Development of a Crisp Fuzzy-Like Controller Using Formula-Based and Vectorized Approaches

Simplifying of implementation of linear state feedback fuzzy controllers is investigated through the thesis. One of the most important problems in fuzzy controller design is the number of fuzzy subsets (membership functions) for each fuzzy input/output variable. The number of fuzzy subsets and consequently the number of fuzzy rules should be big enough to achieve good approximation of control surface and have a smooth and robust control. However as the number of rules increases, the memory space, and program cycle time and total project cost will also increase dramatically. The thesis proposes crisp-fuzzy like controller derived by two novel approaches. The first one which is formula based crisp fuzzy-like controller proves that the monotonic fuzzy controller is similar to nonlinear saturated controller and then represents several different controller formulas. The second controller namely vectorized crisp fuzzy -like controller maps the fuzzy variables in a vectorial space and derives formula that has the structure similar to PID controllers. The proposed controllers are inspired from fuzzy logic where they can express the control law semantically but they are absolutely crips.Consenquently the needed memory space is minimizes since the rule table has been replace with the formula. On the other fuzzy controllers have high computational complexity while the new controllers are very simple to design, tune and implment.some new performance indexes also are porposed to evaluate the performance and stability of different controllers. Several well-known industrial models are used for simulation and a dimmer circuit to control the bulb temperature,has been used as a case study. Both simulation and experimental results show that the crips - fuzzy like controllers have the same or in some cases better performance and stability compare with the conventional fuzzy logic controllers, with extra merits of lower memory space and cycle time

Decentralized Hybrid Formation Control of Unmanned Aerial Vehicles

This paper presents a decentralized hybrid supervisory control approach for a team of unmanned helicopters that are involved in a leader-follower formation mission. Using a polar partitioning technique, the motion dynamics of the follower helicopters are abstracted to finite state machines. Then, a discrete supervisor is designed in a modular way for different components of the formation mission including reaching the formation, keeping the formation, and collision avoidance. Furthermore, a formal technique is developed to design the local supervisors decentralizedly, so that the team of helicopters as whole, can cooperatively accomplish a collision-free formation task

Cooperative tasking for multi-agent systems

Ph.DDOCTOR OF PHILOSOPH

Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering

The detection performance of maritime radars is restricted by the unwanted sea echo or clutter. Although the number of these target-like data is small, they may cause false alarm and perturb the target detection. K-distribution is known as the best fit probability density function for the radar sea clutter. This paper proposes a novel approach to estimate the parameters of K-distribution, based on fuzzy Gustafson–Kessel clustering and fuzzy Takagi–Sugeno Kang modelling. The main contribution of the proposed method is the ability to estimate the parameters, given a small number of data which will usually be the case in practical applications. This is achieved by a pre-estimation using fuzzy clustering that provides a prior knowledge and forms a rough model to be fine tuned using the least square method. The algorithm also improves the calculations of shape and width of membership functions by means of clustering in order to improve the accuracy. The resultant estimator then acts to overcome the bottleneck of the existing methods in which it achieves a higher performance and accuracy in spite of small number of data

Universal controller for monotone systems inspired from fuzzy logic control

This paper starts with formulation of monotone fuzzy system and then proposes a formula based universal controller for class of monotone systems which is inspired from fuzzy logic control by extending the number of fuzzy sets into infinity. After taking the limit, the fuzzy rule table is replaced by an explicit formula and consequently the needed memory space is minimized. It is shown that this controller can be approximated by a linear state feedback controller followed by a nonlinear saturation function. Furthermore, the optimal control solution and global asymptotic stability for a monotone control system are shown. The experimental results show that the crisp fuzzy-inspired controllers have the same or in some cases better performance and stability with extra merit of lower memory space and cycle time

Fault-tolerant Cooperative Tasking for Multi-agent Systems

A natural way for cooperative tasking in multi-agent systems is through a top-down design by decomposing a global task into sub-tasks for each individual agent such that the accomplishments of these sub-tasks will guarantee the achievement of the global task. In our previous works [1], [2] we presented necessary and sufficient conditions on the decomposability of a global task automaton between cooperative agents. As a follow-up work, this paper deals with the robustness issues of the proposed top-down design approach with respect to event failures in the multi-agent systems. The main concern under event failure is whether a previously decomposable task can still be achieved collectively by the agents, and if not, we would like to investigate that under what conditions the global task could be robustly accomplished. This is actually the fault-tolerance issue of the top-down design, and the results provide designers with hints on which events are fragile with respect to failures, and whether redundancies are needed. The main objective of this paper is to identify necessary and sufficient conditions on failed events under which a decomposable global task can still be achieved successfully. For such a purpose, a notion called passivity is introduced to characterize the type of event failures. The passivity is found to reflect the redundancy of communication links over shared events, based on which necessary and sufficient conditions for the reliability of cooperative tasking under event failures are derived, followed by illustrative examples and remarks for the derived conditions.Comment: Preprint, Submitted for publicatio

Minimum rule-based parallel structure fuzzy controller

One of the most important issues in fuzzy logic controller design is the number of fuzzy subsets for inputs and outputs. The number of fuzzy terms should be big enough to achieve sufficient approximation and must be small enough to save the space of memory. There is a trade off between approximation and memory space (algorithm cycle time). This paper proposes a simple parallel structure of fuzzy controllers where simulation is performed on a real temperature model. It can be shown that the proposed parallel structure fuzzy controllers has the same performance and stability compared with the conventional fuzzy controller, with an advantage of significantly lower number of rules. This can save memory space and reduces cycle time which is an important element in practical implementation problems