of coordinates and measurements is formulated as a linear time-invariant system.
A distributed satellite formation, modeled as an arbitrary number of fully connected nodes in a network, could be controlled using a decentralized controller framework that distributes operations in parallel over the network. For such problems, a solution that minimizes data transmission requirements, in the context of linear-quadratic-Gaussian (LQG) control theory, was given by Speyer. This approach is advantageous because it is non-hierarchical, detected failures gracefully degrade system performance, fewer local computations are required than for a centralized controller, and it is optimal with respect to the standard LQG cost function. Disadvantages of the approach are the need for a fully connected communications network, the total operations performed over all the nodes are greater than for a centralized controller, and the approach is formulated for linear time-invariant systems. To investigate the feasibility of the decentralized approach to satellite formation flying, a simple centralized LQG design for a spacecraft orbit control problem is adapted to the decentralized framework. The simple design uses a fixed reference trajectory (an equatorial, Keplerian, circular orbit), and by appropriate choice of coordinates and measurements is formulated as a linear time-invariant system.
The Thermal Calculation Analysis Tool (TCAT), originally developed for the Space Systems Design Lab at the Georgia Institute of Technology, is a conceptual design tool capable of integrating aeroheating analysis into conceptual reusable launch vehicle design. It provides Thermal Protection System (TPS) unit thicknesses and acreage percentages based on the geometry of the vehicle and a reference trajectory to be used in calculation of the total cost and weight of the vehicle design. TCAT has proven to be reasonably accurate at calculating the TPS unit weights for in-flight trajectories; however, it does not have the capability of sizing TPS materials above cryogenic fuel tanks for ground hold operations. During ground hold operations, the vehicle is held for a brief period (generally about two hours) during which heat transfer from the TPS materials to the cryogenic fuel occurs. If too much heat is extracted from the TPS material, the surface temperature may fall below the freezing point of water, thereby freezing any condensation that may be present at the surface of the TPS. Condensation or ice on the surface of the vehicle is potentially hazardous to the mission and can also damage the TPS. It is questionable whether or not the TPS thicknesses provided by the aeroheating analysis would be sufficiently thick to insulate the surface of the TPS from the heat transfer to the fuel. Therefore, a design tool has been developed that is capable of sizing TPS materials at these cryogenic fuel tank locations to augment TCAT's TPS sizing capabilities.
A study has been made of the use o f a terminal controller technique i n the guidance of a high-drag, variable-lift reentry vehicle to a desired landing point. The technique uses linearized equations of motion attained by the perturbation of the dependent variables from those of a reference trajectory. The guidance system continuously predicts the terminal range error and uses this error to control the angle of attack of the vehicle in an on-off manner until the predicted range error is within +-O.1 degrees of the required arc or +-6.9 miles.
The Mars Science Laboratory will be the first Mars mission to attempt a guided entry with the objective of safely delivering the entry vehicle to a survivable parachute deploy state within 10 km of the pre-designated landing site. The Entry Terminal Point Controller guidance algorithm is derived from the final phase Apollo Command Module guidance and, like Apollo, modulates the bank angle to control range based on deviations in range, altitude rate, and drag acceleration from a reference trajectory. For application to Mars landers which must make use of the tenuous Martian atmosphere, it is critical to balance the lift of the vehicle to minimize the range while still ensuring a safe deploy altitude. An overview of the process to generate optimized guidance settings is presented, discussing improvements made over the last four years. Performance tradeoffs between ellipse size and deploy altitude will be presented, along with imposed constraints of entry acceleration and heating. Performance sensitivities to the bank reversal deadbands, heading alignment, attitude initialization error, and atmospheric delivery errors are presented. Guidance settings for contingency operations, such as those appropriate for severe dust storm scenarios, are evaluated.