Sankrith Subramanian

Robust nonlinear aircraft tracking control using synthetic jet actuators

A robust, nonlinear tracking control strategy is presented for an aircraft equipped with synthetic jet actuators (SJA). The control law is designed to be easily implementable, requiring no observers, function approximators, or adaptive laws. By exploiting minimal knowledge of the structure of the nonlinear SJA dynamic model, a matrix decomposition technique is exploited to compensate for the input-multiplicative parametric uncertainty inherent in the SJA dynamics. The control law is shown to yield global asymptotic trajectory tracking in the presence of parametric uncertainty, actuator nonlinearity, and unknown, nonlinear external disturbances. A rigorous Lyapunov-based stability analysis is utilized to prove the theoretical result, and numerical simulation results are provided to demonstrate the performance of the proposed control law.

Nonlinear Control of Hypersonic Missiles for Maximum Target Penetration

The design of guidance and control laws for missiles traveling at hypersonic speeds is an inherently challenging task due to the fact that the system dynamics are nonlinear and highly coupled. An even more challenging task is the design of guidance laws for hypersonic missiles, which incorporates the terminal conditions to maximize target penetration. In this research, nonlinear control techniques are combined with optimal control methods to develop guidance and control laws for air-breathing hypersonic missiles in the presence of system uncertainty and external disturbances. One of the contributions of this research is detailed theoretical analysis of the performance characteristics of the proposed control design. Moreover, by including terminal constraints in the cost function, target penetration is maximized. Specifically, by minimizing angle of attack (AoA) and inertial angle of obliquity (AoO) at impact, maximum target penetration is achieved. Lyapunov-based stability analysis is utilized to prove the theoretical result, and high-fidelity numerical simulation results are provided to verify the practical performance of the proposed guidance law design.

Power control for cellular communications with channel uncertainties

In the reverse link of a wireless cellular network, power control is used to ensure that each link achieves its target signal-to-interference-plus-noise ratio (SINR), while minimizing the interference to adjacent cells. In cellular systems using direct-sequence code-division multiple access (CDMA), the SINR depends inversely on the power assigned to the other users in the system, creating a nonlinear control problem. Mobility of the terminals, along with associated random shadowing and multi-path fading, results in uncertainty in the channel state. A regulation controller is developed in this paper for a CDMA cellular system with uncertainties in the state and channel noise. The developed controller regulates the SINR to a small region about a target value. An analysis is also provided to examine how mobility and the desired SINR regulation range affects the choice of channel update times.

Vision based connectivity maintenance of a network with switching topology

Networks of cooperating agents are investigated for formation and coverage control, target tracking, flocking, and consensus applications. Within these applications, agents are required to coordinate to make appropriate decisions and achieve desired goals; hence, the ability to maintain connectivity with other agents is paramount. In this paper, we propose a two level control framework for connectivity maintenance and cooperation of multi-agent systems. Each agent is equipped with an omnidirectional camera and wireless communication capabilities. Image feedback is the primary method to maintain connectivity among agents with wireless communication that is only used to broadcast information when a specific topology change occurs. All agents in the team are categorized as clusterheads or regular nodes. A high level graph is composed of all clusterheads and the motion of the clusterheads is controlled to maintain existing connections among them. A low level graph composed of all regular nodes is controlled to maintain connectivity with respect its specific clusterhead.

Stabilizing a nonlinear model-based networked control system with communication constraints

In this paper, a class of nonlinear networked control systems (NCS) operating over a shared-channel are considered. For sensor networks and networks requiring information collaboration among various devices, the objective to reduce contention and use the bandwidth limited network resources more efficiently can be achieved by developing “smart” sensors. Model-based control and event-based triggering can be fused such that smart sensors determine the “value of information” for stable operation of control systems. A context-aware feedback policy can be developed for a class of nonlinear NCS based on the informational value of sensor measurements that minimizes network usage or traffic. The developed aperiodic feedback policy guarantees global asymptotic tracking of output states of an uncertain system along the desired time-varying trajectory. A direct adaptive parameter update law is formulated to estimate the uncertain system dynamics that can further reduce feedback requirements. A piecewise continuous tracking controller is developed and validated using extensive simulation results for nonlinear scalar and coupled MIMO systems.

Continuous congestion control for Differentiated-Services networks?

Network traffic in the transport layer of end-to-end congestion networks plays a vital role in effecting the throughput in the Medium Access Control (MAC) layer. Common queue length management techniques on nodes in such networks focus on servicing the packets based on their Quality of Service (QoS) requirements (e.g., Differentiated-Services, or DiffServ, networks). In this paper, a continuous control strategy is suggested for a DiffServ network to track the desired ensemble average queue length level specified by the network operator. A Lyapunov-based stability analysis is provided to illustrate global asymptotic tracking, and simulations demonstrate the performance and feasibility of the controller, along with showing global asymptotic tracking of the queue lengths in the Premium Service buffer.

A cross-layer approach to mixed-control topology management for MANETs

Topology Control (TC) algorithms are generally applied to tactical network environments to create or maintain connectivity graphs with specific topological properties. In the context of this work, network topology defines the connectivity and link properties between nodes in the network. While protocols in the communications stack are traditionally designed to adapt to different traffic demands and underlying changes in network topology, TC algorithms offer an opportunity for applications to become proactive, and to drive changes in network topology. In most cases, topology control is achieved through a number of independent control strategies such as power management, node mobility or spectrum allocation, each of which operates at a different time scale, with different constraints and capabilities. In this work we introduce a mixed topology control strategy for highly dynamic tactical networks. The proposed approach combines two controllers (one for transmit power and one for node mobility) to enable a self-regulating link maintenance algorithm that compensates for short term variations in link conditions while supporting a more permanent, slower adaptation based on node position. While applied for transmit power and node mobility in this paper, the approach is generic enough to be extended to different parameters. After describing the control formulation and its stability analysis, we introduce simple leader-follower scenarios simulated in NS-3 to illustrate the capabilities and properties of the proposed approach.

Prediction-based power control for distributed cellular communication networks with time-varying channel uncertainties

Fast changing radio channels in a CDMA based cellular network have detrimental effects on the control efforts required to regulate the Signal to Interference plus Noise ratio (SINR) to the desired level, especially for highly mobile terminals (MTs). The motivation behind introducing a prediction-based power control algorithm is to meet the problems associated with rapid changes in the channel gain (by orders of magnitude between power update intervals) influenced by fading and exacerbated by the MTs coming out of the ‘deep faded’ zone. For a fast fading channel, a reliable prediction of the channel coefficient is required for accurate control design. For this purpose, we propose to use a linear prediction filter to estimate the channel fading parameter, and this information is fed to the controller. The controller uses local SINR measurements from the current and neighboring cells to maintain the SINRs of all the MTs present in the acceptable communication range. A Lyapunov based analysis is provided to explain the bound that the SINR error reaches, the size of which can be reduced by choosing appropriate control gains. The power control algorithm is simulated on a cellular network with distributed cells and the results indicate that the controller regulates the SINRs of all the MTs with low outage probability.

Throughput maximization in CSMA networks with collisions

In the Medium Access Control (MAC) layer of a wireless network that uses Carrier Sense Multiple Access (CSMA), the performance is limited by collisions that occur because of carrier sensing delays associated with propagation and the sensing electronics. In this paper, we use a continuous-time Markov model to analyze and optimize the performance of a system using CSMA with collisions caused by sensing delays. The throughput of the network is quantified using the stationary distribution of the Markov model. An online algorithm is developed for the unconstrained throughput maximization problem. Further, a constrained problem is formulated and solved using a numerical algorithm. Simulations are provided to analyze and validate the solution to the unconstrained and constrained optimization problems.

Throughput Maximization in CSMA Networks with Collisions and Hidden Terminals

The throughput at the medium-access control (MAC) layer in a wireless network, that uses the carrier-sense multiple-access (CSMA) protocol, is degraded by collisions caused by failures of the carrier-sensing mechanism. Two sources of failure in the carrier-sensing mechanism are delays in the carrier sensing mechanism and hidden terminals, in which an ongoing transmission cannot be detected at a terminal that wishes to transmit because the path loss from the active transmitter is large. In this chapter, the effect of these carrier-sensing failures is modeled using a continuous-time Markov model. The throughput of the network is determined using the stationary distribution of the Markov model. The throughput is maximized by finding optimal mean transmission rates for the terminals in the network subject to constraints on successfully transmitting packets at a rate that is at least as great as the packet arrival rate.