Lara S. Crawford

Optimal tracking with feedback-feedforward control separation over a network

This paper studies tracking of a reference path in a networked control system where the controller consists of a central decision maker and an on-site controller, which are connected through a discrete noiseless channel. The reference path is available noncausally to the central decision maker and the on-site controller has access to noisy observations from the plant and the reference information provided by the central decision maker. For a quadratic optimization objective, we provide the optimal control using dynamic programming and show that the optimal controller can be separated into a noncausal feedforward term (generated by the central decision maker) plus a feedback term (generated by the on-site controller) which has causal access to the controls applied without any loss of performance. We show that the feedforward control is the solution of a deterministic quadratic program, i.e., certainty equivalence holds. We later study the problem of transmission of the feedforward controls to the on-site controller over a discrete noiseless channel. We formulate and solve an optimization problem for the optimal time-varying and time invariant uniform quantization of the feedforward control signals sent by the central decision maker to the on-site controller over a communication network

A general constraint-based control framework with examples in modular self-reconfigurable robots

In this paper, we advocate a general constraint-based control framework that is highly promising for building control systems with complex dynamic structures, such as modular self-reconfigurable robots. In this framework, a controller consists of constraint solving components distributed in a network of embedded processors. Constraint solvers are goal oriented deliberative agents that can be used as control regulators or as information retrievers. The framework is built on the attribute/service model (ASM), a middleware for coordinating actuators, sensors and tasks in distributed real-time embedded systems. The communications and coordination among the services are realized via shared attributes. Examples of controlling a modular self-reconfigurable robot are illustrated in the paper.

Synchronized control in a large-scale networked distributed printing system

As engineered systems that have traditionally been controlled centrally become more modular, distributed, and autonomous, techniques are needed to maintain control coordination among independent elements, often across a network with delays and bandwidth limitations. In particular, manufacturing systems may require tight coordination, or synchronization, among components acting on the same physical object. This paper addresses the problem of controller synchronization in such a system. We present an implementation of exact controller synchronization for independent controllers in a highly modular printing domain. Our approach, which allows networked controllers to join and leave a task dynamically, has produced excellent results on a high-speed printer prototype.

Coordinated control for highly reconfigurable systems

The remarkable drop in the cost of embedded computing, sensing, and actuation is creating an explosion in applications for embedded software. As manufacturers make use of these technologies, they attempt to reduce complexity and contain cost by modularizing their systems and building reconfigurable products from simpler but smarter components. Of particular interest have recently been highly reconfigurable systems, i.e., systems that can be customized, repaired, and upgraded at a fine level of granularity throughout their lifetime. n nHigh reconfigurability is putting new demands on the software that is dynamically calibrating, controlling, and coordinating the operations of the systems modules. There is much promise in existing software approaches, in particular in model-based approaches; however, current techniques face a number of new challenges before they can be embedded in the kind of real-time, distributed, and dynamic environment found in highly reconfigurable systems. Here, we discuss challenges, solutions, and lessons learned in the context of a long-term project at PARC to bring such techniques to a highly reconfigurable paper path system.

Efficient waypoint tracking hybrid controllers for double integrators using classical time optimal control

This paper is a response to requests from several respected colleagues in academia for a careful writeup of the classical time-optimal control based hybrid controllers that we have been using for material transport control in our modular reconfigurable manufacturing systems application. Specifically, we show how classical closed form time optimal control, which exploits the special structure of double integrator systems (ie ones with point-mass Newton¿s Law dynamics) can be used to design hybrid controllers for waypoint tracking. While double integrator dynamics are very simple, they are extremely prevalent in many domains, beyond manufacturing systems, eg, transportation, disk drives, robotics, and aerospace. We present two methods, one which will track general way point specs, and another which will track waypoints that lie on convex or concave trajectories. Both approaches are based on appropriate setting (switching) of the state of a reference generator with the same point mass dynamics in a two-degree-of-freedom controller topology. The techniques we present admit very compact implementations, suitable for use in low cost micro controllers and DSP chips used in modular reconfigurable embedded systems applications. Since these controllers were to be integrated with a discrete planner, as part of the control software of a large complex new research platform, every effort was made to keep the controllers as simple as possible. Our controllers can be viewed as examples of basic hybrid controllers that are being used successfully in practice, and can be used as benchmarks by controls researchers for more sophisticated hybrid control design methods.

A new constraint test-case generator and the importance of hybrid optimizers

In the past decade, significant progress has been made in understanding problem complexity of discrete constraint problems. In contrast, little similar work has been done for constraint problems in the continuous domain. In this paper, we study the complexity of typical methods for non-linear constraint problems and present hybrid solvers with improved performance. To facilitate the empirical study, we propose a new test-case generator for generating non-linear constraint satisfaction problems (CSPs) and constrained optimization problems (COPs). The optimization methods tested include a sequential quadratic programming (SQP) method, a penalty method with a fixed penalty function, a penalty method with a sequence of penalty functions, and an augmented Lagrangian method. For hybrid solvers, we focus on the form that combines two or more optimization methods in sequence. In the experiments, we apply these methods to solve a series of continuous constraint problems with increasing constraint-to-variable ratios. The test problems include artificial benchmark problems from the test-case generator and problems derived from controlling a hyper-redundant modular manipulator. We obtain novel results on complexity phase transition phenomena of the various methods. Specifically, for constraint satisfaction problems, the SQP method is the best on weakly constrained problems, whereas the augmented Lagrangian method is the best on highly constrained ones. Although the static penalty method performs poorly by itself, by combining it with the SQP method, we show a hybrid solver that is significantly better than any of the individual methods on problems with moderate to large constraint-to-variable ratios. For constrained optimization problems, the hybrid solver obtains much better solutions than SQP, while spending comparable amount of time. In addition, the hybrid solver is flexible and can achieve good results on time-bounded applications by setting parameters according to the time limits.

Synchronization of State Based Control Processes with Delayed and Asynchronous Measurements

This paper addresses the problem of controller state synchronization in a networked control system with distributed sensing and actuation, where actuators must hand off and switch controllers on the fly as they go from performing one task to another, in the presence of fixed communication delays and asynchronous measurements. We present a technique that enables new controllers to seamlessly join and leave a task, by encapsulating the controller in a finite state machine that handles the synchronization. We also discuss issues related to the real-time implementation of this technique and we finish with a demonstration on an example from the document printing domain.

Control in printing systems: Modular reconfigurable media paths

The remarkable drop in the cost of embedded computing, sensing, and actuation is creating a corresponding explosion in the use of these technologies in new systems. In order to reduce complexity and contain costs, manufacturers are moving toward modularizing their systems and building reconfigurable products from simpler but smarter components. Of particular interest have recently been highly reconfigurable systems, i.e., systems that can be customized, repaired, and upgraded at a fine level of granularity throughout their lifetime. High reconfigurability puts new demands on the dynamic calibration, control, and coordination software in the system. There is much promise in existing software approaches, but current techniques face a number of new challenges before they can be embedded in the kind of real-time, distributed, and dynamic environment found in highly reconfigurable systems. In this tutorial paper, we will discuss challenges, solutions, and lessons learned in the context of a long-term project at PARC to bring such techniques to a highly reconfigurable paper path system.

Towards printing as an electronics manufacturing method: Micro-scale chiplet position control

We address the problem of position control of micro-chips (chiplets) immersed in dielectric fluid. An electric field, shaped by controlling the voltages of spiral shaped electrodes, is used to reliably and accurately transport and position chiplets using dielectrophoretic forces. A lumped, capacitive based (nonlinear) motion model is used to generate an open loop control policy. The open loop policy is generated using a one step model predictive control approach. By exploiting the spatial symmetry and periodicity of the open loop control solution, a real-time control scheme is designed by applying simple algebraic operations to a base function defined on a finite domain. The chiplet position is tracked using image processing algorithms. We demonstrate the validity of our approach by describing an experimental result, where real-time control is used to move a chiplet for 1000µm in a controlled manner.

On-Line Reconfigurable Machines

A recent trend in intelligent machines and manufacturing has been toward reconfigurable manufacturing systems, which move away from the idea of a fixed factory line executing an unchanging set of operations, and toward the goal of an adaptable factory structure. The logical next challenge in this area is that of on-line reconfigurability. With this capability, machines can reconfigure while running, enable or disable capabilities in real time, and respond quickly to changes in the system or the environment (including faults). We propose an approach to achieving on-line reconfigurability based on a high level of system modularity supported by integrated, model-based planning and control software. Our software capitalizes on many advanced techniques from the artificial intelligence research community, particularly in model-based domain-independent planning and scheduling, heuristic search, and temporal resource reasoning. We describe the implementation of this design in a prototype highly modular, parallel printing system.