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Articles 1 - 30 of 47
Full-Text Articles in Aerospace Engineering
Investigation And Control Of Görtler Vortices In High-Speed Flows, Omar Es-Sahli
Investigation And Control Of Görtler Vortices In High-Speed Flows, Omar Es-Sahli
Theses and Dissertations
High-amplitude freestream turbulence and surface roughness elements can excite a laminar boundary-layer flow sufficiently enough to cause streamwise-oriented vortices to develop. These vortices resemble elongated streaks having alternate spanwise variations of the streamwise velocity. Following the transient growth phase, the fully developed vortex structures downstream undergo an inviscid secondary instability mechanism and, ultimately, transition to turbulence. This mechanism becomes much more complicated in high-speed boundary layer flows due to compressibility and thermal effects, which become more significant for higher Mach numbers. In this research, we formulate and test an optimal control algorithm to suppress the growth rate of the aforementioned …
Stability Of Deep Neural Networks For Feedback-Optimal Pinpoint Landings, Omkar S. Mulekar, Hancheol Cho, Riccardo Bevilacqua
Stability Of Deep Neural Networks For Feedback-Optimal Pinpoint Landings, Omkar S. Mulekar, Hancheol Cho, Riccardo Bevilacqua
Student Works
The ability to certify systems driven by neural networks is crucial for future rollouts of machine learning technologies in aerospace applications. In this study, the neural networks are used to represent a fuel-optimal feedback controller for two different 3-degree-of-freedom pinpoint landing problems. It is shown that the standard sum-ofsquares Lyapunov candidate is too restrictive to assess the stability of systems with fuel-optimal control profiles. Instead, a parametric Lyapunov candidate (i.e. a neural network) can be trained to sufficiently evaluate the closed-loop stability of fuel-optimal control profiles. Then, a stability-constrained imitation learning method is applied, which simultaneously trains a neural network …
Optimal Sizing And Control Of Hybrid Rocket Vehicles, Srija Ryakam
Optimal Sizing And Control Of Hybrid Rocket Vehicles, Srija Ryakam
Doctoral Dissertations and Master's Theses
In the present work, a genetic algorithm is used to optimize a hybrid rocket engine in order to minimize the propellant required for a specific mission. In a hybrid rocket engine, the mass flow rate of the oxidizer can be throttled to enhance the performance of the rocket. First, an analysis of the internal ballistics and the ascent trajectory has been carried out for different mass flow rates of the oxidizer as a function of time, for a fixed amount of oxidizer, in order to study the effect of throttling. Two equivalent problems are considered: in the first problem the …
Sufficient Conditions For Optimal Control Problems With Terminal Constraints And Free Terminal Times With Applications To Aerospace, Sankalp Kishan Bhan
Sufficient Conditions For Optimal Control Problems With Terminal Constraints And Free Terminal Times With Applications To Aerospace, Sankalp Kishan Bhan
McKelvey School of Engineering Theses & Dissertations
Motivated by the flight control problem of designing control laws for a Ground Collision Avoidance System (GCAS), this thesis formulates sufficient conditions for a strong local minimum for a terminally constrained optimal control problem with a free-terminal time. The conditions develop within the framework of a construction of a field of extremals by means of the method of characteristics, a procedure for the solution of first-order linear partial differential equations, but modified to apply to the Hamilton-Jacobi-Bellman equation of optimal control. Additionally, the thesis constructs these sufficient conditions for optimality with a mathematically rigorous development. The proof uses an approach …
A Radial Basis Function Method For Solving Optimal Control Problems., Hossein Mirinejad
A Radial Basis Function Method For Solving Optimal Control Problems., Hossein Mirinejad
Electronic Theses and Dissertations
This work presents two direct methods based on the radial basis function (RBF) interpolation and arbitrary discretization for solving continuous-time optimal control problems: RBF Collocation Method and RBF-Galerkin Method. Both methods take advantage of choosing any global RBF as the interpolant function and any arbitrary points (meshless or on a mesh) as the discretization points. The first approach is called the RBF collocation method, in which states and controls are parameterized using a global RBF, and constraints are satisfied at arbitrary discrete nodes (collocation points) to convert the continuous-time optimal control problem to a nonlinear programming (NLP) problem. The …
Optimization Based Control Design Techniques For Distributed Parameter Systems, Manoj Kumar
Optimization Based Control Design Techniques For Distributed Parameter Systems, Manoj Kumar
Doctoral Dissertations
"The study presents optimization based control design techniques for the systems that are governed by partial differential equations. A control technique is developed for systems that are actuated at the boundary. The principles of dynamic inversion and constrained optimization theory are used to formulate a feedback controller. This control technique is demonstrated for heat equations and thermal convection loops. This technique is extended to address a practical issue of parameter uncertainty in a class of systems. An estimator is defined for unknown parameters in the system. The Lyapunov stability theory is used to derive an update law of these parameters. …
A New State Observer And Flight Control Of Highly Maneuverable Aircraft, S. N. Balakrishnan, Ming Xin
A New State Observer And Flight Control Of Highly Maneuverable Aircraft, S. N. Balakrishnan, Ming Xin
Mechanical and Aerospace Engineering Faculty Research & Creative Works
In this paper, a new nonlinear observer (θ-D observer) is proposed to estimate the feedback states for optimal control of a highly maneuverable aircraft. This observer is derived by constructing the dual of a recently developed nonlinear optimal control technique-known as the θ-D technique. The θ-D optimal control approach provides an approximate closed-form solution to the Hamilton-Jacobi-Bellman (HJB) equation. An optimal flight controller using this technique is designed for a highly maneuverable aircraft operating at high angle of attack where the θ-D observer is employed to estimate the states for feedback. The structure of this observer is similar to the …
Optimal Neuro-Controller Synthesis For Variable-Time Impulse Driven Systems, Xiaohua Wang, S. N. Balakrishnan
Optimal Neuro-Controller Synthesis For Variable-Time Impulse Driven Systems, Xiaohua Wang, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
This paper develops a systematic scheme to solve for the optimal controls of variable time impulsive systems. First, the optimality conditions for variable time impulse driven systems are derived using the calculus of variation. After wards, a neural network based adaptive critic method is proposed to numerically solve the two-point boundary value problems formulated based on the optimality conditions derived. Finally, two examples - one linear and one nonlinear - are presented to illustrate the conditions derived and to show the power of the neural network based adaptive critic method proposed.
Optimal Controller Synthesis Of Variable-Time Impulsive Problems Using Single Network Adaptive Critics, Xiaohua Wang, S. N. Balakrishnan
Optimal Controller Synthesis Of Variable-Time Impulsive Problems Using Single Network Adaptive Critics, Xiaohua Wang, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
This paper presents a systematic approach to solve for the optimal control of a variable-time impulsive system. First, optimality condition for a variable-time impulsive system is derived using the calculus of variations method. Next, a single network adaptive critic technique is proposed to numerically solve for the optimal control and the detailed algorithm is presented. Finally, two examples-one linear and one nonlinear-are solved applying the conditions derived and the algorithm proposed. Numerical results demonstrate the power of the neural network based adaptive critic method in solving this class of problems.
Weighting Matrix Design For Robust Monotonic Convergence In Norm Optimal Iterative Learning Control, Douglas A. Bristow
Weighting Matrix Design For Robust Monotonic Convergence In Norm Optimal Iterative Learning Control, Douglas A. Bristow
Mechanical and Aerospace Engineering Faculty Research & Creative Works
In this paper we examine the robustness of norm optimal ILC with quadratic cost criterion for discrete-time, linear time-invariant, single-input single-output systems. A bounded multiplicative uncertainty model is used to describe the uncertain system and a sufficient condition for robust monotonic convergence is developed. We find that, for sufficiently large uncertainty, the performance weighting can not be selected arbitrarily large, and thus overall performance is limited. To maximize available performance, a time-frequency design methodology is presented to shape the weighting matrix based on the initial tracking error. The design is applied to a nanopositioning system and simulation results are presented.
Optimal Control Of Class Of Non-Linear Plants Using Artificial Immune Systems: Application Of The Clonal Selection Algorithm, S. A. Panimadai Ramaswamy, Ganesh K. Venayagamoorthy, S. N. Balakrishnan
Optimal Control Of Class Of Non-Linear Plants Using Artificial Immune Systems: Application Of The Clonal Selection Algorithm, S. A. Panimadai Ramaswamy, Ganesh K. Venayagamoorthy, S. N. Balakrishnan
Electrical and Computer Engineering Faculty Research & Creative Works
The function of natural immune system is to protect the living organisms against invaders/pathogens. Artificial Immune System (AIS) is a computational intelligence paradigm inspired by the natural immune system. Diverse engineering problems have been solved in the recent past using AIS. Clonal selection is one of the few algorithms that belong to the family of AIS techniques. Clonal selection algorithm is the computational implementation of the clonal selection principle. The process of affinity maturation of the immune system is explicitly incorporated in this algorithm. This paper presents the application of AIS for the optimal control of a class of non-linear …
Robust/Optimal Temperature Profile Control Of A High-Speed Aerospace Vehicle Using Neural Networks, Vivek Yadav, Radhakant Padhi, S. N. Balakrishnan
Robust/Optimal Temperature Profile Control Of A High-Speed Aerospace Vehicle Using Neural Networks, Vivek Yadav, Radhakant Padhi, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. a 1-D distributed parameter model of a fin is developed from basic thermal physics principles. ldquoSnapshotrdquo solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the ldquoproper orthogonal decompositionrdquo (POD) technique and the snapshot solutions. a low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. an ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a …
Near Optimal Output-Feedback Control Of Nonlinear Discrete-Time Systems In Nonstrict Feedback Form With Application To Engines, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Near Optimal Output-Feedback Control Of Nonlinear Discrete-Time Systems In Nonstrict Feedback Form With Application To Engines, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
A novel reinforcement-learning based output-adaptive neural network (NN) controller, also referred as the adaptive-critic NN controller, is developed to track a desired trajectory for a class of complex nonlinear discrete-time systems in the presence of bounded and unknown disturbances. The controller includes an observer for estimating states and the outputs, critic, and two action NNs for generating virtual, and actual control inputs. The critic approximates certain strategic utility function and the action NNs are used to minimize both the strategic utility function and their outputs. All NN weights adapt online towards minimization of a performance index, utilizing gradient-descent based rule. …
Optimal Neuro-Controller Synthesis For Impulse-Driven System, Xiaohua Wang, S. N. Balakrishnan
Optimal Neuro-Controller Synthesis For Impulse-Driven System, Xiaohua Wang, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
This paper presents a new controller design technique for systems driven with impulse inputs. Necessary conditions for optimal impulse control are derived. A neural network structure to solve the resulting equations is presented. The solution concepts are illustrated with a few example problems that exhibit increasing levels of difficulty. Two linear problems-one scalar and one vector-and a benchmark nonlinear problem-Van Der Pol oscillator-are used as case studies. Numerical results show the efficacy of the new solution process for impulse driven systems. Since the theoretical development and the design technique are free from restrictive assumptions, this technique is applicable to many …
Optimal Impulse Control Of Systems With Control Constraints And Application To Hiv Treatment, Vivek Yadav, S. N. Balakrishnan
Optimal Impulse Control Of Systems With Control Constraints And Application To Hiv Treatment, Vivek Yadav, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
In this paper, conditions for optimal impulse control of an impulsive system with constraints on control are derived. These hold for a system whose states can be changed instantaneously at discrete times with impulses while a continuous control is being applied between those times. The conditions derived are applied to the problem of optimal HIV treatment. Simulation results are presented to show the treatment procedure. The results obtained show that the intervention method developed leads to good results.
Optimal Management Of Beaver Population Using A Reduced-Order Distributed Parameter Model And Single Network Adaptive Critics, Radhakant Padhi, S. N. Balakrishnan
Optimal Management Of Beaver Population Using A Reduced-Order Distributed Parameter Model And Single Network Adaptive Critics, Radhakant Padhi, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Beavers are often found to be in conflict with human interests by creating nuisances like building dams on flowing water (leading to flooding), blocking irrigation canals, cutting down timbers, etc. At the same time they contribute to raising water tables, increased vegetation, etc. Consequently, maintaining an optimal beaver population is beneficial. Because of their diffusion externality (due to migratory nature), strategies based on lumped parameter models are often ineffective. Using a distributed parameter model for beaver population that accounts for their spatial and temporal behavior, an optimal control (trapping) strategy is presented in this paper that leads to a desired …
An Optimal Dynamic Inversion Approach For Controlling A Class Of One-Dimensional Nonlinear Distributed Parameter Systems, Radhakant Padhi, S. N. Balakrishnan
An Optimal Dynamic Inversion Approach For Controlling A Class Of One-Dimensional Nonlinear Distributed Parameter Systems, Radhakant Padhi, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Combining the principles of dynamic inversion and optimization theory, a new approach is presented for stable control of a class of one-dimensional nonlinear distributed parameter systems, assuming the availability a continuous actuator in the spatial domain. Unlike the existing approximate-then-design and design-then-approximate techniques, here there is no need of any approximation either of the system dynamics or of the resulting controller. Rather, the control synthesis approach is fairly straight-forward and simple. The controller formulation has more elegance because we can prove the convergence of the controller to its steady state value. To demonstrate the potential of the proposed technique, a …
Hierarchical Optimal Force-Position-Contour Control Of Machining Processes. Part I. Controller Methodology, Yan Tang, Robert G. Landers, S. N. Balakrishnan
Hierarchical Optimal Force-Position-Contour Control Of Machining Processes. Part I. Controller Methodology, Yan Tang, Robert G. Landers, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
There has been a tremendous amount of research in machine tool servomechanism control, contour control, and machining force control; however, to date these technologies have not been tightly integrated. This paper develops a hierarchical optimal control methodology for the simultaneous regulation of servomechanism positions, contour error, and machining forces. The contour error and machining force process reside in the top level of the hierarchy where the goals are to 1) drive the contour error to zero to maximize quality and 2) maintain a constant cutting force to maximize productivity. These goals are systematically propagated to the bottom level, via aggregation …
Hierarchical Optimal Force-Position-Contour Control Of Machining Processes. Part Ii. Illustrative Example, Yan Tang, Robert G. Landers, S. N. Balakrishnan
Hierarchical Optimal Force-Position-Contour Control Of Machining Processes. Part Ii. Illustrative Example, Yan Tang, Robert G. Landers, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
There has been a tremendous amount of research in machine tool servomechanism control, contour control, and machining force control; however, to date these technologies have not been tightly integrated. This paper develops a hierarchical optimal control methodology for the simultaneous regulation of servomechanism positions, contour error, and machining forces. The contour error and machining force process reside in the top level of the hierarchy where the goals are to 1) drive the contour error to zero to maximize quality and 2) maintain a constant cutting force to maximize productivity. These goals are systematically propagated to the bottom level, via aggregation …
Optimal And Hierarchical Formation Control For Uav, Xiaohua Wang, S. N. Balakrishnan
Optimal And Hierarchical Formation Control For Uav, Xiaohua Wang, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
In this paper, optimal and hierarchical control concepts are investigated for cooperative formation flying of aircrafts. The airplanes are modeled as point mass and represented by double integrators. And all the planes are considered to be in a plane. For demonstration of the concepts, a task of forming a square from arbitrary initial conditions is presented to four airplanes. The final position that each airplane has to reach is unknown to them. The goal for the team is abstracted in the top layer. The system is modeled as a two layer hierarchical system in which the global information comes from …
Optimal Control Of A Class Of One-Dimensional Nonlinear Distributed Parameter Systems With Discrete Actuators, Radhakant Padhi, S. N. Balakrishnan
Optimal Control Of A Class Of One-Dimensional Nonlinear Distributed Parameter Systems With Discrete Actuators, Radhakant Padhi, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Combining the principles of dynamic inversion and optimization theory, a new approach is presented for stable control of a class of one-dimensional nonlinear distributed parameter systems with a finite number of actuators in the spatial domain. Unlike the existing ''approximate-then-design'' and ''design-then-approximate'' techniques, this approach does not use any approximation either of the system dynamics or of the resulting controller. The formulation has more practical significance because one can implement a set of discrete controllers with relative ease. To demonstrate the potential of the proposed technique, a real-life temperature control problem for a heat transfer application is solved through simulations. …
Hierarchical Optimal Force-Position Control Of A Turning Process, B. Pandurangan, Robert G. Landers, S. N. Balakrishnan
Hierarchical Optimal Force-Position Control Of A Turning Process, B. Pandurangan, Robert G. Landers, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Machining process control technologies are currently not well integrated into machine tool controllers and, thus, servomechanism dynamics are often ignored when designing and implementing process controllers. In this brief, a hierarchical controller is developed that simultaneously regulates the servomechanism motions and cutting forces in a turning operation. The force process and servomechanism system are separated into high and low levels, respectively, in the hierarchy. The high-level goal is to maintain a constant cutting force to maximize productivity while not violating a spindle power constraint. This goal is systematically propagated to the lower level and combined with the low-level goal to …
Development And Analysis Of A Feedback Treatment Strategy For Parturient Paresis Of Cows, Radhakant Padhi, S. N. Balakrishnan
Development And Analysis Of A Feedback Treatment Strategy For Parturient Paresis Of Cows, Radhakant Padhi, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
An intelligent on-line feedback treatment strategy based on nonlinear optimal control theory is presented for the parturient paresis of cows. A limitation in the development of an existing nonlinear mathematical model for the homogeneous system is addressed and further modified to incorporate a control input. A neural network based optimal feedback controller is synthesized for the treatment of the disease. Detailed studies are used to analyze the effectiveness of a feedback medication strategy and it is compared with the current "impulse" strategy. The results show that while the current practice may fail in some cases, especially if it is carried …
Optimal Beaver Population Management Using Reduced Order Distributed Parameter Model And Single Network Adaptive Critics, Radhakant Padhi, S. N. Balakrishnan
Optimal Beaver Population Management Using Reduced Order Distributed Parameter Model And Single Network Adaptive Critics, Radhakant Padhi, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Using a distributed parameter model for beaver population that accounts for their spatial and temporal behavior, an optimal control for a desired distribution of the animals is presented. Optimal solutions are obtained through a "single network adaptive critic" (SNAC) neural network architecture. The objective of this research is to design an "optimal" beaver harvesting scheme for a region of interest.
Optimal Control Synthesis Of A Class Of Nonlinear Systems Using Single Network Adaptive Critics, Radhakant Padhi, Nishant Unnikrishnan, S. N. Balakrishnan
Optimal Control Synthesis Of A Class Of Nonlinear Systems Using Single Network Adaptive Critics, Radhakant Padhi, Nishant Unnikrishnan, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Adaptive critic (AC) neural network solutions to optimal control designs using dynamic programming has reduced the need of complex computations and storage requirements that typical dynamic programming requires. In this paper, a "single network adaptive critic" (SNAC) is presented. This approach is applicable to a class of nonlinear systems where the optimal control (stationary) equation is explicitly solvable for control in terms of state and costate variables. The SNAC architecture offers three potential advantages; a simpler architecture, significant savings of computational load and reduction in approximation errors. In order to demonstrate these benefits, a real-life micro-electro-mechanical-system (MEMS) problem has been …
Development And Implementation Of New Nonlinear Control Concepts For A Ua, Vijayakumar Janardhan, Derek Schmitz, S. N. Balakrishnan
Development And Implementation Of New Nonlinear Control Concepts For A Ua, Vijayakumar Janardhan, Derek Schmitz, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
A reconfigurable flight control method is developed to be implemented on an Unmanned Aircraft (UA), a thirty percent scale model of the Cessna 150. This paper presents the details of the UAV platform, system identification, reconfigurable controller design, development, and implementation on the UA to analyze the performance metrics. A Crossbow Inertial Measurement Unit provides the roll, pitch and yaw accelerations and rates along with the roll and pitch. The 100400 mini-air data boom from spaceage control provides the airspeed, altitude, angle of attack and the side slip angles. System identification is accomplished by commanding preprogrammed inputs to the control …
Hierarchical Optimal Control Of A Turning Process - Linearization Approach, Anand Dasgupta, B. Pandurangan, Robert G. Landers, S. N. Balakrishnan
Hierarchical Optimal Control Of A Turning Process - Linearization Approach, Anand Dasgupta, B. Pandurangan, Robert G. Landers, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Machining process control technologies are currently not well integrated into machine tool controllers and, thus, servomechanism dynamics are often ignored when designing and implementing process controllers. In this paper, a hierarchical controller is developed that simultaneously regulates the servomechanism positions and cutting forces in a lathing operation. The force process and servomechanism system are separated into high and low levels, respectively, in the hierarchy. The high level goal is to maintain a constant cutting force to maximize productivity while not violating a spindle power constraint. This goal is systematically propagated to the lower level and combined with the low level …
Proper Orthogonal Decomposition Based Modeling And Experimental Implementation Of A Neurocontroller For A Heat Diffusion System, Prashant Prabhat, S. N. Balakrishnan, Dwight C. Look, Radhakant Padhi
Proper Orthogonal Decomposition Based Modeling And Experimental Implementation Of A Neurocontroller For A Heat Diffusion System, Prashant Prabhat, S. N. Balakrishnan, Dwight C. Look, Radhakant Padhi
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Experimental implementation of a dual neural network based optimal controller for a heat diffusion system is presented. Using the technique of proper orthogonal decomposition (POD), a set of problem-oriented basis functions are designed taking the experimental data as snap shot solutions. Using these basis functions in Galerkin projection, a reduced-order analogous lumped parameter model of the distributed parameter system is developed. This model is then used in an analogous lumped parameter problem. A dual neural network structure called adaptive critics is used to obtain optimal neurocontrollers for this system. In this structure, one set of neural networks captures the relationship …
Approximate Dynamic Programming Based Optimal Neurocontrol Synthesis Of A Chemical Reactor Process Using Proper Orthogonal Decomposition, Radhakant Padhi, S. N. Balakrishnan
Approximate Dynamic Programming Based Optimal Neurocontrol Synthesis Of A Chemical Reactor Process Using Proper Orthogonal Decomposition, Radhakant Padhi, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
The concept of approximate dynamic programming and adaptive critic neural network based optimal controller is extended in this study to include systems governed by partial differential equations. An optimal controller is synthesized for a dispersion type tubular chemical reactor, which is governed by two coupled nonlinear partial differential equations. It consists of three steps: First, empirical basis functions are designed using the "Proper Orthogonal Decomposition" technique and a low-order lumped parameter system to represent the infinite-dimensional system is obtained by carrying out a Galerkin projection. Second, approximate dynamic programming technique is applied in a discrete time framework, followed by the …
Nonlinear H Infinity Missile Longitudinal Autopilot Design With Θ-D Method, Ming Xin, S. N. Balakrishnan
Nonlinear H Infinity Missile Longitudinal Autopilot Design With Θ-D Method, Ming Xin, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
In this paper, a new nonlinear control synthesis technique, the theta- D method, is employed to design a missile longitudinal autopilot. The θ-D technique yields suboptimal solutions to nonlinear optimal control problems in the sense that it provides approximate solution to the Hamilton-Jacobi-Bellman (HJB) equation. Semi-global asymptotic stability can be achieved by manipulating the perturbation terms which are added to the cost function in developing a series solution. Furthermore, this method can be used to provide an approximate closed-form solution to the state dependent Riccati equation. The particular θ-D methodology adopted in this paper is referred to as θ-D H …