Gordon K. F. Lee

Decentralized control of large scale systems with dynamic interconnected subsystems

Two algorithms for decentralized control of large scale systems with dynamic interconnected systems are presented. These algorithms are based upon two controller configurations and result in the optimization of a regulator-type performance measure. The approach is computationally attractive in that existing Ricatti matrix solutions may be directly applied. Furthermore, these algorithms may perform well even under small system parameter variation or system disturbance. Examples are provided to illustrate the method.

A pole assignment algorithm for multivariable control systems

A general compensation design algorithm for pole assignment is considered. The methodology presented is an extension of previous work [10] in which plant and compensator dynamics are described in such a way that the influence of compensation on the poles of the system is directly observed. By holding some of the poles of the plant and compensator stationary at each iteration, the design problem is transformed into an equivalent multi-input, single-output system to which root locus techniques can be directly applied. The design algorithm is iterative in nature and allows the designer the freedom to use his expertise within a standardized framework. An example of a general compensation problem is given to illustrate the simplicity of the design method.

Pole assignment via optimization methods

The design of multivariable systems can be approached with many different design objectives. An appealing approach from a mathematical point of view is to describe the dynamics of plant and compensator in state-spaco form, transform the resulting augmented system into a problem involving a system performance index such as pole assignment, and apply optimization techniques to choose compensator parameters. This paper develops a methodology whereby exact or partial pole assignment under variations of plant characteristics is incorporated into the system performance index. Through calculations of the gradients of the performance index with respect to compensator parameters, one is able to apply derivative optimization methods to the design problem. Examples are provided to illustrate the design methodology.

Decentralized control of discrete-time large-scale systems by dynamic programming

A decentralized control algorithm for discrete-time large-scale systems with dynamic interconnections and external disturbances is presented. The method is based upon minimization of a discrete linear regulator performance measure and application of the principle of optimality. A suboptimal control law may be found by applying an approximation to the design. An example of a three-reach river pollution control problem is presented to illustrate the algorithm.

Robustness Investigation of Adaptive Control Under Reference Model Switching for a Cylindrical Robot

Space robots are expected to play a significant role in future space missions. This requires a thorough investigation into the capabilities of such robots. A typical task that will need to be performed by the space robot is the capture and manipulation of large objects. This could increase the mass of the robot by as much as 100%. Additionally, the object capture task will require the robot to handle high dynamic disturbance. The control system of the robot must maintain stability under these harsh conditions. In this paper, the authors have conducted an investigation into the robustness properties of a new robot control strategy based on the Direct Model Reference Adaptive Control (MRAC) Algorithm under switching of the reference model. Experimental results of the investigation are presented for a three degree-of-freedom cylindrical robot. The new control scheme is demonstrated to be a powerful approach to the difficult problems that will be encountered in space robotics control.

ON THE DESIGN OF ROBUST CONTROL SYSTEMS FOR DISTILLATION COLUMNS

Abstract The distillation column dynamics is very nonlinear, especially at high purity. Multivariable control system designs, which are essentially linear, may not be able to perform well at different operating conditions. This paper looks at three different multivariable design techniques—decoupling control, optimal state feedback and pole assignment as applied to distillation column control. Robustness of these techniques are analyzed by looking at the performance of these controllers at different operating conditions. Some interesting results are obtained.

Obstacle Avoidance for a Robotic Arm Employing Real-Time Expert System Techniques

Typically a robot cannot handle a situation in which it has to avoid a random obstacle in its path. This paper discusses an approach for on-line obstacle avoidance using a real-time expert system. The method relies on an algorithm which employs a one-step optimization with N-step lookahead and global linearization. The system receives input data from a vision system, which is used to identify the obstacles and their shape. An expert system observes the movements of the robot and takes over the control when there is a possibility of collision. The system employs the concept of focusing, moving faster when there is space, and slowing down to give more time to solve the problem of bypassing when operating space is restricted.

On The Approximate Decoupling Of Linear Stochastic Systems

In this paper, the decoupling problem for systems with additive noise is addressed. The decoupled model is initially constructed in the absence of noise. By imbedding feedforward and constant o utput feedback matrices into a control structure, a performance index can be formulated, representing an error between the output of a desired model and the output o f the actual system. Optimization of this performance measure results in the parametric design for the feedback and feedforward matrices which decouple the system in spite of external noise d isturbances.

Pole Assigmunt In Linear Time-varying Systeks Using State Feedback

This paper addresses the pole assignment problem in linear time-varying systems using state feedback. Two algorithms for computing the state gain feedback are developed and examples are provided to illustrate these approaches.

Discrete-time decentralized optimal controllers for multimachine power systems

Decentralized compensation of large-scale power systems has the appealing feature that local substations may be controlled by a small subset of state or output variables. In this paper, the problem of decentralized control by discrete-time compensation is addressed. By formulating the dynamics of each subsystem and including the interaction terms with other subsystems, a performance measure is constructed, based upon local desired system performance. This resulting controller is optimal, even if the subsystems are strongly coupled. An example using a 10-machine power system is provided to illustrate the improvement of the system response to faults when compared to classical excitation control.