Wassim Haddad | Georgia Institute of Technology (original) (raw)
Papers by Wassim Haddad
Impulsive and Hybrid Dynamical Systems, 2006
2018 Annual American Control Conference (ACC), 2018
In this paper, we present a Lyapunov function-based optimization approach for designing state and... more In this paper, we present a Lyapunov function-based optimization approach for designing state and output feedback control laws for systems with polynomial nonlinearities. We use local polynomial expansions of a chosen order to approximate a higher-order nonlinear stochastic dynamical system, reformulate stochastic asymptotic stability conditions in the form of a nonlinear constrained optimization problem, and computationally determine the domain of attraction of the synthesized nonlinear controller on the original system. Finally, we illustrate the effectiveness of the proposed algorithm on two illustrative numerical examples.
Nonnegative and Compartmental Dynamical Systems, 2010
Nonnegative and Compartmental Dynamical Systems, 2010
Nonnegative and Compartmental Dynamical Systems, 2010
Mathematics, Feb 22, 2024
Systems & Control Letters
2021 60th IEEE Conference on Decision and Control (CDC), 2021
In this paper, we investigate the role of Lyapunov functions in evaluating nonlinear-nonquadratic... more In this paper, we investigate the role of Lyapunov functions in evaluating nonlinear-nonquadratic cost functionals for Ito-type nonlinear stochastic difference equations. Specifically, it is shown that the cost functional can be evaluated in closed-form as long as the cost functional is related in a specific way to an underlying Lyapunov function that guarantees asymptotic stability in probability. This result is then used to analyze discrete-time linear stochastic systems as well as nonlinear stochastic dynamical systems with polynomial and multilinear cost functionals.
2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012
ABSTRACT The laws of thermodynamics define the concepts of thermal equilibrium and thermal energy... more ABSTRACT The laws of thermodynamics define the concepts of thermal equilibrium and thermal energy, and determine whether a particular transfer of thermal energy can occur. Collectively, these laws imply that a closed collection of thermodynamic subsystems will tend to energy equipartition. That is, the system will tend towards a condition where energy is evenly distributed over all subsystems. Applied to conductive heat transfer in a connected network of lumped thermal masses, the laws of thermodynamics imply that the system will approach thermal equilibrium. This paper generalizes the concepts of energy and entropy to undirected and directed networks of single integrators, and demonstrates how thermodynamic principles embodied by the laws of conductive heat transfer may be applied to the design of distributed consensus control algorithms for networked dynamic systems.
2020 American Control Conference (ACC), 2020
In this paper, we develop distributed output feedback adaptive consensus control protocols for ad... more In this paper, we develop distributed output feedback adaptive consensus control protocols for addressing networked multiagent systems subject to exogenous stochastic disturbances and sensor and actuators attacks. Specifically, for a class of linear leader-follower multiagent systems with an undirected communication graph topology we develop an output feedback adaptive control design protocol for each follower agent to address malicious attacks on the actuator signals of the follower agents as well as sensor attacks on the output neighborhood synchronization errors measurements. The proposed adaptive controllers involve an indirect adaptive architecure that estimates and compensates for the malicious attacks while guaranteeing uniform ultimate boundedness of the state tracking error for each agent in a mean-square sense.
2018 Annual American Control Conference (ACC), 2018
In this paper, we develop an energy-based static and dynamic control framework for stochastic por... more In this paper, we develop an energy-based static and dynamic control framework for stochastic port-controlled Hamiltonian systems. In particular, we obtain constructive sufficient conditions for stochastic feedback stabilization that provide a shaped energy function for the closed-loop system while preserving a Hamiltonian structure at the closed-loop level. In the dynamic control case, energy shaping is achieved by combining the physical energy of the plant and the emulated energy of the controller.
International Journal of Sustainable Engineering
arXiv (Cornell University), Aug 10, 2015
2019 American Control Conference (ACC), 2019
In this paper, we develop partial dissipativity theory for nonlinear dynamical systems using basi... more In this paper, we develop partial dissipativity theory for nonlinear dynamical systems using basic input-output and state properties. Specifically, partial dissipativity is characterized using both an input-output as well as a state dissipation inequality involving a partial storage function that is nonnegative definite with respect to part of the system state. The results are then used to derive Kalman-Yakubovich-Popov conditions for characterizing necessary and sufficient conditions for partial dissipativity of nonlinear dynamical systems using continuously differentiable partial storage functions that are nonnegative definite with respect to part of the systems state. In addition, feedback interconnection partial stability results for nonlinear dynamical systems are developed thereby providing a generalization of the small gain and positivity theorems for guaranteeing partial stability of feedback systems.
2018 Annual American Control Conference (ACC), 2018
Due to advances in embedded computational resources over the last several years, a considerable r... more Due to advances in embedded computational resources over the last several years, a considerable research effort has been devoted to the control of networks and control over networks. Network systems involve distributed decision-making for coordination of networks of dynamic agents and address a broad area of applications including cooperative control of unmanned air vehicles, microsatellite clusters, mobile robotics, battle space management, and congestion control in communication networks. In this paper, we develop a conservation-based framework for addressing almost sure consensus problems for nonlinear stochastic multiagent dynamical systems with fixed communication topologies. Specifically, we present a distributed nonlinear controller architectures for multiagent coordination over networks with state-dependent stochastic communication uncertainty. The proposed controller architecture involves the exchange of generalized charge or energy between agents guaranteeing that the closed-loop dynamical network is stochastically semistable to an equipartitioned equilibrium representing a state of almost sure consensus consistent with basic thermodynamic principles.
2016 American Control Conference (ACC), 2016
In this paper, we develop stochastic dissipativity notions for stochastic dynamical systems using... more In this paper, we develop stochastic dissipativity notions for stochastic dynamical systems using basic input-output and state properties. Specifically, a stochastic version of dissipativity using both an input-output as well as a state dissipation inequality for controlled Markov diffusion processes is presented. The results are then used to derive extended Kalman-Yakubovich-Popov conditions for characterizing necessary and sufficient conditions for stochastic dissipativity of stochastic systems using two-times continuously differentiable storage functions.
Impulsive and Hybrid Dynamical Systems, 2006
2018 Annual American Control Conference (ACC), 2018
In this paper, we present a Lyapunov function-based optimization approach for designing state and... more In this paper, we present a Lyapunov function-based optimization approach for designing state and output feedback control laws for systems with polynomial nonlinearities. We use local polynomial expansions of a chosen order to approximate a higher-order nonlinear stochastic dynamical system, reformulate stochastic asymptotic stability conditions in the form of a nonlinear constrained optimization problem, and computationally determine the domain of attraction of the synthesized nonlinear controller on the original system. Finally, we illustrate the effectiveness of the proposed algorithm on two illustrative numerical examples.
Nonnegative and Compartmental Dynamical Systems, 2010
Nonnegative and Compartmental Dynamical Systems, 2010
Nonnegative and Compartmental Dynamical Systems, 2010
Mathematics, Feb 22, 2024
Systems & Control Letters
2021 60th IEEE Conference on Decision and Control (CDC), 2021
In this paper, we investigate the role of Lyapunov functions in evaluating nonlinear-nonquadratic... more In this paper, we investigate the role of Lyapunov functions in evaluating nonlinear-nonquadratic cost functionals for Ito-type nonlinear stochastic difference equations. Specifically, it is shown that the cost functional can be evaluated in closed-form as long as the cost functional is related in a specific way to an underlying Lyapunov function that guarantees asymptotic stability in probability. This result is then used to analyze discrete-time linear stochastic systems as well as nonlinear stochastic dynamical systems with polynomial and multilinear cost functionals.
2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012
ABSTRACT The laws of thermodynamics define the concepts of thermal equilibrium and thermal energy... more ABSTRACT The laws of thermodynamics define the concepts of thermal equilibrium and thermal energy, and determine whether a particular transfer of thermal energy can occur. Collectively, these laws imply that a closed collection of thermodynamic subsystems will tend to energy equipartition. That is, the system will tend towards a condition where energy is evenly distributed over all subsystems. Applied to conductive heat transfer in a connected network of lumped thermal masses, the laws of thermodynamics imply that the system will approach thermal equilibrium. This paper generalizes the concepts of energy and entropy to undirected and directed networks of single integrators, and demonstrates how thermodynamic principles embodied by the laws of conductive heat transfer may be applied to the design of distributed consensus control algorithms for networked dynamic systems.
2020 American Control Conference (ACC), 2020
In this paper, we develop distributed output feedback adaptive consensus control protocols for ad... more In this paper, we develop distributed output feedback adaptive consensus control protocols for addressing networked multiagent systems subject to exogenous stochastic disturbances and sensor and actuators attacks. Specifically, for a class of linear leader-follower multiagent systems with an undirected communication graph topology we develop an output feedback adaptive control design protocol for each follower agent to address malicious attacks on the actuator signals of the follower agents as well as sensor attacks on the output neighborhood synchronization errors measurements. The proposed adaptive controllers involve an indirect adaptive architecure that estimates and compensates for the malicious attacks while guaranteeing uniform ultimate boundedness of the state tracking error for each agent in a mean-square sense.
2018 Annual American Control Conference (ACC), 2018
In this paper, we develop an energy-based static and dynamic control framework for stochastic por... more In this paper, we develop an energy-based static and dynamic control framework for stochastic port-controlled Hamiltonian systems. In particular, we obtain constructive sufficient conditions for stochastic feedback stabilization that provide a shaped energy function for the closed-loop system while preserving a Hamiltonian structure at the closed-loop level. In the dynamic control case, energy shaping is achieved by combining the physical energy of the plant and the emulated energy of the controller.
International Journal of Sustainable Engineering
arXiv (Cornell University), Aug 10, 2015
2019 American Control Conference (ACC), 2019
In this paper, we develop partial dissipativity theory for nonlinear dynamical systems using basi... more In this paper, we develop partial dissipativity theory for nonlinear dynamical systems using basic input-output and state properties. Specifically, partial dissipativity is characterized using both an input-output as well as a state dissipation inequality involving a partial storage function that is nonnegative definite with respect to part of the system state. The results are then used to derive Kalman-Yakubovich-Popov conditions for characterizing necessary and sufficient conditions for partial dissipativity of nonlinear dynamical systems using continuously differentiable partial storage functions that are nonnegative definite with respect to part of the systems state. In addition, feedback interconnection partial stability results for nonlinear dynamical systems are developed thereby providing a generalization of the small gain and positivity theorems for guaranteeing partial stability of feedback systems.
2018 Annual American Control Conference (ACC), 2018
Due to advances in embedded computational resources over the last several years, a considerable r... more Due to advances in embedded computational resources over the last several years, a considerable research effort has been devoted to the control of networks and control over networks. Network systems involve distributed decision-making for coordination of networks of dynamic agents and address a broad area of applications including cooperative control of unmanned air vehicles, microsatellite clusters, mobile robotics, battle space management, and congestion control in communication networks. In this paper, we develop a conservation-based framework for addressing almost sure consensus problems for nonlinear stochastic multiagent dynamical systems with fixed communication topologies. Specifically, we present a distributed nonlinear controller architectures for multiagent coordination over networks with state-dependent stochastic communication uncertainty. The proposed controller architecture involves the exchange of generalized charge or energy between agents guaranteeing that the closed-loop dynamical network is stochastically semistable to an equipartitioned equilibrium representing a state of almost sure consensus consistent with basic thermodynamic principles.
2016 American Control Conference (ACC), 2016
In this paper, we develop stochastic dissipativity notions for stochastic dynamical systems using... more In this paper, we develop stochastic dissipativity notions for stochastic dynamical systems using basic input-output and state properties. Specifically, a stochastic version of dissipativity using both an input-output as well as a state dissipation inequality for controlled Markov diffusion processes is presented. The results are then used to derive extended Kalman-Yakubovich-Popov conditions for characterizing necessary and sufficient conditions for stochastic dissipativity of stochastic systems using two-times continuously differentiable storage functions.