Keck Voon Ling

Inverse optimal adaptive control for attitude tracking of spacecraft

The attitude tracking control problem of a rigid spacecraft with external disturbances and an uncertain inertia matrix is addressed using the adaptive control method. The adaptive control laws proposed in this paper are optimal with respect to a family of cost functionals. This is achieved by the inverse optimality approach, without solving the associated Hamilton-Jacobi-Isaacs partial differential (HJIPD) equation directly. The design of the optimal adaptive controllers is separated into two stages by means of integrator backstepping, and a control Lyapunov argument is constructed to show that the inverse optimal adaptive controllers achieve H/sub /spl infin// disturbance attenuation with respect to external disturbances and global asymptotic convergence of tracking errors to zero for disturbances with bounded energy. The convergence of adaptive parameters is also analyzed in terms of invariant manifold. Numerical simulations illustrate the performance of the proposed control algorithms.

Embedded Model Predictive Control (MPC) Using a FPGA

Model Predictive Control (MPC) is increasingly being proposed for application to miniaturized devices, fast and/or embedded systems. A major obstacle to this is its computation time requirement. Continuing our previous studies of implementing constrained MPC on Field Programmable Gate Arrays (FPGA), this paper begins to exploit the possibilities of parallel computation, with the aim of speeding up the MPC implementation. Simulation studies on a realistic example show that it is possible to implement constrained MPC on an FPGA chip with a 25MHz clock and achieve MPC implementation rates comparable to those achievable on a Pentium 3.0 GHz PC.

Receding horizon recursive state estimation

Describes a receding horizon discrete-time state observer using the deterministic least squares framework. The state estimation horizon, which determines the number of past measurement samples used to reconstruct the state vector, is introduced as a tuning parameter for the proposed state observer. A stability result concerning the choice of the state estimation horizon is established. It is also shown that the fixed memory receding horizon state observer can be related to the standard dynamic observer by using an appropriate end-point state weighting on the estimator cost function.

H ∞ Inverse Optimal Attitude-Tracking Control of Rigid Spacecraft

The attitude trajectory tracking control problem for a rigid spacecraft with external disturbances is addressed using the robust inverse optimal-control method. The proposed feedback-control law is optimal with respect to a meaningful cost functional involving tracking errors, control efforts, and extended disturbances, and the associated Lyapunov function satisfies a Hamilton‐Jacobi‐Isaacs partial differential equation. The controller is H∞ optimal with respect to extended disturbances. The performance limitation of the inverse optimal feedback controller is analyzed and guidelines for the selection of the controller gains are established. Numerical simulations are performed to demonstrate the effectiveness of the proposed control algorithm and the tuning guidelines. Nomenclature � A� = induced 2-norm of the matrix A ∈ R n × n , � A �= √ [λmax(A T A)] A T = transpose of A |a| = Euclidean norm of the vectora ∈ R n , |a |= √ (a T a) d, ˆ d =e xternal disturbance and extended disturbance, respectively J = inertia matrix of the spacecraft, J = J T > 0 L f V = Lie derivative of the Lyapunov function V (x) with respect to f (x), L f V = ∂ V (x) ∂ x f (x)

MULTIPLEXED MODEL PREDICTIVE CONTROL

Abstract Most academic control schemes for MIMO systems assume all the control variables are updated simultaneously. MPC outperforms other control strategies through its ability to deal with constraints. This requires on-line optimization, hence computational complexity can become an issue when applying MPC to complex systems with fast response times. The multiplexed MPC scheme described in this paper solves the MPC problem for each subsystem sequentially and updates subsystem controls as soon as the solution is available, thus distributing the control moves over a complete update cycle. The resulting computational speed-up allows faster response to disturbances, and hence improved performance, despite finding sub-optimal solutions to the original problem. The multiplexed MPC scheme is also closer to industrial practice in many cases. This paper presents initial stability results for two variants of multiplexed MPC, and illustrates the performance benefit by an example.

Prostate Boundary Detection From Ultrasonographic Images

Objective. Prostate diseases are very common in adult and elderly men, and prostate boundary detection from ultrasonographic images plays a key role in prostate disease diagnosis and treatment. However, because of the poor quality of ultrasonographic images, prostate boundary detection still remains a challenging task. Currently, this task is performed manually, which is arduous and heavily user dependent. To improve the efficiency by automating the boundary detection process, numerous methods have been proposed. We present a review of these methods, aiming to find a good solution that could efficiently detect the prostate boundary on ultrasonographic images. Methods. A full description of various methods is beyond the scope of this article; instead, we focus on providing an introduction to the different methods with a discussion of their advantages and disadvantages. Moreover, verification methods for estimating the accuracies of the algorithms reported in the literature are discussed as well. Results. From the investigation, we summarize several key issues that might be confronted and project possible future research. Conclusions. Those model‐based methods that minimize user involvement but allow for interactive guidance of experts will likely be most immediately successful.

Brief paper: A state space GPC with extensions to multirate control

A state space formulation for generalized predictive control (GPC) is presented. Unlike other state space formulations, we derive both the state feedback controller and state estimator gains using a least squares framework. The present formulation provides a set of consistent design choices for both the controller and the state estimator design. It also encapsulates both single rate and multirate controllers in the same algorithm. It is argued that such a design approach can be advantageous especially when the control algorithm is required to tolerate sensor failure. The generality of the design method is illustrated by synthesizing two well-known multirate control algorithms. A link with the generalized sampled-data hold function is also established.

Model predictive control on a chip

Model predictive control (MPC) has become an established control technology in the petrochemical industry, and its use is currently being pioneered in an increasingly wide range of process industries. It is also being proposed for a range of higher bandwidth applications, such as ships, aerospace and road vehicles. To extend its applications to miniaturized devices and/or embedded systems, this paper explores the implementation of MPC technology into reconfigurable hardware such as a FPGA chip. A rapid prototyping environment suitable for exploring the various implementation issues to bring MPC onto a chip is described. Simulation tests were conducted to verify the applicability of the UMPC on a chip idea. It is shown that a modest FPGA chip could he used to implement a reasonably sized constrained MPC controller.

Low cost SINS/GPS integration for land vehicle navigation

The recent progress in the field of micro-electromechanical systems (MEMS) has made low cost inertial devices become a possible option for land navigation. However, the weak stand-alone accuracy and poor run-to-run stability of low cost inertial devices make them not usable as a sole navigation system. Even the integration of them as a supporting device into a navigation system requires non-traditional approaches and algorithms. The objective of this paper is to assess the feasibility of using this kind of low cost inertial device, specifically the Crossbow DMU-6X, integrated with GPS information, to provide the navigation capability to bridge the GPS outages for tens of seconds. A series of tests were conducted in a land vehicle. Post-processing results show that when the GPS signal is available, the position accuracy of low cost SINS/GPS integration is same as that of GPS only. With the complete loss of GPS signals, position error is shown to be less than 10 meters, after 10 seconds. From these results, we can conclude that although GPS and current low cost IMU integration cannot improve the absolute positioning accuracy, it has a high data update rate and can give motion information by SINS only when GPS is not available for a short time, such as in heavily forested areas, in urban centers, in buildings or underground.

Energy-aware probabilistic multiplier: design and analysis

Probabilistic CMOS is considered to be a promising technology for substantial energy savings for computing devices, such as DSPs and graphics chips. The basic principle is to relax the energy requirement by allowing possibly incorrect computation results. For devices with probabilistic components, energy should be assigned to each component wisely, in order to achieve a good trade-off between energy consumption and correctness of the outputs. Recently, a few schemes have been proposed for energy assignment of ripple-carry adders, which are often based on intuitive arguments. In the present paper, we extend the idea of energy assignment to probabilistic multipliers. We focus on a fundamental type of multipliers, known as array multipliers. We derive some analytical results. Guided by these results, we devise an energy assignment scheme. We also find that energy assignment for array multipliers and ripple-carry adders can be quite different, due to differences in their structures. To our best knowledge, our work here is the first attempt in the literature to consider energy assignment for multipliers. Some examples, including digital image enhancement, are presented to demonstrate the effectiveness of the proposed scheme.